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ICASSP
2008
IEEE
15 years 9 months ago
Voice source cepstrum coefficients for speaker identification
We propose a novel feature set for speaker recognition that is based on the voice source signal. The feature extraction process uses closed-phase LPC analysis to estimate the voca...
Jon Gudnason, Mike Brookes
113
Voted
ICASSP
2008
IEEE
15 years 9 months ago
French prominence: A probabilistic framework
Identification of prosodic phenomena is of first importance in prosodic analysis and modeling. In this paper, we introduce a new method for automatic prosodic phenomena labellin...
Nicolas Obin, Xavier Rodet, Anne Lacheret-Dujour
110
Voted
ICASSP
2008
IEEE
15 years 9 months ago
Towards the use of full covariance models for missing data speaker recognition
This work investigates the use of missing data techniques for noise robust speaker identification. Most previous work in this field relies on the diagonal covariance assumption ...
Marco Kühne, Daniel Pullella, Roberto Togneri...
122
Voted
ICASSP
2008
IEEE
15 years 9 months ago
Analysis-by-synthesis features for speech recognition
We present a framework for speech recognition that accounts for hidden articulatory information. We model the articulatory space using a codebook of articulatory configurations g...
Ziad Al Bawab, Bhiksha Raj, Richard M. Stern
129
Voted
ICASSP
2008
IEEE
15 years 9 months ago
LSF mapping for voice conversion with very small training sets
To make voice conversion usable in practical applications, the number of training sentences should be minimized. With traditional Gaussian mixture model (GMM) based techniques sma...
Elina Helander, Jani Nurminen, Moncef Gabbouj