Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Irina Illina"'
Publikováno v:
Text, Speech, and Dialogue ISBN: 9783031162695
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ab55264a2b4c5a559ea10857bb9554b
https://doi.org/10.1007/978-3-031-16270-1_20
https://doi.org/10.1007/978-3-031-16270-1_20
Autor:
Irina Illina, Dominique Fohr
Publikováno v:
TSD 2021-24th International Conference on Text, Speech and Dialogue
TSD 2021-24th International Conference on Text, Speech and Dialogue, Sep 2021, Olomouc, Czech Republic
Text, Speech, and Dialogue ISBN: 9783030835262
TDS
TSD 2021-24th International Conference on Text, Speech and Dialogue, Sep 2021, Olomouc, Czech Republic
Text, Speech, and Dialogue ISBN: 9783030835262
TDS
International audience; In this work, we address the problem of improving an automatic speech recognition (ASR) system. We want to efficiently model long-term semantic relations between words and introduce this information through a semantic model. W
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::02764de7ddbbf8b1e70a39a6a7e69fab
https://hal.archives-ouvertes.fr/hal-03239211/document
https://hal.archives-ouvertes.fr/hal-03239211/document
Publikováno v:
Interspeech
Interspeech, Aug 2021, Brno, Czech Republic
INTERSPEECH 2021
INTERSPEECH 2021, Aug 2021, Brno, Czech Republic. ⟨10.21437/Interspeech.2021-276⟩
Interspeech, Aug 2021, Brno, Czech Republic
INTERSPEECH 2021
INTERSPEECH 2021, Aug 2021, Brno, Czech Republic. ⟨10.21437/Interspeech.2021-276⟩
International audience; We describe the LORIA-Inria-MULTISPEECH system submitted to the Oriental Language Recognition AP20-OLR Challenge. This system has been specifically designed to be robust to unknown conditions: channel mismatch (task 1) and noi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25b377a69c300e4b29b3c08cbcbfcc2a
https://hal.archives-ouvertes.fr/hal-03228823
https://hal.archives-ouvertes.fr/hal-03228823
Publikováno v:
INTERSPEECH 2021
INTERSPEECH 2021, Aug 2021, Brno, Czech Republic. ⟨10.21437/Interspeech.2021-277⟩
INTERSPEECH 2021, Aug 2021, Brno, Czech Republic
INTERSPEECH 2021, Aug 2021, Brno, Czech Republic. ⟨10.21437/Interspeech.2021-277⟩
INTERSPEECH 2021, Aug 2021, Brno, Czech Republic
International audience; Automatic speech recognition is complementary to language recognition. The language recognition systems exploit this complementarity by using frame-level bottleneck features extracted from neural networks trained with a phone
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::54f4a6d4c5b0cf8c412dceddd97dbedc
https://hal.science/hal-03264085/file/bnf-lid_interspeech2021_publication.pdf
https://hal.science/hal-03264085/file/bnf-lid_interspeech2021_publication.pdf
Autor:
Irina Illina, Dominique Fohr
Publikováno v:
INTERSPEECH 2021
INTERSPEECH 2021, Aug 2021, Brno, Czech Republic
INTERSPEECH 2021, Aug 2021, Brno, Czech Republic. ⟨10.21437/Interspeech.2021-313⟩
INTERSPEECH 2021, Aug 2021, Brno, Czech Republic
INTERSPEECH 2021, Aug 2021, Brno, Czech Republic. ⟨10.21437/Interspeech.2021-313⟩
International audience; This work aims to improve automatic speech recognition (ASR) by modeling long-term semantic relations. We propose to perform this through rescoring the ASR N-best hypotheses list. To achieve this, we propose two deep neural ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3769e5f32fa861f38c3dec5547d7bc22
https://hal.archives-ouvertes.fr/hal-03248881
https://hal.archives-ouvertes.fr/hal-03248881
Publikováno v:
ICASSP 2021-46th International Conference on Acoustics, Speech, and Signal Processing
ICASSP 2021-46th International Conference on Acoustics, Speech, and Signal Processing, Jun 2021, Toronto, Canada
ICASSP
ICASSP 2021-46th International Conference on Acoustics, Speech, and Signal Processing, Jun 2021, Toronto / Virtual, Canada
ICASSP 2021-46th International Conference on Acoustics, Speech, and Signal Processing, Jun 2021, Toronto / Virtual, Canada. ⟨10.1109/ICASSP39728.2021.9414758⟩
ICASSP 2021-46th International Conference on Acoustics, Speech, and Signal Processing, Jun 2021, Toronto, Canada
ICASSP
ICASSP 2021-46th International Conference on Acoustics, Speech, and Signal Processing, Jun 2021, Toronto / Virtual, Canada
ICASSP 2021-46th International Conference on Acoustics, Speech, and Signal Processing, Jun 2021, Toronto / Virtual, Canada. ⟨10.1109/ICASSP39728.2021.9414758⟩
Submitted to ICASSP 2020; Speech separation with several speakers is a challenging task because of the non-stationarity of the speech and the strong signal similarity between interferent sources. Current state-of-the-art solutions can separate well t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eef7a68ce9a1575cbfbbd61a560d9912
https://hal.archives-ouvertes.fr/hal-02985794v2/document
https://hal.archives-ouvertes.fr/hal-02985794v2/document
Publikováno v:
SocialNLP@NAACL
SocialNLP 2021-The 9th International Workshop on Natural Language Processing for Social Media
SocialNLP 2021-The 9th International Workshop on Natural Language Processing for Social Media, Jun 2021, Virtual, France
SocialNLP 2021-The 9th International Workshop on Natural Language Processing for Social Media
SocialNLP 2021-The 9th International Workshop on Natural Language Processing for Social Media, Jun 2021, Virtual, France
International audience; The state-of-the-art abusive language detection models report great in-corpus performance, but underperform when evaluated on abusive comments that differ from the training scenario. As human annotation involves substantial ti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b41d5198902051d7781f7713447ce8a
https://hal.inria.fr/hal-03204605
https://hal.inria.fr/hal-03204605
Publikováno v:
Text, Speech, and Dialogue ISBN: 9783030835262
TDS
TDS
Deep Neural Network (DNN) based classifiers have gained increased attention in hate speech classification. However, the performance of DNN classifiers increases with quantity of available training data and in reality, hate speech datasets consist of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fc7e000254a2e0a138b3697c711ab084
https://doi.org/10.1007/978-3-030-83527-9_12
https://doi.org/10.1007/978-3-030-83527-9_12
Publikováno v:
Natural Language Processing and Information Systems ISBN: 9783030805982
NLDB
NLDB
The task of automatically detecting hate speech in social media is gaining more and more attention. Given the enormous volume of content posted daily, human monitoring of hate speech is unfeasible. In this work, we propose new word-level features for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dff9511908155240fd19a58d7a51dde6
https://doi.org/10.1007/978-3-030-80599-9_14
https://doi.org/10.1007/978-3-030-80599-9_14
Publikováno v:
IEEE/ACM Transactions on Audio, Speech and Language Processing
IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2021, 29, pp.2310-2323. ⟨10.1109/TASLP.2021.3092838⟩
IEEE/ACM Transactions on Audio, Speech and Language Processing, 2021, 29, pp.2310-2323. ⟨10.1109/TASLP.2021.3092838⟩
IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2021, 29, pp.2310-2323. ⟨10.1109/TASLP.2021.3092838⟩
IEEE/ACM Transactions on Audio, Speech and Language Processing, 2021, 29, pp.2310-2323. ⟨10.1109/TASLP.2021.3092838⟩
Deep neural network (DNN)-based speech enhancement algorithms in microphone arrays have now proven to be efficient solutions to speech understanding and speech recognition in noisy environments. However, in the context of ad-hoc microphone arrays, ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55c013beccddd2627ab3b5853b5c151a
https://hal.archives-ouvertes.fr/hal-02985867
https://hal.archives-ouvertes.fr/hal-02985867