Title :
An HMM based semi-automatic syllable labeling system for Manipuri language
Author :
Nandakishor, Salam ; Dutta, S.K. ; Singh, L. Joyprakash
Author_Institution :
Dept. of ECE, Speech & Image Process. Lab., Shillong, China
Abstract :
This paper describes the development of a SemiAutomatic Syllable Labeling System for the Manipuri language which is a scheduled Indian language of Tibeto-Burman origin and very highly agglutinative language. A system is developed using HMM tool kit (HTK), version 3.4 and later analyzed using popular speech analysis software (WaveSurfer), version 8.5.8. The HTK has been used for training, segmentation and labeling of the data. The system can segment the manual phonetic transcription into syllables with timing information. The syllable offset and onset of the automatic and the manual syllable labeling are compared to calculate the “Time Deviation” (W) of each syllable. We have found the “Average Deviation” of the syllables of our system is 25 ms. The Detection Rate of the syllables of the system is calculated by considering various “Time Deviations”.
Keywords :
hidden Markov models; natural language processing; speech processing; HMM based semiautomatic syllable labeling system; HMM tool kit; Indian language; Manipuri language; Tibeto-Burman language; WaveSurfer speech analysis software; data labeling; data segmentation; data training; hidden Markov model; phonetic transcription; syllable average deviation; syllable detection rate; syllable time deviation; timing information; Acoustics; Feature extraction; Hidden Markov models; Labeling; Manuals; Speech; Speech recognition; HTK; Manipuri; Phonetic segmentation; Phonetic transcription; Syllable labeling; WaveSurfer;
Conference_Titel :
Computing, Communication & Automation (ICCCA), 2015 International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-8889-1
DOI :
10.1109/CCAA.2015.7148548
