Comparative deep models for minority and historical languages

Cardamom Seminar Series #13 – Dr Hassan Sajjad (Qatar Computing Research Institute)
2022-06-27 17:00 - 18:00 (Europe/Dublin)
Analyzing Latent Concepts in Deep Neural Network Models of NLP

The Unit for Linguistic Data at the Insight SFI Research Centre for Data Analytics / Data Science Institute, National University of Ireland Galway is delighted to welcome Dr Hassan Sajjad, a senior scientist at the Qatar Computing Research Institute, to be the next speaker in our seminar series. He will talk about the unsupervised methods to analyze latent spaces of deep neural network models. Register here.

Abstract:

Despite the benefits of deep neural network models, their opaqueness is a major cause of concern. Deep neural network models work as a black box and it can be impossible to understand what and how much a model learns about language to solve a task. In this talk, I will present a novel unsupervised method to analyze latent spaces of deep neural network models. I will seek answers to the following questions: i) Is the linguistic hierarchy, such as morphology and semantics, learned in the model? ii) how such knowledge is structured in the model? iii) what are the novel concepts learned by the model? Some notable findings suggest that the models learn n-gram-based and semantically related concepts in the lower layers, core-linguistic concepts are learned in the middle-higher layers, and the last layers’ latent spaces represent task-specific concepts. Moreover, the models learn novel multifacet concepts comprised of more than one linguistic concept such as a concept based on a mix of syntactic and morphological properties.

About the Speaker:

Dr Hassan Sajjad is a Senior Scientist at the Qatar Computing Research Institute. He leads and manages the machine translation project and the Explainable AI project, NeuroX. His research interests include the interpretation of deep neural networks, machine translation, domain adaptation, and natural language processing involving low-resource and morphologically-rich languages. His research work has been published in several prestigious venues such as CL, ICLR, ACL and AAAI. His work in collaboration with MIT and Harvard on the interpretation of deep models has also been featured in several tech blogs. Dr Sajjad regularly serves as an area chair and as a reviewer at various machine learning and computational linguistics conferences and journals. He co-organized the BlackboxNLP workshop 2020/21 and the shared task on MT Robustness 2019/20. In addition, he has been teaching courses on deep learning internationally at several spring and summer schools. Before joining QCRI, Dr Sajjad was at the University of Stuttgart, Germany where he did his PhD in Computer Science under the supervision of Prof. Dr Hinrich Schütze.

Host:

The seminar series is led by the Cardamom project team. The Cardamom project aims to close the resource gap for minority and under-resourced languages using deep-learning-based natural language processing (NLP) and exploiting similarities of closely related languages. The project further extends this idea to historical languages, which can be considered closely related to their modern form. It aims to provide NLP through both space and time for languages that current approaches have ignored.

Registration link:

Cardamom Seminar Series #12 – Dr Annemarie Verkerk (Saarland University)
2022-05-30 10:00 - 11:00 (Europe/Dublin)
Cross-linguistic modelling of communicative efficiency

The Unit for Linguistic Data at the Insight SFI Research Centre for Data Analytics / Data Science Institute, National University of Ireland Galway welcomes Dr Annemarie Verkerk to be the next speaker in our seminar series. Dr Verkerk will highlight the impact of information status on the cross-linguistic modelling of communicative efficiency. Register here.

Abstract:

Information-theoretic modelling of cross-linguistic data has uncovered general principles of language optimization—dependency length minimization and dependency locality (Futrell et al. 2015, 2020) — and its link to efficient memory use (Ferrer I Cancho 2015; Hahn et al. 2021), among others. While existing studies usually provide statements about the overall difference between languages, they do not inspect in detail which language-specific structures license them. We believe that one important factor that has been missing in these accounts is information structure and correspondingly, word order variability, as word order is one strategy used by languages to encode information structure. In this talk, we present an upcoming project investigating the impact of information status on the cross-linguistic modelling of communicative efficiency, and importantly, the parallel corpus that we have been building for this purpose. A pilot study on communicative efficiency in coding argument relations is presented as well.

About the Speaker:

Annemarie Verkerk is junior professor at the Language Science and Technology department at Saarland University. She is a linguistic typologist working with corpus-based and phylogenetic methods for studying language diversity. Her current research focuses on investigating universals using Grambank (glottobank.org) and the impact of information status on information-theoretic modeling across languages.

Host:

The seminar series is led by the Cardamom project team. The Cardamom project aims to close the resource gap for minority and under-resourced languages using deep-learning-based natural language processing (NLP) and exploiting similarities of closely related languages. The project further extends this idea to historical languages, which can be considered closely related to their modern form. It aims to provide NLP through both space and time for languages that current approaches have ignored.

Registration link:

Cardamom Seminar Series #11 – Dr Fahad Khan (ILC, Pisa) & Dr William Short (Exeter)
2022-04-25 17:00 - 18:00 (Europe/Dublin)
Towards an Old English WordNet and the Creation of a Family of WordNets for Historical Languages

The Unit for Linguistic Data at the Insight SFI Research Centre for Data Analytics / Data Science Institute, National University of Ireland Galway, welcomes Dr Fahad Khan and Dr William Michael Short to be the next speaker in our seminar series. Dr Khan and Dr Short will highlight the benefits of creating WordNets for historical languages. They will also discuss some of the questions related to the WordNets of historical languages.

Abstract:

In view of the benefits that the creation of WordNets for modern languages such as English and Polish has brought to the computer-aided study of these languages, scholars of historical languages have begun to explore the development of WordNets for Latin, Greek, Sanskrit, Ancient Egyptian, and – now – Old English. However, the often very long traditions of philological study that characterise scholarship on these languages, the particular research interests of linguists, literary scholars, and cultural historians who work with these languages, and – above all – their specific syntactic, morphological, and lexical profiles invite important questions around how WordNets for historical languages might need to differ from those of modern languages, and to what uses they might then be put.

In this talk we will look at a project for developing a family of ancient Indo-European language WordNets and which is intended to answer some of these questions (Biagetti, Zanchi, and Short 2021). The project began by developing WordNets for Latin, Ancient Greek and Sanskrit; these have been designed to accommodate the highly inflected nature of these languages by incorporating detailed morphological data, including a fine-grained morphosyntactic tagging schema, principal-part information, etc, that can additionally be utilised in lemmatization tasks. Data structures have been introduced to link lemmas – as well as synsets – to etymological information, and represent the rich derivational morphology of these languages. Additionally changes to the WordNet framework for capturing semantic structures have been made, introducing – at the level of synset attribution – distinctions between literal, metonymic, and metaphoric signification, and – at a supralexical level of organisation – by incorporating the idea of ‘conceptual metaphor’ from cognitive linguistics as mapping relations between synsets (see Buccheri, Fedriani, and Short 2021). Finally, it is possible to capture diachronic sense change by tagging specific sense attributions with temporal and/or periodic annotations; synset attributions can also be marked generically to help capture stylistic variations. All the WordNets within this project are being built on single database architecture, with a common API, so that it is possible to programmatically access their lexical and semantic data in a consistent and standardised manner, regardless of language. Other, broader considerations also go into the development of this family of WordNets for historical languages: as well as being used for downstream NLP tasks, such WordNets might often be put to didactic purposes, for instance, or used, in research for comparing the different conceptual distinctions codified in word senses across languages and cultures.

As well as introducing and describing this project we will also look at a recently launched collaboration to create a WordNet for Old English within the ambit of this project. We introduce the challenges of working with this particular historical language and discuss both how the addition of Old English will contribute to elaborating and enriching the existing framework, and how researchers in Old English can help to contribute to this new resource.

About the Speaker:

Fahad Khan is a researcher at the Istituto di Linguistica Computazionale, Consiglio Nazionale delle Ricerche, Pisa, Italy. His interests include language resources, linked data, lexical standards, and the overlap between ontologies and the digital humanities. He is a member of the ISO/TC 37/WG 4 Language Resource Management working group and a co-author of the recently published Lexical Markup Framework (LMF) standard on representing etymological data. He is also a co-chair of the W3C Ontology-Lexica Community Group as well as is involved in the Nexus Linguarum Cost action.

William Michael Short, Lecturer in Classics, Department of Classics & Ancient History, University of Exeter, has pioneered the application of conceptual metaphor theory to the study of the Latin language and Latin literature. Along with numerous publications on specific aspects of the metaphorical structuring of Latin’s and, to a lesser extent, Greek’s semantic systems, his Embodiment in Latin Semantics inaugurated a research paradigm that combines cognitive linguistics, cognitive anthropology, and cultural semantics, in order to reconstruct the worldview of ancient cultures through the study of large-scale patterns of metaphor in their languages. At the same time, he leads the international efforts to create WordNets for Latin, Greek, and Sanskrit, with collaborators at Harvard’s Center for Hellenic Studies, the Universities of Pavia and Bergamo, and elsewhere.

Host:

The seminar series is led by the Cardamom project team. The Cardamom project aims to close the resource gap for minority and under-resourced languages using deep-learning-based natural language processing (NLP) and exploiting similarities of closely related languages. The project further extends this idea to historical languages, which can be considered closely related to their modern form. It aims to provide NLP through both space and time for languages that current approaches have ignored.

Registration link:

Cardamom Seminar Series #10 – Prof Girish Nath Jha (Jawaharlal Nehru University)
2022-03-31 10:00 - 11:00 (Europe/Dublin)
Panini’s Kāraka System and Challenges for Computing

The Unit for Linguistic Data at the Insight SFI Research Centre for Data Analytics / Data Science Institute, NThe Unit for Linguistic Data at the Insight SFI Research Centre for Data Analytics / Data Science Institute, National University of Ireland Galway is delighted to welcome Prof Girish Nath Jha of the Jawaharlal Nehru University to be the next speaker in our seminar series. Prof Jha will highlight some of the semantic aspects of Pāṇini’s kāraka system and highlight the challenges in implementing these rules. Register here.

Abstract:

Panini’s grammar is widely known for its formal treatment of the Sanskrit language and as a cross-linguistic model. However, on a closer look, several complications arise especially in Pāṇini’s recourse to semantics in many of the sūtras like those of the vidhi and the saṁjñā. This seems to happen more in the kāraka prakaraṇa than in other components of his grammar Aṣṭādhyāyī. The talk will focus on some of the semantic aspects of Pāṇini’s kāraka system and highlight the challenges in implementing these rules. It will also look at possible strategies to handle such situations and propose pseudocode renderings of those kāraka sūtras which are relatively easily mappable.

About the Speaker:

Prof. Girish Nath Jha is a Professor who teaches Computational Linguistics at the School of Sanskrit and Indic Studies at Jawaharlal Nehru University(JNU). He is also a Concurrent Faculty at the School of Engineering, Center of Linguistics and the Special Center of e-learning in JNU. His research interests include Indian languages, corpora and standards, Sanskrit and Hindi linguistics, Science & Technology in Sanskrit, Lexicography, Machine Translation, e-learning, web-based technologies, RDBMS techniques, software design and localization. Prof Jha has completed several sponsored projects for Indian language technology development and led a consortium of 17 universities/institutes to develop corpora and standards for Indian languages. He has done collaborative research with the Center for Indic Studies University of Massachusetts Dartmouth as “Mukesh and Priti Chatter Distinguished Professor of History of Science” during 2009-12. He was awarded DAAD fellowship in 2014 and 2016 to teach Digital Humanities and Indology at the University of Würzburg, Germany and has been a visiting Professor at the University of Florence in the summer of 2016. He was also awarded the prestigious Datta Peetha Asthan Vidwan Award for Sanskrit. His work on the revival of the Sharada script earned him the KECSS felicitation award.

He also worked as a software engineer and software development specialist in the USA before joining JNU in 2002. He has had several consultancies, including Google, Nuance, Swiftkey, Microsoft Research, Microsoft Corporation, Linguistic Data Consortium (U. Penn), U.Mass Dartmouth and EZDI.

Host:

The seminar series is led by the Cardamom project team. The Cardamom project aims to close the resource gap for minority and under-resourced languages using deep-learning-based natural language processing (NLP) and exploiting similarities of closely related languages. The project further extends this idea to historical languages, which can be considered closely related to their modern form. It aims to provide NLP through both space and time for languages that current approaches have ignored.

Registration link:

Cardamom Seminar Series #9 – Prof Delyth Prys (Bangor University)
2022-02-21 17:00 - 18:00 (Europe/Dublin)
Language Technology and Language Revitalization in Wales

The Unit for Linguistic Data at the Insight SFI Research Centre for Data Analytics / Data Science Institute, National University of Ireland Galway is delighted to welcome Prof Delyth Prys of the University of Bangor (Wales) to be the next speaker in our seminar series. As this seminar will be held on International Mother Language Day, Prof Prys will highlight aspects of language revitalization and digital language equality in the context of the Welsh language, in addition to providing an overview of recent developments in speech and language technology for this under-resourced Celtic language.

Abstract:

This talk will present the UniMorph project, an attempt to create a universal (cross-lingual) annotation schema. UniMorph allows an inflected word from any language to be defined by its lexical meaning, typically carried by the lemma, and a bundle of universal morphological features defined by the schema. Since 2016, the UniMorph database has been gradually developed and updated with new languages, and SIGMORPHON shared tasks served as a platform to compare computational models of inflectional mThis talk will examine recent development of speech and language technology, translation technology and conversational AI for Welsh in the context of the current Government Welsh Language Technology Action Plan. It will detail new resources, tools, services and products created for Welsh and published in GitHub and the ELG under open permissive licences, the philosophy of open source publishing as an aid to language revitalization and economic recovery in peripheral regions, and the impact of this philosophy on the drive for digital language equality in Europe.

About the Speaker:

Delyth Prys is Professor in the School of Arts, Culture of Language and Head of Language Technologies at Bangor University. She has been engaged in Terminology Standardization at BU since 1993, and since 2001 has led a mixed team of linguists and computer scientists in researching and developing innovative language technologies for less-resourced languages. The main focus of her work is Welsh, together with the wider Celtic family of languages, but she also investigates innovative solutions to data sparsity and the use of language technologies for language revitalization in general.

Professor Prys is a member of numerous Welsh Government committees, a member of BSI/TS1 and convenor of ISO/TC37 working group on socioterminology. In 2018 she won the Womanspire ‘Building Wales’ Award for Science and Technology, and in 2019 the UK’s RCSLT’s Giving Voice Award.

Host:

The seminar series is led by the Cardamom project team. The Cardamom project aims to close the resource gap for minority and under-resourced languages using deep-learning-based natural language processing (NLP) and exploiting similarities of closely related languages. The project further extends this idea to historical languages, which can be considered closely related to their modern form. It aims to provide NLP through both space and time for languages that current approaches have ignored.

Cardamom Seminar Series #8 - Dr Ekaterina Vylomova (University of Melbourne)
2022-02-01 10:00 - 11:00 UTC
The Unit for Linguistic Data at the Insight SFI Research Centre for Data Analytics / Data Science Institute, National University of Ireland Galway is delighted to welcome Dr Ekaterina Vylomova, a Lecturer and a Postdoctoral Fellow at the University of Melbourne, to be the next speaker in our seminar series. The title of her talk is Documenting and modelling inflectional paradigms in under-resourced languages. She will talk about the UniMorph project, which attempts to create a universal (cross-lingual) annotation schema. Register here.

Abstract:

This talk will present the UniMorph project, an attempt to create a universal (cross-lingual) annotation schema. UniMorph allows an inflected word from any language to be defined by its lexical meaning, typically carried by the lemma, and a bundle of universal morphological features defined by the schema. Since 2016, the UniMorph database has been gradually developed and updated with new languages, and SIGMORPHON shared tasks served as a platform to compare computational models of inflectional morphology. During 2016–2021, the shared tasks made it possible to explore the data-driven systems’ ability to learn declension and conjugation paradigms and evaluate how well they generalize across typologically diverse languages. It is essential since the elaboration of formal techniques of cross-language generalization and prediction of universal entities across related languages should provide new potential to the modelling and documentation of under-resourced languages. The talk will outline the major challenges we faced while converting the language-specific features into the UniMorph schema, especially in under-resourced languages. In addition, we will discuss typical errors made by the majority of the systems, e.g. incorrectly predicted instances due to allomorphy, form variation, misspelt words, looping effects. Finally, it will provide case studies for Russian, Tibetan, and Nen.

About the Speaker:

Dr Ekaterina Vylomova is a Lecturer and a Postdoctoral Fellow at the University of Melbourne. Her research is focused on compositionality modelling for morphology, models of inflectional and derivational morphology, linguistic typology, diachronic language models, and neural machine translation. She co-organized SIGTYP 2019 – 2021 workshops and shared tasks and the SIGMORPHON 2017 – 2021 shared tasks on morphological re-inflection.

Host:

The seminar series is led by the Cardamom project team. The Cardamom project aims to close the resource gap for minority and under-resourced languages using deep-learning-based natural language processing (NLP) and exploiting similarities of closely related languages. The project further extends this idea to historical languages, which can be considered closely related to their modern form. It aims to provide NLP through both space and time for languages that current approaches have ignored.

Cardamom Seminar Series #7 - Prof Will Lamb (University of Edinburgh)
2021-11-30 17:00 - 18:00 (Europe/Dublin)
The Unit for Linguistic Data at the Insight SFI Research Centre for Data Analytics / Data Science Institute, National University of Ireland Galway is delighted to welcome Dr Will Lamb, Senior Lecturer in Scottish Ethnology / EFI Research Affiliate at The University of Edinburgh, to be the next speaker in our seminar series. The title of his talk is ‘Scottish Gaelic Language Technology: Current Provision and Future Potentials’. Register here!

Abstract:

For a minority language with less than 60k speakers, Scottish Gaelic has a surprising level of provision in language technology. Over the past ten years, researchers have developed: part-of-speech taggers, lemmatisers, machine translation systems, an orthographic normaliser, a text-to-speech system, a syntactic parser, a handwriting recogniser and, most recently, a speech-to-text system. This talk will outline the current state-of-the-art and how some of these tools are being used within education and applied research. It will then consider what is necessary to move towards next generation NLP and NLG systems, such as a virtual assistant.

About the Speaker:

Dr Will Lamb is a Senior Lecturer in Celtic and Scottish Studies at the University of Edinburgh. Originally from Baltimore, MD he came to Edinburgh in 1996 to study an MSc in Celtic Studies (University of Edinburgh). It was during his PhD on Gaelic register variation (1997–2002), also at the University of Edinburgh, that he became interested in language technology. Along with his brother, a computer programmer, he designed an early concordancer, which he used during his study of Gaelic register variation. As part of his research, he put together the first part-of-speech tagged corpus of Scottish Gaelic.

From 2000 to 2010, Will was a lecturer in Gaelic language and music at Lews Castle College in Benbecula. In 2010, he returned to the University of Edinburgh as a Lecturer in Scottish Ethnology. From 2012, he has led a number of funded studies on Gaelic NLP. Using the tagged corpus that he developed during his PhD, he helped to develop the first part-of-speech tagger for the language, and its first representative, tagged corpus (ARCOSG). Subsequently, he has had a hand in developing a number of other language technologies for the language, including a lemmatiser, a handwriting recogniser, a syntactic parser and, more recently, an automatic speech recognition system. He is currently the PI for a three-year, international digital humanities project funded by the AHRC and IRC, ‘Decoding Hidden Heritages’. This project will make available millions of words of vernacular Gaelic folklore in text and audio, providing valuable data for next generation language and acoustic models.

Host:

The seminar series is led by the Cardamom project team. The Cardamom project aims to close the resource gap for minority and under-resourced languages using deep-learning-based natural language processing (NLP) and exploiting similarities of closely related languages. The project further extends this idea to historical languages, which can be considered closely related to their modern form. It aims to provide NLP through both space and time for languages that current approaches have ignored.

Registration link:

Cardamom Seminar Series #6 - Dr Nils Reimers (Hugging Face)
2021-10-26 17:00 - 18:00 (Europe/Dublin)
The Unit for Linguistic Data at the Insight SFI Research Centre for Data Analytics / Data Science Institute, National University of Ireland Galway is delighted to welcome Nils Reimers, research scientist at Hugging Face, to be the next speaker in our seminar series. He will talk about his research on the application of neural networks in low resource settings. Register here.

Abstract:

Search results can be significantly improved by using neural networks; however, those models are often fine-tuned on hundred thousands of annotated data pairs. For many cases and languages other than English, such large labelled datasets are sadly seldom available. This talk will cover different approaches and how to train these methods if no or only little labelled data is available.

About the Speaker:

Nils Reimers holds the position of Research Scientist at Hugging Face. He is not only an NLP scientist but a professional web developer. He is also interested in entrepreneurship and especially interested in IT start-ups that use bleeding-edge technology.

Dr Reimers is an expert in Natural Language Processing with a particular focus on deep learning. His main research interest is in representing the semantics of words, sentences, and paragraphs in vector spaces such that texts with similar meanings are close. He has also developed state-of-the-art open-source solutions commonly known as Sentence BERT (SBERT), which are very popular in research & industry.

Host:

The seminar series is led by the Cardamom project team. The Cardamom project aims to close the resource gap for minority and under-resourced languages using deep-learning-based natural language processing (NLP) and exploiting similarities of closely related languages. The project further extends this idea to historical languages, which can be considered closely related to their modern form. It aims to provide NLP through both space and time for languages that current approaches have ignored.

Cardamom Seminar Series #5 – Prof Greg Toner (Queen's University Belfast)
2021-09-27 17:00 - 18:00 (Europe/Dublin)
Temporal Text Classification: Computer-Based Dating of Medieval Irish Texts

The Unit for Linguistic Data at the Insight SFI Research Centre for Data Analytics / Data Science Institute, National University of Ireland Galway is delighted to welcome Greg Toner, professor of Irish at Queen’s University Belfast, to be the next speaker in our seminar series. He will present his research on the application of machine-learning techniques to the dating of medieval Irish texts. Register here.

Abstract:

This paper presents the results of a Leverhulme-funded project which explored the applicability of machine-learning techniques to the dating of medieval Irish texts. We will explore the methods developed in order to construct a model which achieved a 75% success rate in dating individual annual entries to within +/- 25 years. We will then examine the application of this model to non-annalistic texts, including the methods that we have developed to cope with genre variation, multiple strata and bias within the data.

About the Speaker:

Greg Toner holds the position of Professor of Irish at Queen’s University, Belfast, having previously held the Professorship of Irish Language and Literature at the University of Ulster. He is not only a Member of the Royal Irish Academy but chairs the management committee of the RIA’s Foclóir Stairiúil na Gaeilge. He is also a member of the Arts and Humanities Research Council Peer Review College and Honorary General Editor of the Irish Texts Society.

Professor Toner is a trailblazer in the area of digital Early Irish research, having directed the Electronic Dictionary of the Irish Language project (eDIL) which saw the digitisation and further development of the original hard-copy Dictionary of the Irish language (DIL). Since the completion of the project, eDIL has become a central resource in medieval Irish studies for language learners and seasoned academics alike. He also developed the widely used Computer-Assisted Practice Activities for Irish Language Learners (CAPAILL). More recently, he led a Leverhulme-funded project to explore the use of computational methods for dating medieval Irish texts. This investigation may represent the first use of machine learning in Early Irish research and forms the basis of his presentation today.

Host:

The seminar series is led by the Cardamom project team. The Cardamom project aims to close the resource gap for minority and under-resourced languages using deep-learning-based natural language processing (NLP) and exploiting similarities of closely related languages. The project further extends this idea to historical languages, which can be considered closely related to their modern form. It aims to provide NLP through both space and time for languages that current approaches have ignored.

Registration link:

Cardamom Seminar Series #4 – Dr John P. McCrae (University of Galway)
2021-07-26 17:00 - 18:00 (Europe/Dublin)
The Unit for Linguistic Data at the Insight SFI Research Centre for Data Analytics / Data Science Institute, University of Galway is delighted to welcome Dr John P. McCrae, a lecturer-above-the-bar and the leader of the Unit for Linguistic Data at the Data Science Institute, National University of Ireland Galway. Dr McCrae will introduce the Cardamom project which is related to the development of natural language processing (NLP) tools and resources for minority and historical languages. Register here.

Abstract:

Cardamom is an IRC-funded project related to the development of natural language processing (NLP) tools for minority and historical languages. At its core, the project builds on the comparative principle, which entails you can learn information about a language by looking at either its close sibling languages or, in the case of historical languages, its modern form. For this goal, we are focussing on building the largest collection of known resources on languages in these families by searching the web, social media and retro-digitization. Then we will form new deep learning models which will be applied to minority languages to generate new dictionaries and computer-aided language learning tools, and to historical languages to provide a workbench to analyse historical language data. We will describe progress towards these goals and the recent collaboration with Translators without Borders to develop language resources for the Rohingya refugee crisis.

About the Speaker:

John P. McCrae is a lecturer above-the-bar (assistant professor) at the University of Galway and the leader of the Unit for Linguistic Data. His work concerns a wide range of areas of natural language processing and data science, especially focused on under-resourced languages and lexicography. He has a PhD from the National Institute of Informatics, Japan and was a postdoctoral researcher at Bielefeld University. He is one of the leading developers of the OntoLex model and the coordinator of the Prêt-à-LLOD project.

Cardamom Seminar Series #3 – Remo Nitschke (University of Arizona)
2021-06-28 17:00 - 18:00 (Europe/Dublin)
Neural Machine Translation Approaches for Vocabulary Reconstruction Tasks

The Unit for Linguistic Data at the Data Science Institute, National University of Ireland Galway is delighted to welcome Remo Nitschke of the Linguistics department at the University of Arizona as our next speaker in the Cardamom Seminar Series. Register here.

Abstract:

In this talk, we will introduce a method for vocabulary reconstruction/prediction via a neural machine translation (NMT) setup. This method relies on adapting a translation/sequence prediction task to predict cognates of a target language from cognates of related languages. It shows that by using a many-to-one mapping in the input (mapping multiple language items to one target), we can reduce the need for large datasets significantly. This has to potential to allow us to use a neural-net based approach even in some low-resource contexts.

Further, we will show that this is possible via a proof-of-concept in the Romance language family. We will then discuss the current efforts to conduct an analog experiment in the Uto-Aztecan language family, an effort which is currently underway.

About the Speaker:

Remo Nitschke is a PhD-candidate at the University of Arizona linguistics department. His research areas are Syntax and NLP for low-resource languages. He is currently working on the Syntax of German adjectives and ways to utilize neural machine translation for low-resource languages.

Cardamom Seminar Series #2 – Dr Rolando Coto Solano (Dartmouth College)
2021-05-31 17:00 - 18:30 (Europe/Dublin)
Linguistically Informed Representations Improve Deep Learning for Extremely Low-Resource Languages

The Unit for Linguistic Data at the Data Science Institute, National University of Ireland Galway is delighted to welcome Rolando Coto-Solano, professor of linguistics at Dartmouth College as the second speaker in our seminar series. Professor Coto-Solano will talk about linguistically informed representations to improve deep learning for extremely low-resource languages, especially focusing on Chibchan languages.

The aim of the seminar series, organised by the Cardamom team, is to connect researchers working to alleviate challenges around language resources and technologies for minority, historical, indigenous and lesser-resourced languages across the globe. The seminar series will provide us with a platform to discuss various types of problems and share our views to solve problems that researchers face during their research.

To sign up for this event, go to the Eventbrite link.

Cardamom Seminar Series #1 - Dr Adriana Molina Muñoz (University of Oxford)
2021-04-26 17:00 - 18:00 (Europe/Dublin)
The Unit for Linguistic Data at the Data Science Institute, National University of Ireland Galway, is delighted to welcome Dr Adriana Molina-Muñoz, a researcher at the University of Oxford, as the first speaker in our seminar series. In her talk, Dr Molina-Muñoz will give an overview of methodological and theoretical challenges that emerge when working with a historical language.

The aim of the seminar series, organised by the Cardamom team, is to connect researchers working to alleviate challenges around language resources and technologies for minority, historical, indigenous and lesser-resourced languages across the globe. The seminar series will provide us with a platform to discuss various types of problems and share our views to solve problems that researchers face during their research.

To sign up for this event, go to the Eventbrite link.
