DE eng

Search in the Catalogues and Directories

Hits 1 – 14 of 14

1
The Zero Resource Speech Challenge 2021: Spoken language modelling
In: ISSN: 0162-8828 ; IEEE Transactions on Pattern Analysis and Machine Intelligence ; https://hal.inria.fr/hal-03329301 ; IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2021, pp.1-1. ⟨10.1109/TPAMI.2021.3083839⟩ (2021)
BASE
Show details
2
The Zero Resource Speech Challenge 2021: Spoken language modelling
In: Interspeech 2021 - Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-03329301 ; Interspeech 2021 - Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic. ⟨10.1109/TPAMI.2021.3083839⟩ (2021)
BASE
Show details
3
VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation
Wang, Changhan; Rivière, Morgane; Lee, Ann. - : HAL CCSD, 2021
In: https://hal.inria.fr/hal-03329290 ; 2021, ⟨10.18653/v1/2021.acl-long.80⟩ (2021)
BASE
Show details
4
VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation ...
BASE
Show details
5
VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation ...
BASE
Show details
6
The Zero Resource Speech Challenge 2021: Spoken language modelling ...
BASE
Show details
7
Textless Speech Emotion Conversion using Discrete and Decomposed Representations ...
BASE
Show details
8
The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling
In: NeuRIPS Workshop on Self-Supervised Learning for Speech and Audio Processing ; https://hal.archives-ouvertes.fr/hal-03070362 ; NeuRIPS Workshop on Self-Supervised Learning for Speech and Audio Processing, Dec 2020, Virtuel, France (2020)
Abstract: 14 pages, including references and supplementary material ; International audience ; We introduce a new unsupervised task, spoken language modeling: the learning of linguistic representations from raw audio signals without any labels, along with the Zero Resource Speech Benchmark 2021: a suite of 4 black-box, zero-shot metrics probing for the quality of the learned models at 4 linguistic levels: phonetics, lexicon, syntax and semantics. We present the results and analyses of a composite baseline made of the concatenation of three unsupervised systems: self-supervised contrastive representation learning (CPC), clustering (k-means) and language modeling (LSTM or BERT). The language models learn on the basis of the pseudo-text derived from clustering the learned representations. This simple pipeline shows better than chance performance on all four metrics, demonstrating the feasibility of spoken language modeling from raw speech. It also yields worse performance compared to text-based 'topline' systems trained on the same data, delineating the space to be explored by more sophisticated end-to-end models.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD]
URL: https://hal.archives-ouvertes.fr/hal-03070362
https://hal.archives-ouvertes.fr/hal-03070362/document
https://hal.archives-ouvertes.fr/hal-03070362/file/2011.11588.pdf
BASE
Hide details
9
Towards unsupervised learning of speech features in the wild
In: SLT 2020 : IEEE Spoken Language Technology Workshop ; https://hal.archives-ouvertes.fr/hal-03070411 ; SLT 2020 : IEEE Spoken Language Technology Workshop, Dec 2020, Shenzhen / Virtual, China (2020)
BASE
Show details
10
LIBRI-LIGHT: a benchmark for asr with limited or no supervision
In: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-02959460 ; ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing, May 2020, Barcelona / Virtual, Spain. pp.7669-7673, ⟨10.1109/ICASSP40776.2020.9052942⟩ (2020)
BASE
Show details
11
Data Augmenting Contrastive Learning of Speech Representations in the Time Domain
In: SLT 2020 - IEEE Spoken Language Technology Workshop ; https://hal.archives-ouvertes.fr/hal-03070321 ; SLT 2020 - IEEE Spoken Language Technology Workshop, Dec 2020, Shenzhen / Virtual, China (2020)
BASE
Show details
12
Unsupervised pretraining transfers well across languages
In: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-02959418 ; ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing, May 2020, Barcelona / Virtual, Spain. pp.7414-7418, ⟨10.1109/ICASSP40776.2020.9054548⟩ (2020)
BASE
Show details
13
Unsupervised pretraining transfers well across languages ...
BASE
Show details
14
The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling ...
BASE
Show details

Catalogues
0
0
0
0
0
0
0
Bibliographies
0
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
14
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern