Analysis and detection of vocal effort for speech recognition.

The impact of changes in a speaker's vocal effort on the performance of automatic speech recognition is the research target. Firstly, this paper performed analysis for sound intensity level, duration, frame energy distribution and spectral tilt, and proposed vocal effort detector based on GMM by using these phonetic properties and acoustic properties. Then, it studied impact of vocal effort variability on automatic speech recognition, and presented multiple model framework approach to improve robustness of speech recognition system. Experiments conducted on isolated-word recognizer show that accompanied by a slight decline for normal mode, significantly improvement of recognition accuracy for the remaining four vocal effort modes can be achieved. Thus, potential of the method is demonstrated. [ABSTRACT FROM AUTHOR]