Word boundary hypothesization for continuous speech in Hindi based on F₀ patterns

Abstract

This paper proposes an algorithm based on F₀ patterns to hypothesize word boundaries and function words in continuous speech in Hindi. It makes use of the properties of F₀ contour such as declination tendency, resetting and fall-rise patterns in Hindi. The syllabic units are identified by using the energy contour, pitch and the first order LP coefficient. Each syllabic unit is assigned an accent value L (Low), H or h (High) by (i) comparing the F₀ value at the mid point of each syllabic nucleus with that of the previous syllabic unit and (ii) comparing the F₀ values at two different points within each syllabic unit in a sequence having an accent value L. Word boundaries are placed between the adjacent syllabic units (i) H and L, (ii) h and L, (iii) L and L, (iv) L and h and (v) H and h. An evaluation conducted on a corpus of 50 sentences in Hindi read aloud by five native speakers in an ordinary office environment showed that about 74 percent of the word boundaries and about 28 percent of the function words were correctly identified. The results of the word boundary hypothesization can be used to improve the performance of the acoustic-phonetic, lexical and syntactic modules in a speech-to-text conversion system. Robustness of the algorithm in handling noisy speech input conditions and telephone speech are also discussed.