Abstract
The paper describes a speaker independent segmentation system for breaking Arabic uttered sentences into its constituent syllables. The goal is to construct a database of acoustical Arabic syllables as a step towards a syllable-based Arabic speech verification/recognition system. The proposed technique segments the utterances based on maxima extraction from delta function of 1st MFC coefficient. This method locates syllables boundaries by applying the template matching technique with reference utterances. The system was applied over a data set of 276 utterances to segment them into their 2544 constituent syllables. A segmentation success rate of about 91.5% was reached.
Highlights
Speech and natural language processing (SNLP) is a vital topic in recent research
Arabic is the spoken language in 60 countries around the world, so it is the second most spoken language in terms of the number of speakers [1]
Our system seeks to perform accurate allocation of syllables boundaries from continuous speech as a step towards building an Arabic database that contributes in developing many applications, such as: a) Diagnosis and treatment of speaking pathology
Summary
Speech and natural language processing (SNLP) is a vital topic in recent research. Computer Aided Language Learning (CALL) systems have received considerable attention in recent years. CALL system are used to improve learning and to evaluate pronunciation quality of speakers. One of the most important issues in the Arabic world is the learning of Quran recitations [2]. A robust language learning system should have a vocabulary database in order to recognize uttered speech, localize and identify pronunciation mistakes and provide meaningful feedback to help users to improve their performance. A new method for the automatic segmentation of Arabic audio signal into its syllables is introduced. Our system seeks to perform accurate allocation of syllables boundaries from continuous speech as a step towards building an Arabic database that contributes in developing many applications, such as: a) Diagnosis and treatment of speaking pathology. This paper is organized as follows; section 2 presents segmentation.
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