Continuous Bangla Speech Segmentation using Short-term Speech Features Extraction Approaches
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...
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| Veröffentlicht in: | International journal of advanced computer science & applications 2012-01, Vol.3 (11) |
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| description | 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%. |
| doi_str_mv | 10.14569/IJACSA.2012.031121 |
| format | Article |
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| ispartof | International journal of advanced computer science & applications, 2012-01, Vol.3 (11) |
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| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Algorithms Centroids Feature extraction Frequency domain analysis Segmentation Sentences Sequences Speech Speech recognition Time domain analysis Word boundaries Words (language) |
| title | Continuous Bangla Speech Segmentation using Short-term Speech Features Extraction Approaches |
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