Automatic word-level lexical stress labelling for Filipino speech - Agoncillo, Arvin Jeremy C.; Galang, Mio Miguel O.; Tejerero, Kristina R. (2011)
An accurate stress model is very important in building robust automatic speech recognition and automatic speech synthesis systems since lexical stress placement can greatly influence word meaning. An automatic lexical stress labelling system for isolated Filipino words was developed in this research. Recordings of isolated words of native Filipino speakers from the Filipino Speech Corpus (FSC) were manually-transcribed and stress-labelled. Pitch, intensity and duration measurements were done on the isolated sub-corpus and the relationships between lexical stress and its three acoustic correlates were observed. Feature extraction on the sub-corpus resulted in 13 speech parameters extraced on every syllable. An automatic word-level lexical stress labelling system using support vector machine (SVM) classifiers was developed after feature extraction. This module was developed using 80% of the gathered features and then tested using the remaining 20%. All, 16,382 possible combinations of the 13 parameters and 2 SVM kernels were explored in the development of the system. Among all the tested primary stress classifiers, the radial basis function SVM classifier using seven parameters yielded the highest testing accuracy of 74.68%. Similarly, among the 16,382 SVM-based secondary stress classifiers, the radial basis function SVM classifier using eight parameters yielded the highest testing accuracy of 90.82%. To aid in the analysis of speech inputs, a syllable segmentation module based on Teager energy was developed to suggest the syllable boundaries of an input word with a syllabication accuracy of 63.40%. The syllable segmentation and stress labelling modules were integrated into a Filipino speech analysis system with a graphical user interface (GUI). The GUI includes a correction option for the possible errors of the syllable segmentation module. The system contributes to the advancement of research in speech signal processing for Filipino speech and is a pioneering quantitative study of lexical stress in Filipino. As a whole, this project was geared towards the development of accurate language models and the standardization of Philippine languages.
Undergraduate student project (B.S. Electronics and Communications Engineering, B.S. Computer Engineering)--University of the Philippines, Diliman.
Keywords: Automatic speech recognition; Filipino language -- Tone; Lexical stress labelling system; Filipino speech corpus