Abstract: A multi-lingual text-to-speech system and method processes a text to be synthesized via an acoustic-prosodic model selection module and an acoustic-prosodic model mergence module, and obtains a phonetic unit transformation table. In an online phase, the acoustic-prosodic model selection module, according to the text and a phonetic unit transcription corresponding to the text, uses at least a set controllable accent weighting parameter to select a transformation combination and find a second and a first acoustic-prosodic models. The acoustic-prosodic model mergence module merges the two acoustic-prosodic models into a merged acoustic-prosodic model, according to the at least a controllable accent weighting parameter, processes all transformations in the transformation combination and generates a merged acoustic-prosodic model sequence. A speech synthesizer and the merged acoustic-prosodic model sequence are further applied to synthesize the text into an L1-accent L2 speech.

Abstract: A multi-lingual text-to-speech system and method processes a text to be synthesized via an acoustic-prosodic model selection module and an acoustic-prosodic model mergence module, and obtains a phonetic unit transformation table. In an online phase, the acoustic-prosodic model selection module, according to the text and a phonetic unit transcription corresponding to the text, uses at least a set controllable accent weighting parameter to select a transformation combination and find a second and a first acoustic-prosodic models. The acoustic-prosodic model mergence module merges the two acoustic-prosodic models into a merged acoustic-prosodic model, according to the at least a controllable accent weighting parameter, processes all transformations in the transformation combination and generates a merged acoustic-prosodic model sequence. A speech synthesizer and the merged acoustic-prosodic model sequence are further applied to synthesize the text into an L1-accent L2 speech.