An analytic derivation of a phase-sensitive observation model for noise robust speech recognition

V. Leutnant, R. Haeb-Umbach, in: Interspeech 2009, 2009.

Conference Paper | English
Author
Abstract
In this paper we present an analytic derivation of the moments of the phase factor between clean speech and noise cepstral or log-mel-spectral feature vectors. The development shows, among others, that the probability density of the phase factor is of sub-Gaussian nature and that it is independent of the noise type and the signal-to-noise ratio, however dependent on the mel filter bank index. Further we show how to compute the contribution of the phase factor to both the mean and the vari- ance of the noisy speech observation likelihood, which relates the speech and noise feature vectors to those of noisy speech. The resulting phase-sensitive observation model is then used in model-based speech feature enhancement, leading to significant improvements in word accuracy on the AURORA2 database.
Publishing Year
Proceedings Title
Interspeech 2009
LibreCat-ID

Cite this

Leutnant V, Haeb-Umbach R. An analytic derivation of a phase-sensitive observation model for noise robust speech recognition. In: Interspeech 2009. ; 2009.
Leutnant, V., & Haeb-Umbach, R. (2009). An analytic derivation of a phase-sensitive observation model for noise robust speech recognition. In Interspeech 2009.
@inproceedings{Leutnant_Haeb-Umbach_2009, title={An analytic derivation of a phase-sensitive observation model for noise robust speech recognition}, booktitle={Interspeech 2009}, author={Leutnant, Volker and Haeb-Umbach, Reinhold}, year={2009} }
Leutnant, Volker, and Reinhold Haeb-Umbach. “An Analytic Derivation of a Phase-Sensitive Observation Model for Noise Robust Speech Recognition.” In Interspeech 2009, 2009.
V. Leutnant and R. Haeb-Umbach, “An analytic derivation of a phase-sensitive observation model for noise robust speech recognition,” in Interspeech 2009, 2009.
Leutnant, Volker, and Reinhold Haeb-Umbach. “An Analytic Derivation of a Phase-Sensitive Observation Model for Noise Robust Speech Recognition.” Interspeech 2009, 2009.
All files available under the following license(s):
Copyright Statement:
This Item is protected by copyright and/or related rights. [...]

Link(s) to Main File(s)
Access Level
Restricted Closed Access

Export

Marked Publications

Open Data LibreCat

Search this title in

Google Scholar