514 citations · 1.4k across the 79 of their papers we have counts for
6 papers · 2 filters
Parameter-Efficient Transfer Learning of Audio Spectrogram Transformers
Umberto Cappellazzo, Daniele Falavigna, Alessio Brutti +1
Parameter-efficient transfer learning (PETL) methods have emerged as a solid alternative to the standard full fine-tuning approach. They only train a few extra parameters for each…
TorchAudio 2.1: Advancing speech recognition, self-supervised learning, and audio processing components for PyTorch
Jeff Hwang, Moto Hira, Caroline Chen +21
TorchAudio is an open-source audio and speech processing library built for PyTorch. It aims to accelerate the research and development of audio and speech technologies by providing…
Speech Self-Supervised Representations Benchmarking: a Case for Larger Probing Heads
Salah Zaiem, Youcef Kemiche, Titouan Parcollet +2
Self-supervised learning (SSL) leverages large datasets of unlabeled speech to reach impressive performance with reduced amounts of annotated data. The high number of proposed appr…
RescueSpeech: A German Corpus for Speech Recognition in Search and Rescue Domain
Sangeet Sagar, Mirco Ravanelli, Bernd Kiefer +2
Despite the recent advancements in speech recognition, there are still difficulties in accurately transcribing conversational and emotional speech in noisy and reverberant acoustic…
Speech Self-Supervised Representation Benchmarking: Are We Doing it Right?
Salah Zaiem, Youcef Kemiche, Titouan Parcollet +2
Self-supervised learning (SSL) has recently allowed leveraging large datasets of unlabeled speech signals to reach impressive performance on speech tasks using only small amounts o…
Fine-tuning Strategies for Faster Inference using Speech Self-Supervised Models: A Comparative Study
Salah Zaiem, Robin Algayres, Titouan Parcollet +2
Self-supervised learning (SSL) has allowed substantial progress in Automatic Speech Recognition (ASR) performance in low-resource settings. In this context, it has been demonstrate…