Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Perotin, Lauréline"'
We present a CNN architecture for speech enhancement from multichannel first-order Ambisonics mixtures. The data-dependent spatial filters, deduced from a mask-based approach, are used to help an automatic speech recognition engine to face adverse co
Externí odkaz:
http://arxiv.org/abs/2006.01708
Autor:
Perotin, Lauréline
Cette thèse s'inscrit dans le contexte de l'essor des assistants vocaux mains libres. Dans un environnement domestique, l'appareil est généralement posé à un endroit fixe, tandis que le locuteur s'adresse à lui depuis diverses positions, sans n
Externí odkaz:
http://www.theses.fr/2019LORR0124/document
Autor:
Perotin, Lauréline
Publikováno v:
Traitement du signal et de l'image [eess.SP]. Université de Lorraine, 2019. Français. ⟨NNT : 2019LORR0124⟩
This work was conducted in the fast-growing context of hands-free voice command. In domestic environments, smart devices are usually laid in a fixed position, while the human speaker gives orders from anywhere, not necessarily next to the device, or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::49d46fceafefef228dc01d95143c1055
https://hal.univ-lorraine.fr/tel-02393258/document
https://hal.univ-lorraine.fr/tel-02393258/document
Akademický článek
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Publikováno v:
WASPAA
WASPAA 2019-IEEE Workshop on Applications of Signal Processing to Audio and Acoustics
WASPAA 2019-IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, IEEE, Oct 2019, New Paltz, United States
WASPAA 2019-IEEE Workshop on Applications of Signal Processing to Audio and Acoustics
WASPAA 2019-IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, IEEE, Oct 2019, New Paltz, United States
International audience; We compare the performance of regression and classification neural networks for single-source direction-of-arrival estimation. Since the output space is continuous and structured, regression seems more appropriate. However, cl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e53e7a2f36dfe70e0f0c28479789e1f0
https://hal.inria.fr/hal-02125985v2
https://hal.inria.fr/hal-02125985v2
Publikováno v:
IWAENC 2018-16th International Workshop on Acoustic Signal Enhancement
IWAENC 2018-16th International Workshop on Acoustic Signal Enhancement, Sep 2018, Tokyo, Japan
IWAENC
IWAENC 2018-16th International Workshop on Acoustic Signal Enhancement, Sep 2018, Tokyo, Japan
IWAENC
International audience; We present a source localization system for first-order Ambisonics (FOA) contents based on a stacked convolutional and recurrent neural network (CRNN). We propose to use as input to the CRNN the FOA acoustic intensity vector,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::90e2f77b53a2b3e8618eb49f3367804c
https://hal.inria.fr/hal-01840453
https://hal.inria.fr/hal-01840453
Publikováno v:
ICASSP
43rd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2018)
43rd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2018), Apr 2018, Calgary, Canada
43rd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2018)
43rd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2018), Apr 2018, Calgary, Canada
International audience; We present a source separation system for high-order ambisonics (HOA) contents. We derive a multichannel spatial filter from a mask estimated by a long short-term memory (LSTM) recurrent neural network. We combine one channel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1981cb166dd3b63bab9b647618fb309
https://doi.org/10.1109/icassp.2018.8461370
https://doi.org/10.1109/icassp.2018.8461370
