Relevancy of time-frequency features for phonetic classification measured by mutual information

Authors:
H. Yang;S. van Vuuren;H. Hermansky
Affiliations:
Dept. of Comput. Sci. & Eng., Oregon Graduate Inst. of Sci. & Technol., Beaverton, OR, USA;-;-
Venue:
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01
Year:
1999

Citing 0
Cited 7

Data-Driven Analysis of Speech

TSD '99 Proceedings of the Second International Workshop on Text, Speech and Dialogue
Data-driven spectral basis functions for automatic speech recognition

Speech Communication
An interactive tool for extracting human knowledge in speech recognition

ISPRA'05 Proceedings of the 4th WSEAS International Conference on Signal Processing, Robotics and Automation
Voicing Detection in Noisy Speech Signal

ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
Universal Estimation of Information Measures for Analog Sources

Foundations and Trends in Communications and Information Theory
Multiple resolution analysis for robust automatic speech recognition

Computer Speech and Language
Extraction of speech-relevant information from modulation spectrograms

Progress in nonlinear speech processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we use mutual information to study the distribution in time and frequency of information relevant for phonetic classification. A large database of hand-labeled fluent speech is used to (a) compute the mutual information between phoneme labels and a point of logarithmic energy in the time-frequency plane and (b) compute the joint mutual information between phoneme labels and two points of logarithmic energy in the time-frequency plane.