Myanmar Continuous Speech to Isolated Word Segmentation
Keywords:
Myanmar language, Energy based VAD, ZCR, Myanmar Tone LengthAbstract
This paper proposes a word segmentation method for Myanmar continuous speech. This system consists of speech processing inclusive of segment boundary detection for isolated words which used zero crossing, duration and energy techniques. Inaccurate segment boundaries are a major cause of errors in automatic speech recognition and a pre-processing stage that segments the speech signal into periods of speech and non-speech is invaluable in improving the recognition accuracy. We propose a combination of three audio features that is energy based voice activity detection, zero crossing rate (ZCR) and duration length for the speech/non-speech detection. Each feature has unique properties to differentiate speech and non-speech segments. We evaluate the results by dividing the speech sample into some segments and used the zero crossing rate, energy based VAD and Myanmar tone length to separate the parts of speech. The algorithm is tested on speech samples that are recorded as sentences of Myanmar speech. The results show that the algorithm managed to segment almost 98.5% of the Myanmar words for all recorded sentences.
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