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In working on the project for the University of Edinburgh, our team from Code Your Future is thrilled to present our project, ‘Crowdsourcing User Judgements for Gaelic Normalisation’. Aimed at Gaelic speakers, this project will collect user inputs on passages of historical Gaelic writing that have been updated to modern orthography by an AI model developed by the University of Edinburgh. Through hard work, collaboration, innovation and problem-solving, we have hugely enhanced a previous research project, ‘An Gocairː An Automatic Gaelic Standardiser’ and not only met but exceeded our goals.
The ‘An Gocair’ Web App
Our team used the PERN stack as it uses a common framework and program language so it can be easily modified to enhance user experience and interactions in the future. In today’s globalised world, it is useful to be able to launch this application from any device and location. We have admin features in our application to give researchers more control over the data, and user sign-in features that allow users to sign in from social media accounts. Throughout the project, there were challenges in terms of adhering to project requirements. Those challenges were an opportunity for us to learn. So we valued our team members’ creativity, experimentation and unique skills to find solutions to the problems that aligned with our project objective.
The Reinforcement Learning with Human Feedback App – for crowdsourcing Gaelic speaker judgements on AI-corrected texts
Our project followed an agile mindset that prioritises interactions, customer collaborations and responsiveness to change. As a result, we adapted agile values and principles focusing on short development cycles like creating simpler tasks, allocating them to the team members and receiving constant feedback from the team lead. Also, the agile approach helped us to manage time efficiently through sprint planning, daily standup meetings and optimising our time allocation and productivity.
By using React we have made every feature into a component so it can be easily modified in the future. By using the Passport module we have made the application more secure. Implementing it into the application was a challenge, however, and took a lot of the time. Before coming up with the passport, we tried a few different authentication tools but they did not give us the ability to be used as login with other social media accounts.
Our project relies on data and the Postgres database management system is useful for storing and managing our data efficiently. Our database Schema design considers scalability in mind to handle a growing dataset and increased user load. We also implemented proper encryption and access control, to protect users’ data and maintain user privacy through admin features.
As the Decoding Hidden Heritages project is nearing the end of its digitisation and metadata collection stage, this is a good opportunity to share some insights from the project on the importance of archival work for the representation of women’s heritage. While the project’s main focus is on the narrative traditions of Scotland and Ireland, valuable information has also been discovered that has wider cultural implications, such as the influence of gender on narrative traditions. These discoveries have been made possible by the digitisation process because it has allowed a re-examination and re-documentation of the archive’s collection. As part of this process at the School of Scottish Studies Archives, I have been able to employ what Prof Melissa Terras terms feminist digitisation practices, which ‘are both an attitude, and an application of technology in an efficient way’.[1] She described this practice as ‘an act of owning women’s history, using digital means, to collate information and histories that the mainstream – for whatever reason – has not tackled’.[2] For this project, that has involved ensuring that women’s material in the archive is accessible to and discoverable by the public through digitisation and accurate metadata collection.
While digitising the Tale Archive I discovered several unique factors that affected women’s presence, or rather their absence, in the archive. In particular, I noticed distinct documentation issues with the archive’s material relating to women. The most significant of these issues was the erasure of women’s names in archival documents and metadata.
There are four distinctive scenarios in which women’s names have been erased:
The documents lack women’s first names.
The most common erasure of women’s names in the archive is the use of only women’s surnames, particularly their married surnames, for example Mrs. Stewart. In SSSA_TA_WT042_001 the informant is only listed as Bean Sheumais (‘Wife of James’). This is most likely because that was how these women would have given their names to the collectors, as was the social practice at the time.
Their husband’s full name is used in lieu of women’s names.
The next most common form of women’s names is their husband’s full name used as their married name, for example Mrs. John MacDonald. In some cases, married women’s first names have been discovered and their full names are included in the metadata. For example, Mrs. Hugh Milne has been recorded as Bella Milne in the project database.
The influence of gender on the documentation of names in these records is made clear in SSSA_TA_GH013_001. The metadata for this transcription records the informant as ‘Andrew Stewart and family’ but the document itself listed it as Mrs. Andy Stewart. Despite the fact that this story is told by Mrs. Stewart about her own experience with a ghost, the metadata recorded her husband as the main informant, erasing Mrs. Stewarts’ ownership over her story. When her husband and son interject into her story, the transcript states ‘Carol Stewart, their son, takes over’ and ‘Andrew takes over’ but, rather than use her full name, it says that the ‘story returns home to Mrs. Stewart’. Each of the male members of the Stewart family have their full names recorded while Mrs. Stewart does not. As a result of re-examining this material, the metadata has been corrected and Mrs. Stewart’s story is now properly recognised in the archive.
The names are unrecorded.
In much of the material, women have shared their stories anonymously. This makes it impossible to document who they are. Women are often referred to as ‘girls’ such as ‘Barra Girl’ (SSSA_TA_GH002_002) or ‘a girl who was native of Glenurqhart’ (SSSA_TA_WT043_002) without their names recorded. Yet, even in these cases it is still important to document the informant’s gender in the metadata. For example, one informant was listed as a ‘Native of Lochcarron’ in SSSA_TA_WT037_015. However, by reading their story it can be ascertained this person was a woman, because she states, ‘when they sent me … I was a young girl at the time’. By documenting their gender in the metadata, at least we are able to accurately acknowledge these women’s presence in the archive.
They are not named in the archive’s metadata but are present in documents.
One of the most significant examples of a woman’s erasure from the archive is SSSA_TA_FL025. This document and its metadata records Walter Johnson as the informant of a transcription. However, the transcription is actually of Bella Higgins telling her personal experience of meeting a fairy [Ed. noted here using the dated and offensive term ‘golliwog’]. Even though it is only Bella speaking, her story had been attributed to Walter Johnson. As a consequence of this incorrect documentation, her voice had been hidden in the archive.
Similarly, in a series of transcriptions by John Stewart and his wife Maggie Stewart (SSSA_TA_GH001_022, 23, 25), John was recorded as the only informant. Even though Maggie was present in them as well, her contributions to their stories were unrecognised. As a result of the careful examination of these documents while they were digitised, these women’s contributions were uncovered and are now appropriately documented in the collection’s metadata.
While in some cases these documentation issues may seem small, they have significant consequences. Women’s names being unrecorded or partially recorded in the archives makes tracing women’s histories and family lineages extremely difficult and often impossible. For example, it is impossible to ascertain from the documentation whether a woman recorded as Mrs. MacDonald is the grandmother, mother, wife or sister-in-law to Mr. John Macdonald because all these women would have been referred to identically. Similarly, when women have no name recorded at all, their contributions to the archive are unidentifiable.
The exclusion of these women misrepresents the material within our archives, presenting the collection as more male dominated than it is. Not only is their re-inclusion into the archive’s metadata important as an act of justice for these women, but it also enriches and expands the historical research and data that can be produced from the archive. As historians Andrew Flinn, Mary Stevens, and Elizabeth Shepherd have argued, ‘the archives that are “chosen” for survival, the terms in which they are described, and the processes by which these decisions are made, do ultimately impact on the collective memory and public histories that are produced from them’.[3]
This is particularly important in the context of the increasing trend in historical research, where historians seek to write women who have been hidden in accounts back into history. A recent example of this is a biography of George Orwell’s wife, ‘Wifedom: Mrs. Orwell’s Invisible Life’ by Anna Funder. She points out that in Orwell’s novel Homage to Catalonia, written while Orwell and his wife were in Spain, he ‘mentions “my wife” 37 times but never once names her. No character can come to life without a name’.[4] However, Funder was able to reconstruct the life of Eileen when she went ‘back to the biographers’ footnotes and sources and into the archives and found details that had been left out. Eileen began to come to life’.[5] Thus, there is immense value in archival sources which is still being discovered today and archivists play a vital role in ensuring that women’s history in these archives does not remain hidden. It is therefore important to seize the opportunity that digitisation projects such as this present to employ feminist digitisation practices on archival collections to uncover women’s hidden histories and ensure their posterity for the future.
The DHH team would like to thank Catherine for her important and timely blog and her excellent contributions to the project.
Bibliography
Flinn, Andrew, Mary Stevens, and Elizabeth Shepherd. “Whose Memories, Whose Archives? Independent Community Archives, Autonomy and the Mainstream”. Archival Science 9, no. 1-2 (2009)
Funder, Anna. “Looking for Eileen: how George Orwell wrote his wife out of his story”. The Guardian, 30 July 2023. Accessed 4 October 2023. https://www.theguardian.com/books/2023/jul/30/my-hunt-for-eileen-george-orwell-erased-wife-anna-funder.
Melissa Terras. “Interview With Professor Melissa Terras On Feminist Digitisation Practices And The Future Of Our Digital Cultural Heritage”. The University Of Edinburgh Futures Institute, 6 January 2023. Accessed 4 October 2023. https://efi.ed.ac.uk/interview-with-professor-melissa-terras-on-feminist-digitisation-practices-and-the-future-of-our-digital-cultural-heritage/.
[1] Melissa Terras, “Interview With Professor Melissa Terras On Feminist Digitisation Practices And The Future Of Our Digital Cultural Heritage”, The University Of Edinburgh Futures Institute, 6 January 2023, accessed 4 October 2023. https://efi.ed.ac.uk/interview-with-professor-melissa-terras-on-feminist-digitisation-practices-and-the-future-of-our-digital-cultural-heritage/.
[3] Andrew Flinn, Mary Stevens, and Elizabeth Shepherd, “Whose Memories, Whose Archives? Independent Community Archives, Autonomy and the Mainstream”, Archival Science 9, no. 1-2 (2009): 76.
[4] Anna Funder, “Looking for Eileen: how George Orwell wrote his wife out of his story”, TheGuardian, 30 July 2023, accessed 4 October 2023. https://www.theguardian.com/books/2023/jul/30/my-hunt-for-eileen-george-orwell-erased-wife-anna-funder.
Our own Prof Will Lamb is working with Dr David Howcroft (lead investigator) and Dr Dimitra Gkatzia from Edinburgh Napier university to build the first tools for Gàidhlig chatbots. This is starting with the creation of a new dataset to train AI models.
Our current experiments (which you can participate in if you speak Gàidhlig!) are focused on building our dataset: we need examples of humans asking and answering questions about museum exhibits in a chat conversation. Participants are paired up and given a set of exhibits from the National Museum of Scotland to discuss, briefly summarising their discussions as well.
The next step? Well, after a bit of data cleanup and anonymisation, it’s time to see how well neural network models for natural language generation work for this amount of data. One of the interesting challenges for this project is trying to see how far you can get in building a chatbot with as little data as possible. The lessons we learn in this work will inform future work, not just in Scottish Gaelic, but in Natural Language Generation more generally!
Why build chatbots for Scottish Gaelic?
We believe the world is a better place when everyone can learn in their preferred language. Scottish Gaelic has fewer language technologies available than languages like English or Mandarin, and we’d like for our research in natural language generation to help in some small way to address this gap.
Why focus on ‘Exhibits’?
Museums are a primary tool for learning outside of schools, libraries, and documentaries, and are increasingly leveraging mobile applications and chatbots to enhance visitor experiences. However, these chatbots are generally available for only a few languages, due to a lack of linguistic and technical resources for minority languages like Scottish Gaelic.
How can I contribute?
If you speak Scottish Gaelic and live in Scotland, you can take our short comprehension quiz (5-10 minutes) and sign up to participate in the study! The full study (after the quiz) takes up to two hours to complete, and participants will receive up to £30 in compensation for their contribution. Additionally, you’ll have the opportunity to be named as contributing to this important Gaelic resource if you so desire! More details here: https://nlg.napier.ac.uk
If you don’t speak Scottish Gaelic or live outside of Scotland, you can share this blogpost with all the Gaelic speakers you know! Encourage them to participate or to spread the word to their friends. All in all, we hope to recruit about 100 people to participate in our study, and we have a ways to go before we reach this goal. If you don’t know what to say to your contacts, how about:
Researchers in Edinburgh are trying to build the first chatbots for Scottish Gaelic and they’re recruiting participants for an experiment paying up to £30! Find out more at: https://blogs.ed.ac.uk/garg/2022/08/23/scottish-gaelic-chatbots-for-museum-exhibits/ or sign up at https://nlg.napier.ac.uk
For an automatic translation into English, click here. For a version in Irish, click here.
15 Am Faoilleach 2022
Ùghdar: Dr Andrea Palandri, Rannsaiche Iar-Dhotaireil
Andrea Palandri
As t-samhradh 2021, fhuair Gaois maoineachadh fo sgeama AHRC-IRC gus pròiseact a thòiseachadh air a’ Phrìomh Chruinneachadh Làmh-sgrìobhainnean bho thasg-lann Coimisean Beul-aithris na h-Èireann (Cumann Béaloideasa Éireann, University College Dublin). Canar Decoding Hidden Heritages ris a’ phròiseact seo. Is e cuspair a’ bhlog seo an obair dhigiteachaidh a tha a’ dol air adhart mar phàirt den phròiseact air làmh-sgrìobhainnean a’ Phrìomh Chruinneachaidh.
Thathas a’ meas gu bheil timcheall air 700,000 duilleag làmh-sgrìobhainn anns a’ Phrìomh Chruinneachadh Làmh-sgrìobhainnean, ga fhàgail mar aon de na cruinneachaidhean as motha de stuth beul-aithris air taobh an iar na Roinn Eòrpa. Bhiodh seo air a bhith na dhùbhlan mòr airson digiteachadh mura biodh Transkribus air teicneòlas AI airson aithne làmh-sgrìobhaidh a leasachadh thar nam beagan bhliadhnaichean a dh’fhalbh. Tha Decoding Hidden Heritages gu mòr an urra air an teicneòlas seo agus leigidh e leis a’ phròiseact a innealan-aithne làmh-sgrìobhaidh fhèin a dhèanamh stèidhichte air sgrìobhadairean sònraichte sa chruinneachadh.
On a thòisich ar luchd-rannsachaidh a bhith ag obair leis a’ bhathar-bog Transkribus tràth san Dàmhair, tha sinn air trì innealan làmh-sgrìobhaidh aithnichte a dhèanamh a tha ag obair aig ìre mionaideachd nas àirde na 95%: aon airson Seosamh Ó Dálaigh, aon airson Seán Ó hEochaidh agus aon airson Liam Mac Coisdealbha, trì de an luchd-cruinneachaidh as dealasaiche a bha ag obair don Choimisean.
Figear 1 (Clí) Seosamh Ó Dálaigh a’ cruinneachadh beul-aithris bho Tomás Mac Gearailt (Paraiste Márthain, Corca Dhuibhne) agus (deas) làmh-sgrìobhainn a sgrìobh e bho chlàradh a rinn e de Tadhg Ó Guithín (Baile na hAbha, Dún Chaoin, Corca Dhuibhne) ga ath-sgrìobh ann an Transkribus.
Tha Transkribus feumail air tar-sgrìobhadh ceart a rèir duilleag na làmh-sgrìobhainne – a rèir làmh-sgrìobhadh agus dual-chainnt an neach-cruinneachaidh – gus an einnsean a thrèanadh. An dèidh a bhith ag aithneachadh timcheall air leth-cheud duilleag san dòigh seo, thrèan sinn modal làmh-sgrìobhaidh aig ìre gu math èifeachdach (90% +). Is e dòigh-obrach a’ phròiseict na dhèidh seo ath-sgrìobhadh a dhèanamh air àireamh mhòr de dhuilleagan gu fèin-ghluasadach agus luchd-taic rannsachaidh (Emma McGee, Kate Ní Ghallchóir agus Róisín Byrne) a chur gan ceartachadh mean air mhean. Na dhèidh sin, faodaidh sinn na modailean a dh’ath-thrèanadh air stòr-dàta nas fharsainge gus modalan cànain nas fheàrr (~ 95%) a fhaighinn. Tha toraidhean eadar-amail na h-obrach seo a’ toirt dòchas dhuinn gum bi e comasach don phròiseact ìre mionaideachd nas àirde a choileanadh anns na mìosan a tha romhainn, a leigeas leinn a bhith ag ath-sgrìobhadh gu fèin-ghluasadach mòran den Phrìomh Chruinneachadh Làmh-sgrìobhainnean cha mhòr thar oidhche.
Figear 2 An lúb ionnsachaidh de mhodalan cànain a chaidh a dhèanamh le Transkirbus gu ruige seo: Seán Ó Dálaigh (clí), Seán Ó hEochaidh (meadhan) agus Liam Mac Coisdealbha (deas).
Tha làmh-sgrìobhainnean a’ Phrìomh Chruinneachaidh am measg nan teacsaichean as motha anns a bheil lorg nan dual-chainntean ann an corpas litreachas Gaeilge an latha an-diugh. Is e dòigh-obrach agus dòighean deasachaidh Shéamuis Ó Duilearga fhèin a tha a’ nochdadh ann an Leabhar Sheáin Í Chonaill. Bhrosnaich agus stèidhidh e Comann Beul-aithris na hÈireann ann an 1927 agus chan eil mìneachadh nas fheàrr air an dòigh-obrach seo na na faclan a sgrìobh Séamus Ó Duilearga fhèin ann an ro-ràdh an leabhair:
Ní raibh ionnam ach úirlis sgríte don tseanachaí: níor atharuíos siolla dá nduairt sé, ach gach aon ní a sgrí chô maith agus d’fhéadfainn é.
Cha robh annam ach inneal sgrìobhaidh dhan t-seanchaidh: cha do dh’atharraich mi lide dhe na thuirt e, ach sgrìobh e a h-uile rud cho math ’s a b’ urrainn dhomh.
(S. Ó Duilearga, Leabhar Sheáin Í Chonaill, xxiv)
Cha deach mòran leabhraichean fhoillseachadh ann an litreachas na Gaeilge bhon uairsin a dh’fhuirich cho dìleas ri dual-chainnt an neach-labhairt ’s a rinn Leabhar Sheáin Í Chonaill: tha cruthan dualchainnteach mar bheadh saé an àite bheadh sé (bhiodh e), no buaileav an àite buaileadh (chaidh a bhualadh) no fáilthiú an àite fáiltiú (fàilteachadh). Mar sin, tha cànan nan làmh-sgrìobhainnean anns a’ Phrìomh Chruinneachadh a’ taisbeanadh dual-chainnt, no eadhon ideo-chainnt, an luchd-fiosrachaidh gu làidir. Mar eisimpleir, bidh claonadh dual-chainnte, do raibh an àite go raibh (gun robh) ga ràdh; bha sin aig cuid de dhaoine à Corca Dhuibhne ann an Chonntaidh Chiarraí, m.e. anns na sgeulachdan a sgrìobh Seosamh Ó Dálaigh bho Thadhg Ó Guithín (Baile na hAbha, Dún Chaoin).
Figear 3 Thug Diarmuid Ó Sé iomradh air an iongantas dualchaint seo ann an Gaeilge Chorca Dhuibhne (§619)
Tha làmh-sgrìobhainnean a’ chruinneachaidh seo car neònach air sàillibh nan cruthan beaga dual-chainnteach a chlàraich an luchd-cruinneachaidh fhad ’s a bha iad gan ath-sgrìobhadh. Is ann air sgàth an iomadachd cànain seo anns a’ chorpas nach eil am pròiseact ag amas air aon mhodail mòr a chruthachadh gus an Cruinneachaidh ath-sgrìobhadh air fad. A bharrachd air sin, chan e a-mhàin gu bheil sinn a’ dèiligeadh ri diofar dhual-chainntean ach tha sinn cuideachd a’ dèiligeadh ri diofar luchd-cruinneachaidh aig nach robh làmh-sgrìobhadh is litreachadh dhual-chainntean co-ionnan. Tha na duilgheadasan seo a’ fàgail gu bheil an corpas Gaeilge seo gu math measgaichte. Feumar dèiligeadh ris le cùram agus le taic bho leabhraichean dhual-chànanachais a bhios a’ toirt cunntas air na puingean beaga cànain a gheibhear ann.
Anns an t-sreath seo, tha sinn a’ toirt sùil air laoich a rinn adhartas cudromach ann an teicneolas nan cànanan Gàidhealach. Airson a’ cheathramh agallaimh, cluinnidh sinn bho Roibeart MacThòmais. Coltach ri Lucy Evans, the Rob air ùr thighinn gu saoghal na Gàidhlig. Chaidh fhastadh airson còig mìosan ann an 2021 mar phàirt de phròiseact a mhaoinich Data-Driven Innovations (DDI), far a robh an sgioba a’ cruthachadh teicneolas aithneachadh labhairt airson na Gàidhlig. Dh’obraich Rob air inneal coimpiutaireachd ùr-nòsach eile, An Gocair.
Nuair a bhios tu a’ feuchainn ri teicneòlas cànain a chruthachadh airson mhion-chànain, ’s e an trioblaid as bunasaiche ach dìth dàta. Chan eil an suidheachadh a thaobh na Gàidhlig buileach cho truagh ri cuid a mhion-chànanan eile, ach tha deagh chuid dhen dàta seann-fhasanta a thaobh dhòighean-sgrìobhaidh. Tha sin a’ fàgail nach gabh e cleachdadh gus modailean Artificial Intelligence a thrèanadh gun a bhith a’ cosg airgead mòr air ath-litreachadh.
Bidh An Gocair ag ath-litreachadh theacsaichean gu fèin-obrachail – tha e glè choltach ri dearbhadair-litrichidh. Chan eil ann ach ro-shamhla (prototype) an-dràsta agus tha sinn a’ sireadh taic a bharrachd airson a leasachadh. Aon uair ‘s gum bi e deiseil, b’ urrainnear a chur gu feum ann an iomadach suidheachadh, leithid foillseachadh, foghlam aig gach ìre, prògraman coimpiutaireachd eile agus rannsachadh sgoileireil. Cuiridh e gu mòr cuideachd ri pròiseact rannsachaidh ùr a tha a’ tòiseachadh an dràsta eadar còig oilthighean ann am Breatainn, Ameireaga agus Èirinn: ‘Decoding Hidden Heritages in Gaelic Traditional Narrative with Text-mining and Phylogenetics’.
In this interview series, we are looking at individuals who have significantly advanced the field of Gaelic, Irish and Manx language technology. For the fourth interview, we hear from Mr Rob Thomas. Like Lucy Evans, whom we interviewed a few months ago, Rob has come to the world of Gaelic language technology only recently. He was chosen from a strong field to work with us on project funded by Data-Driven Innovations (DDI), in which we were developing the world’s first automatic speech recogniser for Scottish Gaelic. Rob worked on an important strand of this project – developing a brand-new piece of software called An Gocair.
When trying to develop language technology for minority languages, the most fundamental problem is data sparsity. The situation for Gaelic is not as dire as for some other minority languages, but much of the textual data available is outdated in terms of orthography. That makes it impossible to train machine learning models – at least without spending a lot of money on editing spelling.
An Gocair re-spells texts automatically – it’s basically an unsupervised spell-checker with some extra bells and whistles. It is currently only a prototype, however, and we are seeking additional support for its development. Once completed, it will be able to be used in a wide range of contexts, including publishing, education at all levels, as part of other computer programs and within academic research. It will also make a significant contribution to a new research project currently underway between five universities in Britain, America and Ireland: ‘Decoding Hidden Heritages in Gaelic Traditional Narrative with Text-mining and Phylogenetics’.
Interview with Rob Thomas
Agallamh le Roibeart MacThòmais
Tell us a little bit about your background. For instance, where are you from, and what got you into language technology work?
Hello! I’m from a small town in South Wales called Monmouth. I grew up mostly in the countryside, quite far from civilisation. My interest in linguistics probably stems from having a fantastic English teacher in my high school. (Shout out to Mr Jones.) I don’t know if it was the content or how he taught it, but I remember at the time really enjoying the subject and his lessons.
Rob Thomas
I went on to study English Language and Linguistics at the University of Portsmouth. After graduating, I worked for a while at Marks and Spencer as I was not yet sure what kind of career I was looking for. Still kind of directionless, I spent a year and a bit traveling and on return began working in tech support. I managed to find a course in Language Technology at the University of Gothenburg, I had recently found a new interest in programming and this was a great way to merge my new interest and my academic foundation. After a few years living, studying and working in Sweden, I returned to the UK and began the job hunt and was lucky to find the position at the University of Edinburgh.
You mention studying language technology at the University of Gothenburg. What did you find most interesting about the course? Do you have any advice for someone who is thinking about studying language technology?
The course was fascinating and it attracted students from quite a broad background. The first meeting was like The Time Machine by H.G Wells: we were all introduced as the linguist or the mathematician, cognitive scientist, computer scientist, philosopher etc. I think what stood out is that language technology, as a field, relies on input and experience from a multitude of academical backgrounds. This is due to the complex nature of language. I think I would advise anyone who is not from a technical or STEM background to think about how important your knowledge and perspective is for the future of language-based AIs, systems and services. But if, like me, you do come from a humanities background be prepared to dive straight back in to the maths that you thought you managed to escape after you completed your GCSEs.
You are developing a tool for Scottish Gaelic that automatically corrects misspelled words and makes text conform to a Gaelic orthographical standard. That’s impressive for someone with Gaelic, and even more so for someone who doesn’t speak it. How did you manage to do this?
I am quite lucky to be supported by Gaelic linguists and other programmers. I found a way to integrate Am Faclair Beag, an online Gaelic dictionary developed by our resident Gaelic domain expert, Michael Bauer. Alongside the dictionary we translated complicated linguistic rules into something a computer could understand. We have managed to develop a program that takes a text and, line by line, attempts to identify spelling that don’t belong to the modern orthography and searches for the right word from our dictionary. If it has no luck, it then attempts to resolve the issue algorithmically. From the start I knew it was important that I was able to compare the program’s output to work done by Gaelic experts so that I could see whether I was improving the tool or just breaking it.
An Gocair
Since you’ve been born, you’ve seen language technology change and permeate how we work and live. What’s been your own experience of the changes that it has brought?
It has been very interesting witnessing the exponential growth of language technology in the mainstream. It wasn’t until I studied it that I realised how much it was already embedded in websites and services that I’ve been using for years. The more visible applications such as smart assistants are becoming much more normalised in our society. Even my grandma uses her smart assistant to turn on classic FM and put on timers which I think is really cool. My grandma is pretty tech savvy to be fair!
With the dominance of world languages in mass media and on the internet, some would say that technology is an existential threat to minority languages like Gaelic and Welsh. What do you think about this? Are there ways for minority languages to survive or even thrive today?
I think one of the issues in language technology is that most of the work is dedicated to languages that already have huge amounts of resources, for example English. Most of the breakthroughs are being made by large companies that ultimately aim to increase the value of their services. There are a lot of companies that sell language technology as a service (e.g. machine translation) rather than serving communities per se. The latter may not have direct monetary value, but it’s essential to keep that focus in order to allow minority languages to gain access to state-of-the-art technology.
What are your predications for language technology in the year 2050? If you had your own way, what would you like to see by that time?
I imagine smart assistants will be present in more spaces in society, perhaps even in a more official capacity. The county council in Monmouthshire already use a smart chatbot for questions about what days your bins are being collected. Imagine if they were given greater powers such as being able to make important decisions (scary thought). The more time goes on, the more I think we are going to end up with malevolent AIs like HAL from 2001, Space Odyssey, rather than ones like C3PO from Star Wars.
I’m not sure what I would like to see. It would be nice if there was more community-developed and open-source alternatives to what the main large tech companies provide, so a consumer would be able to be sure their data was being used in a safe and respectable way.
Decoding Hidden Heritages in Gaelic Traditional Narrative with Text-Mining and Phylogenetics
This exciting new three-year study is funded by the AHRC and IRC jointly under the UK–Ireland collaboration in digital humanities programme. It brings together five international universities, two folklore archives and two online folklore portals.
October 2021–Sept 2024
‘Morraha’ by John Batten. From Celtic Fairy Tales (Jacobs 1895)
Summary
This project will fuse deep, qualitative analysis with cutting-edge computational methodologies to decode, interpret and curate the hidden heritages of Gaelic traditional narrative. In doing so, it will provide the most detailed account to date of convergence and divergence in the narrative traditions of Scotland and Ireland and, by extension, a novel understanding of their joint cultural history. Leveraging recent advances in Natural Language Processing, the consortium will digitise, convert and help to disseminate a vast corpus of folklore manuscripts in Irish and Scottish Gaelic.
The project team will create, analyse and disseminate a large text corpus of folktales from the Tale Archive of the School of Scottish Studies Archives and from the Main Manuscript Collection of the Irish National Folklore Collection. The creation of this corpus will involve the scanning of c.80k manuscript pages (and will also include pages scanned by the Dúchas digitisation project), the recognition of handwritten text on these pages (as well as some audio material in Scotland), the normalisation of non-standard text, and the machine translation of Scottish Gaelic into Irish. The corpus will then be annotated with document-level and motif-level metadata.
Analysis of the corpus will be carried out using data mining and phylogenetic techniques. Both the data mining and phylogenetic workstreams will encompass the entire corpus, however, the phylogenetic workstream will also focus on three folktale types as case studies, namely Aarne–Thompson–Uther (ATU) 400 ‘The Search for the Lost Wife’, ATU 425 ‘The Search for the Lost Husband’, and ATU 503 ‘The Gifts of the Little People’. The results of these analyses will be published in a series of articles and in a book entitled Digital Folkloristics. The corpus will be disseminated via Dúchas and Tobar an Dualchais, and via a new aggregator website (under construction) that will include map and graph visualisations of corpus data and of the results of our analysis.
Project team
UK
Principal Investigator Dr William Lamb, The University of Edinburgh (School of Literatures, Languages and Cultures)
Co-Investigator Prof. Jamshid Tehrani, Durham University (Department of Anthropology)
Co-Investigator Dr Beatrice Alex, The University of Edinburgh (School of Literatures, Languages and Cultures)
University of Edinburgh
Language Technician, Michael Bauer
Louise Scollay, Copyright Administrator
Ireland
Co-Principal Investigator Dr Brian Ó Raghallaigh, Dublin City University (Fiontar & Scoil na Gaeilge)
Co-Investigator Dr Críostóir Mac Cárthaigh, University College Dublin (National Folklore Collection)
Co-Investigator Dr Barbara Hillers, Indiana University (Folklore and Ethnomusicology)
While some of our research group has been busy creating the world’s first Scottish Gaelic Speech Recognition system, others been creating the world’s first Scottish Gaelic Text Normaliser. Although it might not turn the heads of AI enthusiasts and smart device lovers in the same way, the normaliser is an invaluable tool for unlocking historical Gaelic, enhancing its use for machine learning and giving people a way to correct Gaelic spelling with no hassle.
Rob Thomas
Why do we need a Gaelic text normaliser? Well, this program takes pre-standardised texts, which can vary in their orthography, and rewrites them in the modern Gaelic Orthographic Conventions (GOC). GOC is a document published by the SQA which details the modern standards for writing in Gaelic. Text normalisation is an important step in text pre-processing for machine learning applications. It’s also useful when reprinting older texts for modern readers, or if you just want to quickly spellcheck something in Gaelic.
I joined the project towards the end and have been fast at work trying to understand Gaelic orthography, how it has developed over the centuries, and what is possible in regards to automated normalisation. I have been working alongside Michael ‘Akerbeltz’ Bauer, a Gaelic linguist with extensive credentials. He has literally written the dictionary on Gaelic as well as a book on Gaelic phonology: it is safe to say I am in good hands. We have been working together to find a way of teaching a program exactly how to normalise Gaelic text. Whereas a human can explain why a word should be spelt a specific way, programming this takes quite a bit of figuring out.
An early ancestor to Scottish Gaelic (Archaic Irish) was written in Ogham, and interestingly enough was carved vertically into stone.
Luckily historical text normalisation is a well-trodden path, and there are plenty of papers and theses online to help. In her thesis, Eva Pettersson describes four main methods for normalising text and, inspired by these, we got started. The first method relies on possessing an extensive lexicon of the target language, which we so happen to have, thanks to Michael.
Lexicon Based Normalisation
This method relies upon having a large lexicon stored that can cover the majority of words in the target language. Using this, you can check to see if a word is spelt correctly, whether it is in a traditional spelling, or if the writer has made a mistake.
The advantage of this method is that you do not have to be an expert in the language yourself (lucky for me!). Our first step was finding a way to integrate the world’s most comprehensive digital Scottish Gaelic dictionary, Am Faclair Beag. The dictionary contains traditional and misspelt words mapped to their correct spellings. This meant that we can have the program go through a text and swap words if it identifies one that needs correcting.
The table above shows some modern words with pre-GOC variants or misspellings. Michael has been collecting Gaelic words and their spelling variants for decades. If our program finds a word that is ‘out of dictionary’, we pass it on to the next stage of normalisation, which involves the hand crafting of linguistic rules.
‘An Gocair’
Rule-based Text Normalisation
Once we have filtered out all of the words that can be handled by our lexicon alone, we try to make use of linguistic rules. It’s not always easy to program a rule so that a computer can understand it. For example, we all know the English rule ‘i before e except after c’ (which of course is an inconsistent rule in English). We can program this by getting the computer to catch all the i’s before e’s and make sure they don’t come after a c.
With guidance from Michael, we went about identifying rules in Gaelic that can be intuitively programmed. One common feature of traditional Gaelic is the replacement of vowels with apostrophes at the end of words if the following word begins with a vowel. This is called ellipsis and is due to the fact that, if one were to speak the phrase, one wouldn’t pronounce both vowels: the writer is simply writing how they would speak. For example, native Gaelic speakers wouldn’t say is e an cù a tha ann ‘it is the dog’: they would say ’s e ’n cù a th’ ann, dropping three vowels. But in writing, we want these vowels to appear – at least for most machine learning situations.
It is not always straightforward working out which vowel an apostrophe replaces, but we can use a rule to help us. Gaelic vowels come in two categories, broad (a, o, u) and slender (e, i). In writing, vowels conform to the ‘broad to broad and slender to slender rule’, so when reinstating a vowel at the end of a word we need to check the form of the first vowel to the left of our apostrophe and ensure that, if it is a broad vowel, we add in a matching vowel.
Pattern Matching with Regular Expression
For this method of normalisation we make use of regular expressions for catching common examples that require normalisation, but are not covered by the lexicon or our previous rules. For example, consider the following example, which is a case of hyper-phonetic spelling, when a person writes like they speak:
Tha sgian ann a sheo tha mis’ a’ toir dhu’-sa.
Here, the word mis’ is given an apostrophe as a final character, because the following word begins with a vowel. GOC suggests that we restore the final vowel. To restore this vowel, we’re helped by the regularity of the Gaelic orthography, a form of vowel harmony, whereby each consonant has to be surrounded either by slender letters (e, i) or broad letters (a, o, u). So in the example above we need to make sure the final vowel of mis’ is a slender vowel (mise), because the first vowel to the left is also slender. We have managed to program this and, using a nifty algorithm, we can then decipher what the correct word should be. When the word is resolved we check to see if the resolved form is in the lexicon and if it is, we save it and move on to the next word.
Evaluation
Now you might be wondering how I managed to learn Scottish Gaelic so comprehensively in five months that I was able to write a program that corrects spelling and also confirm that it is working properly. Well, I didn’t. From the start of the task, I knew there was no way I would be able to gain enough knowledge about the language that I could confidently assess how well the tool was performing. Luckily I did have a large amount of text that was corrected by hand, thanks to Michael’s hard work.
To be able to verify that the tool is working, I had to write some code that automatically compares the output of the tool to the gold standard that Michael created, and then provide me with useful metrics. Eva Peterssonn describes in her thesis on Historical Text Normalisation two such metrics: error reduction and accuracy. Error reduction provides you with the percentage of errors in a text that are successfully corrected using the following formula:
Accuracy simply evaluates the number of words in the gold standard text which has an identical spelling in the normalised version. Below you can see the results of normalisation on a test set of sentences. The green line shows the percentage or errors that are corrected whilst the red and blue line show the accuracy before and after normalisation, respectively. As you can see the normaliser manages to successfully improve the accuracy, sometimes even to 100%.
From GOC to ‘An Gocair’
With a play of words on GOC, we have named the program An Gocair ‘The Un-hooker’. We have tried to make it as easy as possible to update it with new rules. We hope to have the opportunity to create more rules in the future ourselves. The program will also improve with the next iteration of Michael’s fabulous dictionary. We hope to release the first version of An Gocair to the world by the end of October 2021. Keep posted!
Acknowledgement
This program was funded by the Data-Driven Innovation initiative (DDI), delivered by the University of Edinburgh and Heriot-Watt University for the Edinburgh and South East Scotland City Region Deal. DDI is an innovation network helping organisations tackle challenges for industry and society by doing data right to support Edinburgh in its ambition to become the data capital of Europe. The project was delivered by the Edinburgh Futures Institute (EFI), one of five DDI innovation hubs which collaborates with industry, government and communities to build a challenge-led and data-rich portfolio of activity that has an enduring impact.
The Celtic Linguistics Group at the University of Arizona invited Dr Will Lamb to speak to them about ‘Emerging NLP for Scottish Gaelic’ on 26 March 2021. This was as part of their Formal Approaches to Celtic Linguistics lecture series. The talk went out on Zoom and was recorded and uploaded on YouTube (provided below). About 43 min into the video, there is a short demonstration of the prototype ASR system, as it stood at the time. Since then, we have improved the system further, incorporating enhanced acoustic and language models, and a post-processing stage that re-inserts much punctuation back into the output.
Anns an t-sreath seo, tha sinn a’ toirt sùil air laoich a rinn adhartas cudromach ann an teicneolas nan cànanan Gàidhealach. Airson an treasamh agallaimh, cluinnidh sinn bho thè Lucy Evans. Tha Lucy air ùr thighinn gu saoghal na Gàidhlig agus gu saoghal teicneolas cànain, ach tha i an sàs ann am pròiseact a bhios glè chudromach san àm ri teachd, thathar an dòchas. Chuir i crìoch san Lùnastal 2020 air MSc ann an Pròiseasadh Cànan is Cainnt aig Oilthigh Dhùn Èideann. Goirid an dèidh sin, thòisich i mar phàirt de sgioba rannsachaidh a bhios a’ feuchainn ris a’ chiad aithneachar cainnt a chruthachadh dhan Ghàidhlig. Thòisich am pròiseact san t-Sultain 2020 le maoineachas bho Shoillse, an lìonradh nàiseanta rannsachaidh airson glèidheadh agus ath-bheothachadh na Gàidhlig. Tha am pròiseact rannsachaidh na chom-pàirteachas eadar Oilthigh Dhùn Èideann, Oilthigh na Gàidhealtachd is nan Eilean (OGE) agus Quorate Technology Ltd. Anns a’ phìos seo, innsidh Lucy dhuinn ciamar a ghabh i ùidh anns a’ chuspair agus ciamar a bhios cuideigin aig nach eil ach glè bheag de Ghàidhlig ag obair air pròiseact toinnte mar seo.
In this series, we look at persons who have significantly advanced the field of Gaelic, Irish and Manx language technology. For the third interview, we hear from Ms Lucy Evans. Lucy has only recently come to the worlds of Gaelic and language technology, but she is involved in a project that hopefully will come to have great importance in the future. In August 2020, she finished her MSc in Speech and Language Processing at the University of Edinburgh. Shortly after that, she joined a research team that is working to develop the first working speech recogniser for Scottish Gaelic. The project began in September 2020 with funding from Soillse, the national research network for the maintenance and revitalisation of Gaelic language and culture. The research project is a collaboration between the University of the Highlands and Islands, the University of Edinburgh and Quorate Technology. In the interview, Lucy tells us how she took an interest in the subject of speech and language technology and how someone with little Gaelic, at present, is able to work on such a complicated project.
Interview with Lucy Evans
Agallamh le Lucy Evans
“You’ve recently joined the research team developing an automatic speech recogniser for Scottish Gaelic. Tell us a little bit about your background. For example, where are you from, and what got you into language technology work?”
Lucy Evans
I grew up bilingually in Switzerland, speaking English and Italian, before moving to the UK for secondary school. Being bilingual at a young age definitely sparked a curiosity about language, and I went on to study French and Linguistics at the University of Leeds. There, I absolutely loved studying linguistics, so started looking for jobs where I could apply my knowledge from the subject. This led me to discover the field of computational linguistics, and through this I found the MSc in Speech and Language Processing. The MSc encompasses all aspects of language technology, and so was a perfect introduction to the field!
“You’ve just finished the MSc in Speech and Language Processing at the University of Edinburgh. What did you find particularly interesting about the course? Do you have any advice for someone who is thinking about doing it in the future?”
Honestly, I found the whole course really interesting! I was constantly in awe of what I was learning – the interface between computer science and linguistics is niche, and so the techniques used are really specialised. I just find the ability of computers to pick up on all the complexities of language so interesting.
My advice for anyone taking the MSc in the future is simply to be prepared for a really intense year – you’ll be challenged constantly, not only academically, but with time management too. Having said this, the stress is definitely worth it! The course covers a huge amount of content in such a short period of time, which means you’ll be left with a really strong background in the field. A second piece of advice is to get friendly with your peers – there is such a sense of community within the course, and this is undoubtedly one of the loveliest aspects of the MSc. You’ll also get a huge amount of support from Simon King, the course director – make the most of this. Everyone really is there to help and support you, and there is so much more to the MSc than just the course content.
“For those not involved in speech technology, it might seem incredible that someone without Gaelic could develop a speech recogniser for the language. Can you explain how this is possible? And how is working with a minority language going to be different from working with a large language like English?”
As long as you have the necessary resources, it’s only the computer that has to do the language learning! One of the resources I’m talking about here is the dictionary – which essentially maps any written Gaelic word to its phonetic pronunciation. Using this and some transcribed speech data, we can split the speech into its smaller phonetic units, depending on the words in the transcription. Then we train the speech recogniser to learn what these smaller units generally sound like. When new speech is input to the speech recogniser, it can use this lower-level acoustic knowledge to predict which phones (and consequent words) make up the input speech. In this way, as long as you have appropriate (and high-quality) resources, you don’t actually need to learn the language you’re working on – the computer can do that itself!
Working with a minority language adds a challenge in that we won’t necessarily have these resources available. Luckily, for Scottish Gaelic, a digital dictionary has already been created. But this is definitely not the case for most minority languages, making the task significantly harder for non-native speakers to attempt. Furthermore, good quality, transcribed speech data is generally not so easy to come by in minority languages. In the world of machine learning, the general pattern is that the more data you have, the better your system will be. So, with less data available for these languages, it’s harder to get a better system up and running. But there are many mediating methods we can use to boost the performance of a low-resource system – it’s really about finding what works best for the dataset.
“In your own lifetime, you’ve seen language technology change and permeate how we work and live. What’s been your own experience of the changes that it has brought?”
When I was younger, I used language technology but was never really aware of what was going on in the background. Take something like a sat-nav: this is probably one of the first speech technologies I came across, and I remember just laughing about the robotic quality of the synthesised speech – I had no idea how complex the problem actually is! But the amount this has progressed in the last 10 years is crazy – it’s really impressive to see how far things have come in such a short time. For example, we can now ask a mobile phone any question and have it answer us instantly, in near-perfect speech. Things like predictive text and spell-check are other language technologies that are now so embedded in my day-to-day life that I almost forget the complex things they’re doing behind the scenes.
“What are your predications for language technology in the year 2050? If you had your own way, what would you like to see by that time?”
This is a tricky question – considering just the changes in my lifetime, who knows where we’ll be in 30 years from now! In an ideal world, I’d love to see language tech being used more to help people and cultures. This project is an example of that – creating modern technology for endangered languages is an important way to revitalise and preserve those languages! Something I’m also really interested in is using technology to help people with speech disorders, which is definitely something that’s gaining momentum at the moment – it’ll be interesting to see how this can be further improved in years to come.
Anns an t-sreath seo, tha sinn a’ toirt sùil air laoich a rinn adhartas mòr ann an teicneolas nan cànanan gàidhealach. Airson an dàrna agallaimh, cluinnidh sinn bho fhear a tha cho cudromach san 21mh linn ri Eideard Dwelly: Mìcheal Bauer. Tha Mìcheal aithnichte airson na h-obrach ealanta a rinn e le Uilleam MacDhunnchaidh airson Am Faclair Beag–faclair air loidhne a thòisich e o chionn còrr is 20 bliadhna is e na oileanach aig Oilthigh Dhùn Èideann. Chan b’ urrainn cus a ràdh air cho feumail agus cho cudromach ’s a tha am faclair seo. Ach tha e air a bhith an sàs ann an iomadach pròiseact eile an lùib teicneolas a’ chànain on a thòisich e air AFB, leithid inneal-bruidhinn Gàidhlig agus aithnichear làmh-sgrìobhainn. Tha e air leabhraichean feumail a chur a-mach leithid Blas na Gàidhlig,a tha a’ teagasg fhuaimean na Gàidhlig. A bharrachd, tha fèill mhòr air na sgilean eadar-theangachaidh aige, gu h-àraid ann an riaghaltas agus saoghal a’ ghnìomhachais. Mòran taing do Mhìcheal airson a bhith deònach an t-agallamh seo a dhèanamh.
In this series, we look at heroes of Gaelic, Irish and Manx language technology . For our second interview, we hear from someone who is perhaps as important to the Gaelic world in the 21st century as the famous lexicographer, Edward Dwelly: Michael Bauer. Michael is best known for the work he did with Will Robertson on Am Faclair Beag, the important on-line Gaelic dictionary that he began when still a student at Edinburgh University, over 20 years ago. But he has been involved in a wide variety of projects connected to Gaelic language technology since then. For instance, he has been instrumental in the recent development of a Gaelic speech synthesiser and handwriting recogniser. He has also produced a number of excellent Gaelic-related books, such as Blas na Gàidhlig–a superb, linguistically informed guide to Gaelic pronunciation. He is also in high demand as a translator, especially in the government and commercial sectors. Many thanks to Michael for taking the time out to do this interview with us.
(NB: We’re presenting some of these interviews in a Gaelic or Irish only format. If required, they can be translated to English using Google Translate.)
Agallamh le Mìcheal Bauer
Interview with Michael Bauer
“Cò às a tha thu is ciamar a chaidh thu an lùib saoghal na Gàidhlig an toiseach?”
’S ann às a’ Ghearmailt a tha mi, taobh a deas na dùthcha. ’S e co-thuiteamas a thug an-seo mi–bha mi aig Oilthigh LMU mun bhliadhna 1997 agus thachair mi ri cuideigin a bha a’ fuireach faisg air Inbhir Nis. ’S ann air an eadar-lìon a bha sin.
Mìcheal Bauer (Akerbeltz)
Thàinig mi an-seo air saor-làithean fada an uairsin agus rinn mi imrich an ath-bhliadhna an dèidh dha Oilthigh Dhùn Èideann àite a thairgsinn dhomh. ’S e cànanachas agus fòn-eòlas a bha mi a’ dèanamh aig an LMU an uairsin agus bha e ’na rud nàdarra dhomh-sa m’ ainm a chur sìos airson Gàidhlig a bharrachd air cànanachas. Sin mar a thachair.
“Dè thug ort a bhith ag obair le teicneolas a’ chànain? Ciamar a thòisich thu san raon seo?”
Ag innse na fìrinn, co-thuiteamas eile. Cha robh mi cho dèidheil–no math–air teicneolas nuair a bha mi òg. Chan urrainn dhomh spot a ruitheas air sgrìn a phrògramachadh fiù an-diugh agus b’ fheudar dha m’ athair maoidheadh orm an aiste mhòr a nì oileanach sa bhliadhna mu dheireadh san àrd-sgoil a sgrìobhadh air a’ PC seach air clò-sgrìobhadair. Mean air mhean, dh’fhàs mi eòlach air an eadar-lìon is rudan mar sin. Bha mi sa chiad bhliadhna aig Oilthigh Dhùn Èideann nuair a tharraing caraid m’ aire do phròiseact a bha a’ dol aig an àm air an robh Google in Your Language. Chuir Google às dhan phròiseact ud beagan bhliadhnaichean air ais ach fad grunn bhliadhnaichean, b’ urrainn dhut d’ ainm a chur sìos mar eadar-theangadair saor-thoileach agus do chànan a chur air na goireasan a bha fosgailte aca airson eadar-theangachadh, mar an search interface aca. Bha mi air mo bheò-ghlacadh leis an nòisean sin, gun robh e nas fhasa–gu ìre–san t-saoghal digiteach ceàrn a dhèanamh airson cànain bheaga leis gun robh bits agus bytes nas saoire na soidhnichean-rathaid no leabhraichean clò-bhuailte. Agus cha do leig am beò-ghlacadh às mi on àm sin.
Bha mi air mo bheò-ghlacadh leis an nòisean sin, gun robh e nas fhasa–gu ìre–san t-saoghal digiteach ceàrn a dhèanamh airson cànain bheaga leis gun robh bits agus bytes nas saoire na soidhnichean-rathaid no leabhraichean clò-bhuailte. Agus cha do leig am beò-ghlacadh às mi on àm sin.
“Am measg nam pròiseactan teicneolais san robh thu an sàs, cò am fear bu chudromaiche no bu thlachdmhoire a bh’ ann dhut fhèin?”
Am faod mi a dhà dhiubh ainmeachadh? [d. Dall ort!] A’ chiad fhear, sin na gleusan airson teacsadh ro-innseach san robh mi an sàs, predictive texting. Bha mi airson sin a dhèanamh fad bhliadhnaichean on chiad turas a chunnaic mi dè cho luath ’s a bha sgrìobhadh air uidheaman mobile le gleus mar sin, seach a bhith sgrìobhadh rudan litir air litir. Ach cha robh comas prògramachaidh sam bith agam mar a thuirt mi roimhe agus an dèidh mar a thachair dha na h-Èireannaich, cha robh mi airson an aon mhearachd a dhèanamh às ùr. ’S e na thachair ann an Èirinn gun do stèidhich Foras na Gaeilge pròiseact Téacs, app airson teacsadh ro-innseach airson na Gaeilge. Dh’obraich sin math ge leòr fad bhliadhnaichean ach cha robh iad ’ga nuadhachadh agus cha do dh’obraich e ach air grunn handsets agus bhàsaich e mu dheireadh thall. Bha mi a’ sireadh pròiseact mòr le iomadh cànan ’na lùib agus sgioba de luchd-leasachaidh a chumadh air dol e. Ach cha robh a leithid idir furasta ri lorg. Ach mu dheireadh thall, thachair mi ri Adaptxt agus le taic o Kevin Scannell, gaisgeach-d nan cànan beaga, chaidh agam air an dàta air an robh feum a chruinneachadh agus chuir Adaptxt Gàidhlig, Gaelg agus Gaeilge ris na cànain aca. B’ fheudar dhuinn gluasad gu gleus eile bliadhnaichean an dèidh sin, Swiftkey, agus tha Gàidhlig air nochdadh ann an gleus eile no dhà on àm sin. Ach bha mi cho sona ri sagart is eallach leabhraichean air nuair a thàinig Adaptxt a-mach. Bha gleusan eile, mar Firefox, air nochdadh sa Ghàidhlig roimhe sin ach bha–agus tha–e doirbh daoine a thàladh air falbh o coimpiutairean làn-Bheurla. Bidh a’ chuid as motha ’gan cleachdadh dìreach mar a thàinig iad às a’ Bhùth agus a ghnàth, tha sin a’ ciallachadh Beurla, Beurla, Beurla. Ach bha uiread a dhaoine deònach Adaptxt a chur air na fònaichean is tablaidean aca gun robh mi fo iongnadh mòr–agus cho toilichte ’s a ghabhas.
Chan eil dad nas fheàrr na a bhith ag obair air seann chlàradh no teacsa le bodach no cailleach a chaochail deicheadan air ais agus dàta a chur ris na mapaichean, a dh’innseadh gur e, aig àm, ponach am facal a bha aig daoine air balach ann am baile Inbhir Nis. Tha e cha mhòr mar séance beag, a’ bruidhinn ris na linntean a dh’aom.
An rud eile, sin fo-phròiseact aig an Fhaclair Bheag, gleus nam mapaichean. Tha sinn uile eòlach air na deasbadan ud a thaobh faclan “nach canadh duine air eilean seo no siud”. Cha robh mi riamh deònach pàirt a ghabhail annta, ged nach eil mi nam matamataigear, tha mi a’ tuigsinn na th’ ann an representative sample agus chan eil aonan, ge be dè cho eòlach ’s a tha iad air cànan, na representative sample. Bhuail na mapaichean a thug Rob Ó Maolalaigh dhuinn sa chùrsa aige air dual-chainntean na Gàidhlig a thaobh na diofar sgìrean a chleachd, can, siobhag seach buaic agus bha guth olc ’nam cheann ag innse dhomh gum biodh rud mar sin snasail san Fhaclair Bheag. Agus ri linn sin, gu math tràth ann am beatha an fhaclair, chuir sinn gleus ris a chumadh dàta mu na h-àitichean ris an robh faclan a’ buntainn. Chan eil dad nas fheàrr na a bhith ag obair air seann chlàradh no teacsa le bodach no cailleach a chaochail deicheadan air ais agus dàta a chur ris na mapaichean, a dh’innseadh gur e, aig àm, ponach am facal a bha aig daoine air balach ann am baile Inbhir Nis. Tha e cha mhòr mar séance beag, a’ bruidhinn ris na linntean a dh’aom. Agus tha e a’ cur solas beag, mu dheireadh thall, air cuid dhe na faclan ann am faclairean mar Dwelly a dh’fhàgadh thu a’ sgròbadh do chinn roimhe a thaobh cò às a thàinig am facal annasach seo no siud.
Mapa airson ‘mand’ (Am Faclair Beag)
“Dè na duilgheadasan a th’ ann ceangailte ri bhith a’ leasachadh teicneolas airson mion-chànan mar a’ Ghàidhlig?”
Tha iomadh rud ann a tha ’ga fhàgail doirbh ach aig deireadh an latha, an dèidh dhomh a bhith an sàs ann an iomairtean teicneolais d’ an leithid fad fichead bliadhna, chanainn gur e gleus sgaoilidh an rud as motha a tha a dhìth oirnn. Innsidh mi dhut carson. Feuch na stràcan. Chan eil e doirbh PC no Mac a chur air dòigh airson ’s gun toireadh iad dhut na stràcan anns gach prògram, gun a bhith a’ tionndadh gu na gleusan àrsaidh ’s toinnte mar ‘Alt 0224’ airson ‘à’. Ach mur eil earbsa annad ann a bhith a’ fiolcadh leis a’ choimpiutair agad, mar is trice cuiridh e eagal do bheatha ort ma mholas cuideigin dhut a dhol a-steach dha na settings. Air an làimh eile, tha daoine a bu chòir a bhith eòlach air rudan mar sin, can muinntir tech supp, no na daoine a dhèiligeas ri riarachadh coimpiutaireachd sna sgoiltean, cho aineolach d’ a thaobh iad fhèin. Nach pailt na litrichean a sgrìobh mi gu comhairlean a thaobh rudan mar an “UK Extended keyboard layout” air coimpiutairean nan sgoiltean agus shaoileadh tu gun do dh’iarr mi orra an space shuttle a phrògramachadh… ’S e na tha a dhìth oirnn buidheann a thèid mun cuairt nan coimhearsnachdan Gàidhlig–agus oifisean nan daoine a nì co-dhùnaidhean a bhuineas ri saoghal digiteach na Gàidhlig–a bheir taic dhaibh leis an teicneolas Gàidhlig a th’ ann an-diugh eadar keyboard layouts agus Firefox ann an Gàidhlig agus a sgaoileas fiosrachaidh mu an dèidhinn. Ach a-rèir coltais, chan eil sin sexy gu leòr airson nam buidhnean stèidhichte… agus ri linn sin, tha aonadan Gàidhlig againn fhathast aig a bheil coimpiutairean air nach urrainn dhut à a sgrìobhadh gun copypaste no rud gòrach mar sin.
Nach pailt na litrichean a sgrìobh mi gu comhairlean a thaobh rudan mar an “UK Extended keyboard layout” air coimpiutairean nan sgoiltean agus shaoileadh tu gun do dh’iarr mi orra an space shuttle a phrògramachadh…
“Anns an làimh eile, bheil cothroman sam bith ann ma bhios tu ag obair le mion-cànan? Cò iad?”
Tha agus chan eil. Aig amannan tha e mar a bhith ’nad shuidhe air dùn-gainmhich. Chan eil stèidh dhaingeann fodhad idir agus an rud a sheas an-dè, falbhaidh e a-màireach. Can Google in Your Language--chaidh a chur ann gun làmh a bhith aig a’ choimhearsnachd ann agus chaidh a spìonadh air falbh gun làmh aig a’ choimhearsnachd. No can rudan mar Adaptxt agus Swiftkey–dìreach nuair a thug sinn ceum air adhart, tha Amazon is Google a’ cur bogsa ’nar dachaighean nach bruidhinn ach Beurla. Agus ma bhruidhneas tu ri teaghlaichean sa Chuimrigh nach bruidhinn dad ach Cuimris aig an taigh, chan e deagh-bhuaidh a th’ aig na h-innealan ud. Tha iomadh cothrom ann ach feumaidh sinn stèidh beagan nas co-ionnan. Feumaidh sinn seasamh còmhla ris na cànain bheaga eile–agus tha mi a’ gabhail feadhainn mar Eastoinis agus Catalanais a-staigh an-sin–agus cothachadh airson stèidh laghail aig ìre an Aonaidh Eòrpaich a sparras air companaidhean mòra cothrom a thoirt do chànain mar a’ Ghàidhlig agus a’ Lugsamburgais ceum a chumail ri ruith nan teicneolasan ùra.
“Nad bheachd fhèin, dè an dùbhlan as motha a th’ ann airson teicneolas na Gàidhlig anns a’ chòig bhliadhna ri teachd?”
Sasamach [d. facal snasail airson ‘Brexit’] na mallachd. Cha suarach an t-airgead a thàinig à diofar sporan an Aonaidh Eòrpaich a chur taic ri pròiseactan teicneolais Ghàidhlig thairis air na bliadhnaichean, eadar maoineachadh acadaimigeach agus maoineachadh nan roinnean, can. Cuiridh mi mo cheann an geall nach cùm Lunnainn an aon taic rinn.
“Dè an fhàisneachd a th’ agad airson teicneolas cànain anns a’ bhliadhna 2050? Dè bu mhath leat fhaicinn airson teicneolas na Gàidhlig ron àm sin?”
An lagh ud a mhol mi gu h-àrd! Ach mas e gleus teicneolais fhèin a bha thu faighneachd, bhiodh e math gleus a nì sgrìobhadh de chainnt math, leis cho dona ’s a tha daoine air sgrìobhadh na Gàidhlig san fharsaingeachd. Ach air an làimh eile, nan cuireamaid sgoil Ghàidhlig anns gach clachan sna h-Eileanan mar a bha againn roimhe, bhiodh sin a cheart cho math, nach biodh?
