Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Anurenjan Purushothaman"'
Publikováno v:
Proceedings of the Thirteenth Indian Conference on Computer Vision, Graphics and Image Processing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3552194488888a12313e84c6aad54cba
https://doi.org/10.1145/3571600.3571611
https://doi.org/10.1145/3571600.3571611
Sign Language is the primary mode of communication for the hearing impaired community and between the community and the outside world. This paper proposes a vision-based sign language gesture recognition model to identify the sign gesture (word) from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0eca8e0b5d5f0a5f5c5d63def5012f4a
https://doi.org/10.21203/rs.3.rs-1736819/v1
https://doi.org/10.21203/rs.3.rs-1736819/v1
The task of speech recognition in far-field environments is adversely affected by the reverberant artifacts that elicit as the temporal smearing of the sub-band envelopes. In this paper, we develop a neural model for speech dereverberation using the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2130a02f532989324d10996e22d1503a
Autor:
Rohit Kumar, R. G. Prithvi Raj, Anurenjan Purushothaman, M. K. Jayesh, M. A. Basha Shaik, Sriram Ganapathy
This paper presents the details of the SRIB-LEAP submission to the ConferencingSpeech challenge 2021. The challenge involved the task of multi-channel speech enhancement to improve the quality of far field speech from microphone arrays in a video con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::48d58b365b709f17187e9e7ec2b91676
Publikováno v:
2020 International Conference on Power Electronics and Renewable Energy Applications (PEREA).
Comparative study on the torque ripple reduction during commutation period of Cuk converter fed BLDCM using mode switching selection circuit is done with current controlled BLDCM drive.H-PWM-L-PWM called modified bipolar PWM method shows superior per
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::63885d95d6d1ba48c209f73dba48f339
https://doi.org/10.1109/perea51218.2020.9339770
https://doi.org/10.1109/perea51218.2020.9339770
Publikováno v:
INTERSPEECH
Automatic speech recognition in reverberant conditions is a challenging task as the long-term envelopes of the reverberant speech are temporally smeared. In this paper, we propose a neural model for enhancement of sub-band temporal envelopes for dere
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d8f168c0addeb26f2d1148963034bf82
https://doi.org/10.21437/interspeech.2020-2283
https://doi.org/10.21437/interspeech.2020-2283
This paper reports the LEAP submission to the CHiME-6 challenge. The CHiME-6 Automatic Speech Recognition (ASR) challenge Track 1 involved the recognition of speech in noisy and reverberant acoustic conditions in home environments with multiple-party
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e81e7d7ec0828a02b35367dd1e2b53e5
http://arxiv.org/abs/2005.11258
http://arxiv.org/abs/2005.11258
Publikováno v:
ICASSP
The conventional approach to automatic speech recognition in multichannel reverberant conditions involves a beamforming based enhancement of the multi-channel speech signal followed by a single channel neural acoustic model. In this paper, we propose
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::360e7a3eb476214344b41413f15c9723
https://doi.org/10.1109/icassp40776.2020.9054481
https://doi.org/10.1109/icassp40776.2020.9054481
Publikováno v:
ICASSP
The state-of-art methods for acoustic beamforming in multi-channel ASR are based on a neural mask estimator that predicts the presence of speech and noise. These models are trained using a paired corpus of clean and noisy recordings (teacher model).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e1111ffa82680fb0d1e03f76c633f5f
https://doi.org/10.1109/icassp40776.2020.9054550
https://doi.org/10.1109/icassp40776.2020.9054550