Discriminative classification model of filled pause and elongation for Malay language spontaneous speech / Raseeda Hamzah
Automated speech recognition (ASR) for spontaneous speech poses extra challenge compared to read speech as it contains varied speaking rates, poor phonation and disfluencies. Studies have shown that filled pause is one of the most common disfluencies of spontaneous speech characteristic where it pre...
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| Format: | Book Section |
| Language: | English |
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Institute of Graduate Studies, UiTM
2016
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| Online Access: | http://ir.uitm.edu.my/id/eprint/20064/ http://ir.uitm.edu.my/id/eprint/20064/1/ABS_RASEEDA%20HAMZAH%20TDRA%20VOL%2010%20IGS%2016.pdf |
| Summary: | Automated speech recognition (ASR) for spontaneous speech poses extra challenge compared to read speech as it contains varied speaking rates, poor phonation and disfluencies. Studies have shown that filled pause is one of the most common disfluencies of spontaneous speech characteristic where it presents considerable problems for ASR performance. In many filled pause studies, the hindering factor is that filled pause being often recognized as short words which particularly has semantic meaning, such as „um” can be recognized as „thumb” or „arm”. This problem becomes especially pertinent where a vowel sound of normal word being relatively long at any position in an utterance, both within a word as well as between words which formerly known as elongation. The existence of elongation causes normal word falsely detected as filled pause due to their similar acoustical feature patterns. Classifying elongation as filled pause affects ASR”s performance as eliminating normal words from recognition may modify the intended context of a speech. Therefore, the main aim of this research is to classify filled pause and elongation into its own classes by constructing a discriminative classification model from the extracted acoustical features. A large number of signal features have been employed for the problem of discriminating filled pause and elongation. Several wellestablished features such as Formant Frequency (FF), Fundamental Frequency (F0), Mel Frequency Cepstral Coefficients (MFCC), Zero Crossing Rates (ZCR) and Short Time Energy (STE) were used in this research. These features are carefully chosen to emphasize signal characteristics that differ between filled pause and elongation… |
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