Developing an enriched natural language grammar for prosodically-improved concent-to-speech synthesis

Abstract

The need for interacting with machines using spoken natural language is growing, along with the expectation that synthetic speech in this context sound natural. Such interaction includes answering questions, where prosody plays an important role in producing natural English synthetic speech by communicating the information structure of utterances. CCG is a theoretical framework that exploits the notion that, in English, information structure, prosodic structure and syntactic structure are isomorphic. This provides a way to convert a semantic representation of an utterance into a prosodically natural spoken utterance. GF is a framework for writing grammars, where abstract tree structures capture the semantic structure and concrete grammars render these structures in linearised strings. This research combines these frameworks to develop a system that converts semantic representations of utterances into linearised strings of natural language that are marked up to inform the prosody-generating component of a speech synthesis system.