Model spectrum-progression with DTW and ANN for speech synthesis

In this paper, an ANN based spectrum-progression model (SPM) is proposed. This model is intended to improve the fluency level of synthetic Mandarin speech under the situation that only a small training corpus is available. In constructing this model, first each target syllable is matched with its reference syllable by using DTW. Then, each warped path, i.e. spectrum-progression path, is time normalized to fixed dimensions, and used to train an ANN based SPM. After training, the SPM is used together with other modules such as text analysis, prosody parameter generation, and signal sample generation to synthesize Mandarin speech. Then, the synthetic speech is used to conduct perception tests. The test results show that the SPM proposed here can indeed improve the fluency level noticeably.