Global syllable set for building speech synthesis in Indian languages

Abstract

Indian languages are syllabic in nature where many syllables are found common across its languages. This motivates us to build a global syllable set by combining multiple language syllables to build a synthesizer which can borrow units from a different language when the required syllable is not found. Such synthesizer make use of speech database in different languages spoken by different speakers, whose output is likely to pick units from multiple languages and hence the synthesized utterance contains units spoken by multiple speakers which would annoy the user. We intend to use a cross lingual Voice Conversion framework using Artificial Neural Networks (ANN) to transform such an utterance to a single target speaker.