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» A hierarchical point process model for speech recognition
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ICASSP
2011
IEEE
12 years 11 months ago
Acoustic model training for non-audible murmur recognition using transformed normal speech data
In this paper we present a novel approach to acoustic model training for non-audible murmur (NAM) recognition using normal speech data transformed into NAM data. NAM is extremely ...
Denis Babani, Tomoki Toda, Hiroshi Saruwatari, Kiy...
JMLR
2010
141views more  JMLR 2010»
13 years 2 months ago
Hierarchical Gaussian Process Regression
We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...
Sunho Park, Seungjin Choi
ICASSP
2008
IEEE
14 years 1 months ago
Name-aware speech recognition for interactive question answering
In this work we show how interactivity in a voice-enabled question answering application may improve speech recognition. We allow the user to provide a target named entity before ...
Svetlana Stoyanchev, Gökhan Tür, Dilek Z...
ICASSP
2011
IEEE
12 years 11 months ago
Phase-sensitive speech enhancement for cochlear implant processing
In this paper, we present a new approach to enhance noisy speech based on an environmental model incorporating the phase between noise and clean speech (often called phasesensitiv...
Pourya S. Jafari, Hou-Yong Kang, Xiaosong Wang, Qi...
ICMI
2004
Springer
159views Biometrics» more  ICMI 2004»
14 years 26 days ago
A segment-based audio-visual speech recognizer: data collection, development, and initial experiments
This paper presents the development and evaluation of a speaker-independent audio-visual speech recognition (AVSR) system that utilizes a segment-based modeling strategy. To suppo...
Timothy J. Hazen, Kate Saenko, Chia-Hao La, James ...