Automatic speech segmentation in syllable centric speech recognition system

Speech recognition is the process of understanding the human or natural language speech by a computer. A syllable centric speech recognition system in this aspect identifies the syllable boundaries in the input speech and converts it into the respective written scripts or text units. Appropriate segmentation of the acoustic speech signal into syllabic units is an important task for development of highly accurate speech recognition system. This paper presents an automatic syllable based segmentation technique for segmenting continuous speech signals in Indian languages at syllable boundaries. To analyze the performance of the proposed technique, a set of experiments are carried out on different speech samples in three Indian languages Hindi, Bengali and Odia and are compared with the existing group delay based segmentation technique along with the manual segmentation technique. The results of all our experiments show the effectiveness of the proposed technique in segmenting the syllable units from the original speech samples compared to the existing techniques. © 2015, Springer Science+Business Media New York.