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Detailed analysis of tonal features for Tibetan Lhasa dialect is an important task for Tibetan automatic speech recognition (ASR) applications. However, it is difficult to utilize tonal information because it remains controversial how many tonal patterns the Lhasa dialect has. Therefore, few studies have focused on modeling the tonal information of the Lhasa dialect for speech recognition purpose...
The objective of this paper is to study the effect of speaking mode on spoken term detection (STD) system. The experiments are conducted with respect to query words recorded in isolated manner and words cut out from continuous speech. Durations of phonemes in query words greatly vary between these two modes. Hence pattern matching stage plays a crucial role which takes care of temporal variations...
In this paper, the voice recognition algorithm based on HMM (Hidden Markov Modeling) is analyzed in detail. The HMM voice recognition algorithm is explained and the importance of voice information DB is revealed for better improvement of voice recognition rate. The feature vector of each voice characteristic parameter is chosen by means of MFCC (Mel Frequency Cepstral Coefficients). The extracting...
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