ILCB round table: Interpreting machine learning in hearing, communication and language sciences

ILCB Round table

Interpreting machine learning in hearing, communication and language sciences: why, how, and the current challenges

Program:

12.00/12.30 – Etienne Thoret (Post-doc ILCB, PRISM, LIS) – Deciphering the acoustical bases of hearing by interpreting biomimetic deep-neural-networks (20 min + 10 min)
12.30/1.00 – Philippe Blache (LPL) – Is language processing incremental? A comparison between Transformer and RNN-based language models and their ability to model human language processing.  (20 min + 10 min)
1.00/1.30 – Ronan Sicre (LIS) – Visual interpretability of deep neural networks: a brief overview.  (20 min + 10 min)
1.30/1.45 – Adrià Torrens (University of Ostrava) Building a grammar for gradient linguistic evaluative expressions: Do Machine learning, neuronal networks, and deep learning help? (10 min + 5min)
1.45/2.30 – Discussion (45 min)

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