55 citations · 101 across the 10 of their papers we have counts for
10 papers
Introducing topography in convolutional neural networks
Maxime Poli, Emmanuel Dupoux, Rachid Riad
Parts of the brain that carry sensory tasks are organized topographically: nearby neurons are responsive to the same properties of input signals. Thus, in this work, inspired by th…
Learning strides in convolutional neural networks
Rachid Riad, Olivier Teboul, David Grangier +1
Convolutional neural networks typically contain several downsampling operators, such as strided convolutions or pooling layers, that progressively reduce the resolution of intermed…
Learning spectro-temporal representations of complex sounds with parameterized neural networks
Rachid Riad, Julien Karadayi, Anne-Catherine Bachoud-Lévi +1
Deep Learning models have become potential candidates for auditory neuroscience research, thanks to their recent successes on a variety of auditory tasks. Yet, these models often l…
Comparison of Speaker Role Recognition and Speaker Enrollment Protocol for conversational Clinical Interviews
Rachid Riad, Hadrien Titeux, Laurie Lemoine +6
Conversations between a clinician and a patient, in natural conditions, are valuable sources of information for medical follow-up. The automatic analysis of these dialogues could h…
Vocal markers from sustained phonation in Huntington's Disease
Rachid Riad, Hadrien Titeux, Laurie Lemoine +5
Disease-modifying treatments are currently assessed in neurodegenerative diseases. Huntington's Disease represents a unique opportunity to design automatic sub-clinical markers, ev…
Identification of primary and collateral tracks in stuttered speech
Rachid Riad, Anne-Catherine Bachoud-Lévi, Frank Rudzicz +1
Disfluent speech has been previously addressed from two main perspectives: the clinical perspective focusing on diagnostic, and the Natural Language Processing (NLP) perspective ai…
Seshat: A tool for managing and verifying annotation campaigns of audio data
Hadrien Titeux, Rachid Riad, Xuan-Nga Cao +5
We introduce Seshat, a new, simple and open-source software to efficiently manage annotations of speech corpora. The Seshat software allows users to easily customise and manage ann…
Sampling strategies in Siamese Networks for unsupervised speech representation learning
Rachid Riad, Corentin Dancette, Julien Karadayi +3
Recent studies have investigated siamese network architectures for learning invariant speech representations using same-different side information at the word level. Here we invest…
XNMT: The eXtensible Neural Machine Translation Toolkit
Graham Neubig, Matthias Sperber, Xinyi Wang +10
This paper describes XNMT, the eXtensible Neural Machine Translation toolkit. XNMT distin- guishes itself from other open-source NMT toolkits by its focus on modular code design, w…
Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the "Speaking Rosetta" JSALT 2017 Workshop
Odette Scharenborg, Laurent Besacier, Alan Black +16
We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and scientific issues surrounding the discovery of linguistic units (subwords and word…