Labelling of Hindi Speech. Issue 2 (3rd March 2016) - Balyan, Archana; Dev, Amita; Kumari, Ruchika; Agrawal, Shyam Sunder
ABSTRACT: The goal of this paper is to obtain segmented and labelled speech at syllable level and also that the reasonable number of syllables may suffice the need for travel domain applications. A base-line group delay-based segmentation technique is applied on spoken speech sentences to generate labelled database at syllable level. The system is validated against 50 manually segmented speech utterances. The segmentation accuracy was evaluated by performing time-error analysis. It is observed that 63.07% syllables have time-error less than 30 ms. It is observed that vowels are more accurately segmented as compared to fricatives. The confidence interval is found to be 0.1147 ms for confidence level of 95%. This paper also presents implementation of algorithm for identifying syllables based on linguistic rules for Hindi words. After survey of the relevant literature, a set of rules are identified and implemented as a simple easy-to-implement algorithm. The text segmentation algorithm is tested on 2400 distinct words and algorithm performs with 99.5% accuracy for segmentation of written text.