Title :
Acoustic Feature Optimization for Emotion Affected Speech Recognition
Author :
Sun, Yanqing ; Zhou, Yu ; Zhao, Qingwei ; Yan, Yonghong
Author_Institution :
ThinkIT Speech Lab., Chinese Acad. of Sci., Beijing, China
Abstract :
This paper tries to deal with the problem of performance degradation in emotion affected speech recognition. The F-ratio analysis method in statistics is utilized to analyze the significance of different frequency bands for speech unit classification. The result is then used to optimize filter bank design for Mel-frequency cepstral coefficients (MFCC) and perceptual linear prediction (PLP) features respectively in emotion affected speech recognition. Under comparable conditions, the modified features get a relative 40.14% decrease for MFCC and 34.93% for PLP in sentence error rate.
Keywords :
acoustic signal processing; emotion recognition; feature extraction; optimisation; speech recognition; statistical analysis; F-ratio analysis method; Mel-frequency cepstral coefficients; acoustic feature optimization; emotion affected speech recognition; filter bank design; perceptual linear prediction; performance degradation; speech unit classification; Acoustics; Algorithm design and analysis; Cepstral analysis; Emotion recognition; Filter bank; Mel frequency cepstral coefficient; Pattern recognition; Speech analysis; Speech recognition; Sun;
Conference_Titel :
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4994-1
DOI :
10.1109/ICIECS.2009.5365821
