Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Mehrez Souden"'
Autor:
Ramin Pichevar, Alex Acero, Jason Wung, Joshua Atkins, Devang Naik, Ante Jukic, Sarmad Malik, Mehrez Souden
Publikováno v:
IEEE Transactions on Signal Processing. 68:3559-3574
Speech dereverberation has been an important component of effective far-field voice interfaces in many applications. Algorithms based on multichannel linear prediction (MCLP) have been shown to be especially effective for blind speech dereverberation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1948edc17d6f3a688bb033a61902ccc6
https://doi.org/10.1109/tsp.2020.2997201
https://doi.org/10.1109/tsp.2020.2997201
Autor:
Michael L. Seltzer, Reinhold Haeb-Umbach, Shinji Watanabe, Bjorn Hoffmeister, Heiga Zen, Michiel Bacchiani, Mehrez Souden, Tomohiro Nakatani
Publikováno v:
IEEE Signal Processing Magazine. 36:111-124
Once a popular theme of futuristic science fiction or far-fetched technology forecasts, digital home assistants with a spoken language interface have become a ubiquitous commodity today. This success has been made possible by major advancements in si
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::00bb4532eb34327e539e5070f9743a94
https://doi.org/10.1109/msp.2019.2918706
https://doi.org/10.1109/msp.2019.2918706
Autor:
Tien Dung Tran, Takuya Higuchi, Masood Delfarah, Shreyas Saxena, Mehrez Souden, Chandra Shekhar Dhir
Publikováno v:
ICASSP
We propose dynamic curriculum learning via data parameters for noise robust keyword spotting. Data parameter learning has recently been introduced for image processing, where weight parameters, so-called data parameters, for target classes and instan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60a7266644b0370e8859d874aed291ee
Publikováno v:
IEEE Transactions on Signal Processing. 62:2127-2142
An inter-channel decorrelation procedure is highly recommended for multi-channel acoustic echo cancellation (AEC) to directly assist adaptive filtering algorithms in overcoming the so-called “non-uniqueness” problem. Although various methods have
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::466d95b6c508c2bbff5b854a61858f59
https://doi.org/10.1109/tsp.2014.2307831
https://doi.org/10.1109/tsp.2014.2307831
Location Feature Integration for Clustering-Based Speech Separation in Distributed Microphone Arrays
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 22:354-367
In distributed microphone arrays (DMAs) the source location information can be defined at the intra and inter-node levels. Indeed, while the first type of information results from the diversity of acoustic channels recorded by microphones embedded in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::645a19c701c775eb816b10e60935fe12
https://doi.org/10.1109/taslp.2013.2292308
https://doi.org/10.1109/taslp.2013.2292308
Publikováno v:
IEEE Transactions on Audio, Speech, and Language Processing. 21:1913-1928
We propose a new framework for joint multichannel speech source separation and acoustic noise reduction. In this framework, we start by formulating the minimum-mean-square error (MMSE)-based solution in the context of multiple simultaneous speakers a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3040762f40a2d0fa7871fc35e95eab99
https://doi.org/10.1109/tasl.2013.2263137
https://doi.org/10.1109/tasl.2013.2263137
Publikováno v:
The Journal of the Acoustical Society of America. 133:EL339-EL345
This paper introduces an approach for online speech source clustering and separation, which is based on the utilization of the multichannel location information in a recursive expectation maximization (EM) algorithm. Specifically, the normalized mult
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::873ba3d68f354151b28d8da669f284f4
https://doi.org/10.1121/1.4795851
https://doi.org/10.1121/1.4795851
Autor:
Tomohiro Nakatani, Marc Delcroix, Masakiyo Fujimoto, Takuya Yoshioka, Seongjun Hahm, Mehrez Souden, Yotaro Kubo, Takaaki Hori, Shinji Watanabe, Atsushi Nakamura, Shoko Araki, Keisuke Kinoshita, Takanobu Oba, Atsunori Ogawa
Publikováno v:
Computer Speech & Language. 27:851-873
Research on noise robust speech recognition has mainly focused on dealing with relatively stationary noise that may differ from the noise conditions in most living environments. In this paper, we introduce a recognition system that can recognize spee
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8337afefbb60968541b5bb975d88e743
https://doi.org/10.1016/j.csl.2012.07.006
https://doi.org/10.1016/j.csl.2012.07.006
Publikováno v:
Applied Acoustics. 74:343-355
Conventional multichannel noise reduction techniques are formulated by splitting the processed microphone observations into two terms: filtered noise-free speech and residual additive noise. The first term is treated as desired signal while the secon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd5f97cbe19befb65f07f1189cabbbf9
https://doi.org/10.1016/j.apacoust.2012.08.002
https://doi.org/10.1016/j.apacoust.2012.08.002
Publikováno v:
IEEE Signal Processing Letters. 19:495-498
We propose a new approach for online noise power spectral density (psd) tracking. In this approach, the prior and posterior probabilities of speech absence and also noise statistics are analytically retrieved from a maximum-likelihood-based criterion
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5a9e442f120c9d6a1ce2f71b93339e8
https://doi.org/10.1109/lsp.2012.2204048
https://doi.org/10.1109/lsp.2012.2204048