Wav2Vec 2.0

material ID: wav2vec2.0

Related Papers

End-to-End Speech Translation with Pre-trained Models and Adapters: UPC at IWSLT 2021

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractThis paper describes the submission to the IWSLT 2021 offline speech translation task by the UPC Machine Translation group. The task consists of building a system capable of translating English …...

20725

On Generative Spoken Language Modeling from Raw Audio

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractWe introduce Generative Spoken Language Modeling, the task of learning the acoustic and linguistic characteristics of a language from raw audio (no text, no labels), and a set of metrics …...

26826

Impact Analysis of the Use of Speech and Language Models Pretrained by Self-Supersivion for Spoken Language Understanding

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractPretrained models through self-supervised learning have been recently introduced for both acoustic and language modeling. Applied to spoken language understanding tasks, these models have shown their great potential by improving …...

15458

ON-TRAC Consortium Systems for the IWSLT 2022 Dialect and Low-resource Speech Translation Tasks

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractThis paper describes the ON-TRAC Consortium translation systems developed for two challenge tracks featured in the Evaluation Campaign of IWSLT 2022: low-resource and dialect speech translation. For the Tunisian Arabic-English …...

20662

Recycle Your Wav2Vec2 Codebook: A Speech Perceiver for Keyword Spotting

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractSpeech information in a pretrained wav2vec2.0 model is usually leveraged through its encoder, which has at least 95M parameters, being not so suitable for small footprint Keyword Spotting. In this …...

3648

GMU Systems for the IWSLT 2023 Dialect and Low-resource Speech Translation Tasks

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractThis paper describes the GMU Systems for the IWSLT 2023 Dialect and Low-resource Speech Translation Tasks. We submitted systems for five low-resource tasks and the dialectal task. In this work, …...

20555

NSYSU-MITLab Speech Recognition System for Formosa Speech Recognition Challenge 2023

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

In this study, the speech recognition sys- tem will be introduced, used by NSYSU- MITLab, for Formosa Speech Recogni- tion Challenge 2023. We use the pre- trained model wav2vec2.0 as …...

1096