Hybrid methods of brandt’s generalised likelihood ratio and short-term energy for malay word speech segmentation

Autor:	Noraini Seman, Ahmad Firdaus Norazam
Rok vydání:	2019
Předmět:	Control and Optimization Computer Networks and Communications Hardware and Architecture Computer science Speech recognition Signal Processing language Segmentation Electrical and Electronic Engineering Speech segmentation language.human_language Information Systems Malay
Zdroj:	Indonesian Journal of Electrical Engineering and Computer Science. 16:283
ISSN:	2502-4760 2502-4752
Popis:	Speech segmentation is an important part for speech recognition, synthesizing and coding. Statistical based approach detects segmentation points via computing spectral distortion of the signal without prior knowledge of the acoustic information proved to be able to give good match, less omission but lot of insertion. In this study the segmentation is done both manually and automatically using Malay words in traditional Malay poetry. This study proposed a hybrid method of Brandt’s generalized likelihood ratio (GLR) and short-term energy algorithm. The Brandt’s algorithm tries to estimate the abrupt change in energy to determine the segmentation points. A total of five Pantun are used in read mode and spoken by one male student in a noise free room. Experiments are conducted to see the the accuracy, insertion, and omission of the segmentation points. Experimental results show on average 80% accuracy with 0.2 second time tolerance for automatic segmentation with the algorithm having no knowledge of the acoustic characteristics.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::4b4fae3bbaaffd2db9783915a122ccd0 https://doi.org/10.11591/ijeecs.v16.i1.pp283-291 Zobrazit plný text záznamu