Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Piergiorgio Svaizer"'
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2010 (2010)
Externí odkaz:
https://doaj.org/article/9561304045764f4e8f084505edc72855
Publikováno v:
Audio Source Separation and Speech Enhancement
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::16aecf831b07608aec82f9e951136e89
https://doi.org/10.1002/9781119279860.ch4
https://doi.org/10.1002/9781119279860.ch4
Publikováno v:
Signal Processing. 93:784-796
This paper presents a parametric approach to classify the radiation pattern of an acoustic source given the signals captured by multiple microphones. The radiation pattern influences the way the acoustic waves propagate within an enclosure, with dire
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2dab42dab566904807d4b6d72749e664
https://doi.org/10.1016/j.sigpro.2012.09.022
https://doi.org/10.1016/j.sigpro.2012.09.022
Publikováno v:
INTERSPEECH
Fondazione Bruno Kessler-IRIS
Fondazione Bruno Kessler-IRIS
The availability of realistic simulated corpora is of key importance for the future progress of distant speech recognition technology. The reliability, flexibility and low computational cost of a data simulation process may ultimately allow researche
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e1c53d0613c0dfa033614843d5301c99
Publikováno v:
IEEE Transactions on Audio, Speech, and Language Processing. 19:624-639
This paper proposes a new method of frequency-domain blind source separation (FD-BSS), able to separate acoustic sources in challenging conditions. In frequency-domain BSS, the time-domain signals are transformed into time-frequency series and the se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::74c06b7316b878d8c400a2a9eb6efecb
https://doi.org/10.1109/tasl.2010.2053027
https://doi.org/10.1109/tasl.2010.2053027
Publikováno v:
ASRU
Speech recognition in a realistic noisy environment using multiple microphones is the focal point of the third CHiME challenge. Over the baseline ASR system provided for this challenge, we apply state of the art algorithms for boosting acoustic model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e114268285d196e0e4ef844b9bfb3675
https://doi.org/10.1109/asru.2015.7404824
https://doi.org/10.1109/asru.2015.7404824
Publikováno v:
ICASSP
Fondazione Bruno Kessler-IRIS
Fondazione Bruno Kessler-IRIS
This paper describes a new corpus of multi-channel audio data designed to study and develop distant-speech recognition systems able to cope with known interfering sounds propagating in an environment. The corpus consists of both real and simulated si
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36e891fb0f954defe84741b7149d5fd0
https://doi.org/10.1109/icassp.2015.7178818
https://doi.org/10.1109/icassp.2015.7178818
Publikováno v:
ICASSP
This work proposes a solution to the problem of under-determined audio source separation using pre-trained redundant source-based prior information. In local Gaussian modeling of a mixing process, an observed mixture is modeled by a Gaussian distribu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70ad934a27a4d3ff1e1aa8500bee619b
Publikováno v:
Computer Speech & Language. 16:205-223
A challenging scenario is addressed in which a distant-talking speech recognizer operates in a noisy office environment with model adaptation. The use of a single far microphone as well as that of a microphone array input are investigated.In addition
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::839e1c3b2ea2bb6a78235c8048eab140
https://doi.org/10.1006/csla.2002.0191
https://doi.org/10.1006/csla.2002.0191
Publikováno v:
IWAENC
This work addresses the problem of underdetermined audio source separation exploiting source-based prior information. To solve the problem by following local Gaussian modeling of a mixing process, the covariance matrix of a mixture of audio sources i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a632f3955359b99ef01ad81afb229dc8
https://doi.org/10.1109/iwaenc.2014.6954301
https://doi.org/10.1109/iwaenc.2014.6954301