3 citations · 5 across the 16 of their papers we have counts for
16 papers
Streaming Speech-to-Text Translation with a SpeechLLM
Titouan Parcollet, Shucong Zhang, Xianrui Zheng +1
Normally, a system that translates speech into text consists of separate modules for speech recognition and text-to-text translation. Combining those tasks into a SpeechLLM promise…
Multi-layer attentive probing improves transfer of audio representations for bioacoustics
Marius Miron, David Robinson, Masato Hagiwara +15
Probing heads map the representations learned from audio by a machine learning model to downstream task labels and are a key component in evaluating representation learning. Most b…
A Study of Data Selection Strategies for Pre-training Self-Supervised Speech Models
Ryan Whetten, Titouan Parcollet, Marco Dinarelli +1
Self-supervised learning (SSL) has transformed speech processing, yet its reliance on massive pre-training datasets remains a bottleneck. While robustness is often attributed to sc…
Robust Unsupervised Adaptation of a Speech Recogniser Using Entropy Minimisation and Speaker Codes
Rogier C. van Dalen, Shucong Zhang, Titouan Parcollet +1
Speech recognisers usually perform optimally only in a specific environment and need to be adapted to work well in another. For adaptation to a new speaker, there is often too litt…
Evaluation of LLMs in Speech is Often Flawed: Test Set Contamination in Large Language Models for Speech Recognition
Yuan Tseng, Titouan Parcollet, Rogier van Dalen +2
Recent work suggests that large language models (LLMs) can improve performance of speech tasks compared to existing systems. To support their claims, results on LibriSpeech and Com…
Loquacious Set: 25,000 Hours of Transcribed and Diverse English Speech Recognition Data for Research and Commercial Use
Titouan Parcollet, Yuan Tseng, Shucong Zhang +1
Automatic speech recognition (ASR) research is driven by the availability of common datasets between industrial researchers and academics, encouraging comparisons and evaluations.…
Benchmarking Rotary Position Embeddings for Automatic Speech Recognition
Shucong Zhang, Titouan Parcollet, Rogier van Dalen +1
Self-attention relies on positional embeddings to encode input order. Relative Position (RelPos) embeddings are widely used in Automatic Speech Recognition (ASR). However, RelPos h…
Towards Early Prediction of Self-Supervised Speech Model Performance
Ryan Whetten, Lucas Maison, Titouan Parcollet +2
In Self-Supervised Learning (SSL), pre-training and evaluation are resource intensive. In the speech domain, current indicators of the quality of SSL models during pre-training, su…
Linear Time Complexity Conformers with SummaryMixing for Streaming Speech Recognition
Titouan Parcollet, Rogier van Dalen, Shucong Zhang +1
Automatic speech recognition (ASR) with an encoder equipped with self-attention, whether streaming or non-streaming, takes quadratic time in the length of the speech utterance. Thi…
An Analysis of Linear Complexity Attention Substitutes with BEST-RQ
Ryan Whetten, Titouan Parcollet, Adel Moumen +2
Self-Supervised Learning (SSL) has proven to be effective in various domains, including speech processing. However, SSL is computationally and memory expensive. This is in part due…
Linear-Complexity Self-Supervised Learning for Speech Processing
Shucong Zhang, Titouan Parcollet, Rogier van Dalen +1
Self-supervised learning (SSL) models usually require weeks of pre-training with dozens of high-end GPUs. These models typically have a multi-headed self-attention (MHSA) context e…
Analyzing Speech Unit Selection for Textless Speech-to-Speech Translation
Jarod Duret, Yannick Estève, Titouan Parcollet
Recent advancements in textless speech-to-speech translation systems have been driven by the adoption of self-supervised learning techniques. Although most state-of-the-art systems…
Open-Source Conversational AI with SpeechBrain 1.0
Mirco Ravanelli, Titouan Parcollet, Adel Moumen +30
SpeechBrain is an open-source Conversational AI toolkit based on PyTorch, focused particularly on speech processing tasks such as speech recognition, speech enhancement, speaker re…
Less Forgetting for Better Generalization: Exploring Continual-learning Fine-tuning Methods for Speech Self-supervised Representations
Salah Zaiem, Titouan Parcollet, Slim Essid
Despite being trained on massive and diverse datasets, speech self-supervised encoders are generally used for downstream purposes as mere frozen feature extractors or model initial…
Open Implementation and Study of BEST-RQ for Speech Processing
Ryan Whetten, Titouan Parcollet, Marco Dinarelli +1
Self-Supervised Learning (SSL) has proven to be useful in various speech tasks. However, these methods are generally very demanding in terms of data, memory, and computational reso…
Enhancing expressivity transfer in textless speech-to-speech translation
Jarod Duret, Benjamin O'Brien, Yannick Estève +1
Textless speech-to-speech translation systems are rapidly advancing, thanks to the integration of self-supervised learning techniques. However, existing state-of-the-art systems fa…