ISCA - International Speech
Communication Association

  • Home
  • M2 Master Internship, Nancy, France

M2 Master Internship, Nancy, France

2024-01-04 15:14 | Anonymous

M2 Master Internship 

Automatic Alsatian speech recognition 

1 Supervisors

Name: Emmanuel Vincent

Team and lab: Multispeech team, Inria research center at Université de Lorraine, Nancy


Name: Pascale Erhart

Team and lab: Language/s and Society team, LiLPa, Strasbourg


2 Motivation and context This internship is part of the Inria COLaF project (Corpora and tools for the languages of France), whose objective is to develop and disseminate inclusive language corpora and technologies for regional languages (Alsatian, Breton, Corsican, Occitan, Picard, etc.), overseas languages and non-territorial immigration languages of France. With few exceptions, these languages are largely ignored by language technology providers [1]. However, such technologies are keys to the protection, promotion and teaching of these languages. Alsatian is the second regional language spoken in France in terms of number of speakers, with 46% of Alsace residents saying they speak Alsatian fairly well or very well [2]. However, it remains an underresourced language in terms of data and language technologies. Attempts at machine translation have been made as well as data collection [3].

3 Objectives The objective of the internship is to design an automatic speech recognition system for Alsatian based on sound archives (radio, television, web, etc.). This raises two challenges: i) Alsatian is not a homogeneous language but a continuum of dialectal varieties which are not always written in a standardized way, ii) the textual transcription is often unavailable or differs from the pronounced words (transcription errors , subtitles, etc.). Solutions will be based on i) finding a suitable methodology for choosing and preparing data, ii) designing an automatic speech recognition system using end-to-end neural networks which can rely on the adaptation of an existing multilingual system like Whisper [4] in a self-supervised manner from a number of untranscribed recordings [5] and in a supervised manner from a smaller number of transcribed recordings, or even from text-only data [6]. The work will be based on datasets collected by LiLPa and the COLaF project’s engineers, which include the television shows Sunndi's Kater [7] and Kùmme Mit [8] whose dialogues are scripted, some radio broadcasts from the 1950s–1970s with their typescripts [9], as well as untranscribed radio broadcasts of France Bleu Elsass. Dictionaries of Alsatian such as the Wörterbuch der elsässischen Mundarten which can be consulted via the Woerterbuchnetz portal [10] or phonetization initiatives [11] could be exploited, for example using Orthal spelling [12]. The internship opens the possibility of pursuing a PhD thesis funded by the COLaF project.

4 Bibliography

[1] DGLFLF, Rapport au Parlement sur la langue française 2023,


[3] D. Bernhard, A-L Ligozat, M. Bras, F. Martin, M. Vergez-Couret, P. Erhart, J. Sibille, A. Todirascu, P. Boula de Mareüil, D. Huck, “Collecting and annotating corpora for three under-resourced languages of France: Methodological issues”, Language Documentation & Conservation, 2021, 15, pp.316-357.

[4] A. Radford, J.W. Kim, T. Xu, G. Brockman, C. McLeavey, I. Sutskever, “Robust speech recognition via large-scale weak supervision”, in 40th International Conference on Machine Learning, 2023, pp. 28492-28518.

[5] A. Bhatia, S. Sinha, S. Dingliwal, K. Gopalakrishnan, S. Bodapati, K. Kirchhoff, “Don't stop selfsupervision: Accent adaptation of speech representations via residual Adapters”, in Interspeech, 2023, pp. 3362-3366.

[6] N. San, M. Bartelds, B. Billings, E. de Falco, H. Feriza, J. Safri, W. Sahrozi, B. Foley, B. McDonnell, D. Jurafsky, “Leveraging supplementary text data to kick-start automatic speech recognition system development with limited transcriptions”, in 6th Workshop on Computational Methods for Endangered Languages, 2023, pp. 1-6.

[7] [8] [9] [10] [11] 10.5281/zenodo.1174213 [12] 

5 Profile MSc in speech processing, natural language processing, computational linguistics, or computer science. Strong programming skills in Python/Pytorch. Knowledge of Alsatian and/or German is a plus, but in no way a prerequisite

 Organisation  Events   Membership   Help 
 > Board  > Interspeech  > Join - renew  > Sitemap
 > Legal documents  > Workshops  > Membership directory  > Contact
 > Logos      > FAQ
       > Privacy policy

© Copyright 2024 - ISCA International Speech Communication Association - All right reserved.

Powered by Wild Apricot Membership Software