Many self-supervised speech models (S3Ms) have been introduced over the last few years,
improving performance and data efficiency on various speech tasks. However, these …

Many self-supervised speech models (S3Ms) have been introduced over the last few years,
producing performance and data efficiency improvements for a variety of speech tasks …

Today's end-to-end (E2E) ASR models achieve strong performance when applied to adult
speech, but deteriorate on children's speech. Most E2E ASR models are pre-trained on adult …

Audio-Visual Speech Recognition (AVSR) uses lip-based video to improve performance in
noise. Since videos are harder to obtain than audio, the video training data of AVSR models …

Audio-Visual Speech Recognition (AVSR) combines lip-based video with audio and can
improve performance in noise, but most methods are trained only on English data. One …

Large-scale pre-trained self-supervised learning (SSL) models have shown remarkable
advancements in speech-related tasks. However, the utilization of these models in complex …

Cross-language transfer learning from English to a target language has shown effectiveness
in low-resourced audiovisual speech recognition (AV-ASR). We first investigate a 2-stage …

The expansion of speech models emphasizes the importance of parameter efficiency in
practical automatic speech recognition (ASR) systems. Parameter sharing, which reuses the …

Self-supervised learning (SSL) models for speaker verification (SV) have gained significant
attention in recent years. However, existing SSL-based SV systems often struggle to capture …

Knowing the particular context associated with a conversation can help improving the
performance of an automatic speech recognition (ASR) system. For example, if we are …