Modifying syllable durations for personalizing chinese mandarin tts using small corpus

Abstract

A method and system for personalizing synthetic speech from a text-to-speech (TTS) system is disclosed. The method uses linguistic feature vectors to correct/modify the synthetic speech, particularly Chinese Mandarin speech. The linguistic feature vectors are used to generate or retrieve onset and rime scaling factors encoding differences between the synthetic speech and a user's natural speech. Together, the onset and rime scaling factors are used to modify every word/syllable of the synthetic speech from a TTS system, for example. In particular, segments of synthetic speech are either compressed or stretched in time for each part of each syllable of the synthetic speech. After modification, the synthetic speech more closely resembles the speech patterns of a speaker for which the scaling factors were generated. The modified synthetic speech may then be transmitted to a user and played to the user via a mobile phone, for example. The linguistic feature vectors are constructed based on a plurality of feature attributes including at least a group ID attribute, voicing attribute, complexity attribute, nasality attribute, and tone for the current syllable. The invention is particularly useful when the user speech corpus is either small or otherwise incomplete.