Thesis (M.Eng.) - Asian Institute of Technology, 1995

A thesis submitted in partial fulfilment of the requirement for the degree of Master of Engineering.

The pitch vanat10n that convey lexical infonnation about the meaning of a word is commonly refeITed to as a tone. Automatic speech recognition of tonal languages requires the recognition of tones associated with the syllables in addition to the phonemes for proper identification of the syllable. Here, in this thesis work, a general model for the automatic recognition of tones of syllables of tonal languages is developed. The pitch contour of the syllable is initially estimated using Subharmonic Summation as the Pitch Determination Algorithm and given as input to vector quantizer for correct recognition of tones associated with the syllable. The input vector is time aligned and pitch n01malised to remove inter and intraspeaker variations before being applied to the vector quantizer. A codebook is implemented containing reference vectors corresponding to each of the tones of the tonal language. A distortion measure is computed between the test vector and each of the reference vectors. The reference vector c01Tesponding to the least distortion is identified as the tone. The perfo1mance evaluation is done in MATLAB environment. Thai language is chosen as the tonal language for the pe1formance evaluation. Four isolated syllables, uttered by four speakers for all the five tones, are used for simulation. For noise-free speech the system gave 100% correct recognition of tones for the four speakers. Recognition rates of 98, 97, 97, 98, 93 and 93 % were obtained for signal-to-noise-ratios of 40 dB, 30 dB, 20 dB, 10 dB, 5 dB and 2 dB respectively for the worst case speaker.