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» Signal Processing for Robust Speech Recognition
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ICASSP
2011
IEEE
14 years 9 months ago
Improved speaker recognition when using i-vectors from multiple speech sources
The concept of speaker recognition using i-vectors was recently introduced offering state-of-the-art performance. An i-vector is a compact representation of a speaker’s utteranc...
Mitchell McLaren, David A. van Leeuwen
ICASSP
2009
IEEE
16 years 20 days ago
The use of acoustically detected filled and silent pauses in spontaneous speech recognition
In recognizing spontaneous speech, the performance of typical speech recognizers tends to be degraded by filled and silent pauses, which are hesitation phenomena frequently occur...
Jun Ogata, Masataka Goto, Katunobu Itou
ICASSP
2009
IEEE
16 years 20 days ago
The effectiveness of histogram equalization on environmental model adaptation
In this paper, we introduce a new histogram equalizationbased environmental model adaptation method for robust speech recognition in noise environments. The proposed method adapts...
Youngjoo Suh, Hoirin Kim
LREC
2008
134views Education» more  LREC 2008»
15 years 7 months ago
A Multi-sensor Speech Database with Applications towards Robust Speech Processing in hostile Environments
In this paper, we present a database with speech in different types of background noises. The speech and noise were recorded with a set of different microphones and including some...
Tomas Dekens, Yorgos Patsis, Werner Verhelst, Fr&e...
ICASSP
2009
IEEE
16 years 20 days ago
Extended VTS for noise-robust speech recognition
Model compensation is a standard way of improving the robustness of speech recognition systems to noise. A number of popular schemes are based on vector Taylor series (vts) compen...
Rogier C. van Dalen, Mark J. F. Gales