Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Dan Chazan"'
Publikováno v:
Signal Processing. 90:3147-3163
In this paper, we address the problem of monaural source separation of a mixed signal containing speech and music components. We use Discrete Energy Separation Algorithm (DESA) to estimate frequency-modulating (FM) signal energy. The FM signal energy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c00e94671a47f76b5c02f2a6da5c3f8d
https://doi.org/10.1016/j.sigpro.2010.05.020
https://doi.org/10.1016/j.sigpro.2010.05.020
Autor:
Dan Chazan, Ann R. Edwards
Publikováno v:
Journal for Research in Mathematics Education. 41:203-208
In the last few decades, mathematics education in the United States has seen a perfect storm with respect to the teaching and learning of algebra—one that is difficult for our colleagues in other countries to fathom. As part of recent largescale ed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61968cfd61410afa6c331beda8956fcc
https://doi.org/10.5951/jresematheduc.41.2.0203
https://doi.org/10.5951/jresematheduc.41.2.0203
Publikováno v:
IEEE Transactions on Audio, Speech, and Language Processing. 15:2373-2382
We describe and analyze a discriminative algorithm for learning to align an audio signal with a given sequence of events that tag the signal. We demonstrate the applicability of our method for the tasks of speech-to-phoneme alignment (ldquoforced ali
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61a8f16f9860458cdb871e7ea67ab7ab
https://doi.org/10.1109/tasl.2007.903928
https://doi.org/10.1109/tasl.2007.903928
Publikováno v:
Neural Computation. 9:771-776
We show that the VC-dimension of a smoothly parameterized function class is not less than the dimension of any manifold in the parameter space, as long as distinct parameter values induce distinct decision boundaries. A similar theorem was published
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::06f1b3424ff1a0d2ceca5d54a2c1e2db
https://doi.org/10.1162/neco.1997.9.4.771
https://doi.org/10.1162/neco.1997.9.4.771
Publikováno v:
Automatic Speech and Speaker Recognition: Large Margin and Kernel Methods
We describe and analyze a discriminative algorithm for learning to align a phoneme sequence of a speech utterance with its acoustical signal counterpart by predicting a timing sequence representing the phoneme start times. In contrast to common HMM-b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2870b9498b9a23f442286b7f92a241c2
https://doi.org/10.1002/9780470742044.ch4
https://doi.org/10.1002/9780470742044.ch4
Autor:
Dan Chazan, Joseph Keshet
Publikováno v:
Automatic Speech and Speaker Recognition: Large Margin and Kernel Methods
We describe a kernel wrapper, a Mercer kernel for the task of phoneme sequence recognition which is based on operations with the Gaussian kernel, and suitable for any sequence kernel classifier. We start by presenting a kernel-based algorithm for pho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb2b582ea912618cd7e0a93ec5c4e9ff
https://doi.org/10.1002/9780470742044.ch5
https://doi.org/10.1002/9780470742044.ch5
Publikováno v:
INTERSPEECH
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::345ffba4ec27ab00514b612987154995
https://doi.org/10.21437/interspeech.2006-588
https://doi.org/10.21437/interspeech.2006-588
Autor:
Dan Chazan, Raimo Bakis, Ron Hoory, Ariel Sagi, Slava Shechtman, Alexander Sorin, Zhi Wei Shuang
Publikováno v:
ICASSP (1)
This paper describes an efficient sinusoidal modeling framework for high quality wide band (WB) speech synthesis and modification. This technique may serve as a basis for speech compression in the context of small footprint concatenative Text to Spee
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7819628929c775913fa8a726bb2d26a1
https://doi.org/10.1109/icassp.2006.1660161
https://doi.org/10.1109/icassp.2006.1660161
Publikováno v:
INTERSPEECH
Scopus-Elsevier
Scopus-Elsevier
We propose a new paradigm for aligning a phoneme sequence of a speech utterance with its acoustical signal counterpart. In contrast to common HMM-based approaches, our method employs a discriminative learning procedure in which the learning phase is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24b68e4c37c5ac7401218735636980fe
https://doi.org/10.21437/interspeech.2005-129
https://doi.org/10.21437/interspeech.2005-129
Publikováno v:
INTERSPEECH
In this paper we present a method for speech modeling and its utilization in IBM’s small footprint concatenative text-tospeech system. The method is based on frequency-domain, complex spectral envelope modeling, where the phase component plays a cr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9760388de7bde90e947d2788ce5e41b6
https://doi.org/10.21437/interspeech.2005-797
https://doi.org/10.21437/interspeech.2005-797