Time and space-efficient architecture for a corpus-based text-to-speech synthesis system

This paper proposes a time and space efficient architecture for a text-to-speech synthesis system (TTS). The proposed architecture can be efficiently used in those applications with unlimited domain, requiring multilingual or polyglot functionality. The integration of a queuing mechanism, heterogeneous graphs and finite-state machines gives a powerful, reliable and easily maintainable architecture for the TTS system. Flexible and language-independent frameworks efficiently integrate all those algorithms used within the scope of the TTS system. Heterogeneous relation graphs are used for linguistic information representation and feature construction. Finite-state machines are used for time and space efficient representation of language resources, for time and space efficient lookup processes, and the separation of language-dependent resources from a language-independent TTS engine. Its queuing mechanism consists of several dequeue data structures and is responsible for the activation of all those TTS engine modules having to process the input text. In the proposed architecture, all modules use the same data structure for gathering linguistic information about input text. All input and output formats are compatible, the structure is modular and interchangeable, it is easily maintainable and object oriented. The proposed architecture was successfully used when implementing the Slovenian PLATTOS corpus-based TTS system, as presented in this paper.