Summary
|
For Full-Text PDF, please login, if you are a member of IEICE, or go to Pay Per View on menu list, if you are a nonmember of IEICE. |
|
A Rapid Model Adaptation Technique for Emotional Speech Recognition with Style Estimation Based on Multiple-Regression HMM Yusuke IJIMA Takashi NOSE Makoto TACHIBANA Takao KOBAYASHI Publication IEICE TRANSACTIONS on Information and Systems Vol.E93-D No.1 pp.107-115 Publication Date: 2010/01/01 Online ISSN: 1745-1361 DOI: 10.1587/transinf.E93.D.107 Print ISSN: 0916-8532 Type of Manuscript: PAPER Category: Speech and Hearing Keyword: emotional speech, speaking style, style estimation, multiple-regression HMM, style adaptation, speaker adaptation, Full Text: PDF(711.9KB)>>
Summary: In this paper, we propose a rapid model adaptation technique for emotional speech recognition which enables us to extract paralinguistic information as well as linguistic information contained in speech signals. This technique is based on style estimation and style adaptation using a multiple-regression HMM (MRHMM). In the MRHMM, the mean parameters of the output probability density function are controlled by a low-dimensional parameter vector, called a style vector, which corresponds to a set of the explanatory variables of the multiple regression. The recognition process consists of two stages. In the first stage, the style vector that represents the emotional expression category and the intensity of its expressiveness for the input speech is estimated on a sentence-by-sentence basis. Next, the acoustic models are adapted using the estimated style vector, and then standard HMM-based speech recognition is performed in the second stage. We assess the performance of the proposed technique in the recognition of simulated emotional speech uttered by both professional narrators and non-professional speakers. | ||||||||||
| ||||||||||