Analysis of Information in Speech Based on MANOVA
Sachin S. Kajarekar, Hynek Heřmanský · neural information processing systems · 2002
We propose analysis of information in speech using three sources - language (phone), speaker and channel. Information in speech is measured as mutual information between the source and the set of features extracted from speech signal. We assume that distribution of features can be modeled using Gaussian distribution. The mutual information is computed using the results of analysis of variability in speech. We observe similarity in the results of phone variability and phone information, and show that the results of the proposed analysis have more meaningful interpretations than the analysis of variability.