​​​​​Starting date: April 2024 (flexible)

Place of work: Laboratoire d’Informatique de Grenoble, CNRS, Grenoble, France

Duration: 4 to 6 months

Contact: maximin.coavoux@univ-grenoble-alpes.fr

Description:

The SynPaX ANR project (Syntactic Parsing of Spontaneous speech with cross-modal transfer learning) aims at investigating modal fusion systems to develop end-to-end speech parsing models, i.e. systems that work directly on speech signal to perform parsing, instead of using only (potentially noisy) speech transcriptions as input.

The internship will focus on either of the two following topics:

• Designing data augmentation methods for parsing spontaneous spoken French
• Multilingual evaluation of the wav2tree parser (Pupier et al 2022)

Scientific environment:

The internship will be conducted within the Getalp team of the LIG laboratory (https://lig-getalp.imag.fr/). The GETALP team has a strong expertise and track record in Natural Language Processing. The recruited person will be welcomed within the team which offer a stimulating, multinational and pleasant working environment. The internship will be supervised by Maximin Coavoux, Adrien Pupier and Benjamin Lecouteux.

The SynPaX ANR project will also fund a PhD scholarship starting in Fall 2024 to work on extensions of this internship.

internship salary: ~600 euros / month

Profile:

• be enrolled in a Masters program (M2) in NLP, computational linguistics or computer science
• background in NLP and/or speech processing
• Python (transformers, pytorch)
• Good communication skills in English. Rudimentary knowledge of French is expected if the chosen topic is data augmentation for French.

How to apply:

• please send CV + cover letter + recent (last ~2 years) academic transcripts to maximin.coavoux@univ-grenoble-alpes.fr
• Informal inquiries are welcome!

References:

End-to-End Dependency Parsing of Spoken French (Interspeech 2022) Adrien Pupier, Maximin Coavoux, Benjamin Lecouteux, Jérôme Goulian https://hal.science/hal-03713551/

Wave to Syntax: Probing spoken language models for syntax Gaofei Shen, Afra Alishahi, Arianna Bisazza, Grzegorz Chrupała https://arxiv.org/abs/2305.18957