Continuous Bangla Speech Segmentation using Short-term Speech Features Extraction Approaches

Abstract

This paper presents simple and novel feature extraction approaches for segmenting continuous Bangla speech sentences into words/sub-words. These methods are based on two simple speech features, namely the time-domain features and the frequency-domain features. The time-domain features, such as short-time signal energy, short-time average zero crossing rate and the frequency-domain features, such as spectral centroid and spectral flux features are extracted in this research work. After the feature sequences are extracted, a simple dynamic thresholding criterion is applied in order to detect the word boundaries and label the entire speech sentence into a sequence of words/sub-words. All the algorithms used in this research are implemented in Matlab and the implemented automatic speech segmentation system achieved segmentation accuracy of 96%.

Authors and Affiliations

Md Mijanur Rahman , Md. Al-Amin Bhuiyan

Keywords

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  • EP ID EP135420
  • DOI 10.14569/IJACSA.2012.031121
  • Views 93
  • Downloads 0

How To Cite

Md Mijanur Rahman, Md. Al-Amin Bhuiyan (2012). Continuous Bangla Speech Segmentation using Short-term Speech Features Extraction Approaches. International Journal of Advanced Computer Science & Applications, 3(11), 131-138. https://europub.co.uk/articles/-A-135420