277 citations · 416 across the 28 of their papers we have counts for
6 papers · 1 filter
On the use of Self-supervised Pre-trained Acoustic and Linguistic Features for Continuous Speech Emotion Recognition
Manon Macary, Marie Tahon, Yannick Estève +1
Pre-training for feature extraction is an increasingly studied approach to get better continuous representations of audio and text content. In the present work, we use wav2vec and…
Align then Summarize: Automatic Alignment Methods for Summarization Corpus Creation
Paul Tardy, David Janiszek, Yannick Estève +1
Summarizing texts is not a straightforward task. Before even considering text summarization, one should determine what kind of summary is expected. How much should the information…
Leverage Unlabeled Data for Abstractive Speech Summarization with Self-Supervised Learning and Back-Summarization
Paul Tardy, Louis de Seynes, François Hernandez +3
Supervised approaches for Neural Abstractive Summarization require large annotated corpora that are costly to build. We present a French meeting summarization task where reports ar…
ON-TRAC Consortium for End-to-End and Simultaneous Speech Translation Challenge Tasks at IWSLT 2020
Maha Elbayad, Ha Nguyen, Fethi Bougares +5
This paper describes the ON-TRAC Consortium translation systems developed for two challenge tracks featured in the Evaluation Campaign of IWSLT 2020, offline speech translation and…
Exploring Gaussian mixture model framework for speaker adaptation of deep neural network acoustic models
Natalia Tomashenko, Yuri Khokhlov, Yannick Esteve
In this paper we investigate the GMM-derived (GMMD) features for adaptation of deep neural network (DNN) acoustic models. The adaptation of the DNN trained on GMMD features is done…
Dialogue history integration into end-to-end signal-to-concept spoken language understanding systems
Natalia Tomashenko, Christian Raymond, Antoine Caubriere +2
This work investigates the embeddings for representing dialog history in spoken language understanding (SLU) systems. We focus on the scenario when the semantic information is extr…