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» Bi-Spectral Acoustic Features for Robust Speech Recognition
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CHI
2009
ACM
13 years 11 months ago
Comparing emotions using acoustics and human perceptual dimensions
Understanding the difference between emotions based on acoustic features is important for computer recognition and classification of emotions. We conducted a study of human percep...
Keshi Dai, Harriet J. Fell, Joel MacAuslan
INTERSPEECH
2010
13 years 2 months ago
Feature versus model based noise robustness
Over the years, the focus in noise robust speech recognition has shifted from noise robust features to model based techniques such as parallel model combination and uncertainty de...
Kris Demuynck, Xueru Zhang, Dirk Van Compernolle, ...
SPEECH
2008
142views more  SPEECH 2008»
13 years 7 months ago
Combined speech enhancement and auditory modelling for robust distributed speech recognition
The performance of automatic speech recognition (ASR) systems in the presence of noise is an area that has attracted a lot of research interest. Additive noise from interfering no...
Ronan Flynn, Edward Jones
ICASSP
2011
IEEE
12 years 11 months ago
Delta-spectral cepstral coefficients for robust speech recognition
Almost all current automatic speech recognition (ASR) systems conventionally append delta and double-delta cepstral features to static cepstral features. In this work we describe ...
Kshitiz Kumar, Chanwoo Kim, Richard M. Stern
ICASSP
2009
IEEE
14 years 2 months ago
Statistical analysis of amplitude modulation in speech signals using an AM-FM model
Several studies have been dedicated to the analysis and modeling of AM–FM modulations in speech and different algorithms have been proposed for the exploitation of modulations i...
Pirros Tsiakoulis, Alexandros Potamianos