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Telecommunications engineering / Filter bank / Beamforming / Speech recognition / Mel-frequency cepstrum / Adaptive filter / Estimation theory / Matched filter / Microphone array / Signal processing / Digital signal processing / Electronic engineering


IEEE TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 14, NO. 6, NOVEMBERSubband Likelihood-Maximizing Beamforming for Speech Recognition in Reverberant Environments
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Document Date: 2006-10-21 10:28:03


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City

A. Feature / San Diego / /

Company

Microsoft / /

Currency

USD / /

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Facility

National Institute of Standards and Technology / Carnegie Mellon University / Naval Warfare Systems Center / /

IndustryTerm

speech recognition systems / calibration algorithm / subband processing implementation / conventional delay-andsum processing / signal processing problem / fact general solutions / filter bank / subband filter-and-sum array processing architecture / array processing architecture / subband filtering algorithms / array processing / conventional array processing algorithms / conventional delay-and-sum processing / microphone array processing / subband processing principles / filter parameter calibration algorithm / signal processing / microphone array processing techniques / array processing method / low-energy regions / microphone array processing problem / subband processing / conventional microphone array processing algorithms / energy / unsupervised processing case / array processing parameters / estimation software / conventional array processing methods / microphone array processing e.g. / bank / required analysis processing / conventional array processing / array processing algorithms / array processing methods / unsupervised processing / array processing algorithm / automatic speech recognition systems / microphone-array processing algorithm / adaptive filtering algorithm / microphone array processing algorithm / distant-talking applications / delay-and-sum processing / subband processing techniques / speech recognition applications / adaptive filtering algorithms / /

MusicAlbum

SPEECH / /

MusicGroup

Calibrated LIMABEAM / LIMABEAM / be expected using Unsupervised LIMABEAM / optimized using Calibrated LIMABEAM / /

Organization

Naval Warfare Systems Center / U.S. Government / National Institute of Standards and Technology / School of Computer Science / Department of Electrical and Computer Engineering / Carnegie Mellon University / Pittsburgh / Space and Naval Warfare Systems Center / /

Person

Maurizio Omologo / Richard M. Stern / /

Position

speaker / associate editor / /

Product

CMU-8 / /

ProvinceOrState

California / /

Technology

Speech Recognition / broadband / LIMABEAM array processing algorithm / calibration algorithm / Calibrated S-LIMABEAM algorithm / Viterbi algorithm / LIMABEAM algorithm / adaptive filtering algorithm / adaptive filtering algorithms / array processing algorithms / speech recognition system / microphone-array processing algorithm / Unsupervised S-LIMABEAM algorithms / subband filtering algorithms / S-LIMABEAM algorithm / two S-LIMABEAM algorithms / proposed S-LIMABEAM algorithm / Unsupervised LIMABEAM algorithms / proposed algorithm / filter parameter calibration algorithm / LIMABEAM ALGORITHM In conventional array processing algorithms / time-domain LIMABEAM algorithms / LMS algorithms / microphone array processing algorithm / Digital Object Identifier / PDA / conventional microphone array processing algorithms / be easily determined using the Viterbi algorithm / /

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