An efficient model for text-to-speech synthesis in Indian languages

摘要

Speech Synthesis deals with artificial production of speech and a text-to-speech system (TTS) in this aspect converts natural language text into a spoken waveform or speech. There are a number of TTS systems available today for different languages, still Indian languages are lacking behind in providing high quality synthesized speech. Even though almost all Indian languages share a common phonetic base, till now a generic model for all official Indian languages is not available. Also, the existing speech synthesis techniques are found to be less effective in the scripting format of Indian languages. Considering the intelligibility of speech production and increasing memory requirement in concate-native speech synthesis technique, in this paper, we have proposed an efficient technique for text-to-speech synthesis in Indian languages. The model uses a pronunciation rule based waveform concatenation approach, to produce intelligible speech minimizing the memory requirement. To show the effectiveness of the technique, at an initial step of implementation the Odia (formerly Oriya), Bengali and Hindi languages are considered. The model is being compared with the existing technique and the results of our experiments show our technique outperforms the existing technique.