118 citations · 215 across the 15 of their papers we have counts for
17 papers
LeBenchmark 2.0: a Standardized, Replicable and Enhanced Framework for Self-supervised Representations of French Speech
Titouan Parcollet, Ha Nguyen, Solene Evain +19
Self-supervised learning (SSL) is at the origin of unprecedented improvements in many different domains including computer vision and natural language processing. Speech processing…
Combining Public Human Activity Recognition Datasets to Mitigate Labeled Data Scarcity
Riccardo Presotto, Sannara Ek, Gabriele Civitarese +3
The use of supervised learning for Human Activity Recognition (HAR) on mobile devices leads to strong classification performances. Such an approach, however, requires large amounts…
Evaluation and comparison of federated learning algorithms for Human Activity Recognition on smartphones
Sannara Ek, François Portet, Philippe Lalanda +1
Pervasive computing promotes the integration of smart devices in our living spaces to develop services providing assistance to people. Such smart devices are increasingly relying o…
Cross-domain Voice Activity Detection with Self-Supervised Representations
Sina Alisamir, Fabien Ringeval, Francois Portet
Voice Activity Detection (VAD) aims at detecting speech segments on an audio signal, which is a necessary first step for many today's speech based applications. Current state-of-th…
Dynamic Time-Alignment of Dimensional Annotations of Emotion using Recurrent Neural Networks
Sina Alisamir, Fabien Ringeval, Francois Portet
Most automatic emotion recognition systems exploit time-continuous annotations of emotion to provide fine-grained descriptions of spontaneous expressions as observed in real-life i…
Transformer-based Models to Deal with Heterogeneous Environments in Human Activity Recognition
Sannara EK, François Portet, Philippe Lalanda
Human Activity Recognition (HAR) on mobile devices has been demonstrated to be possible using neural models trained on data collected from the device's inertial measurement units.…