4 accepted papers
Existing automatic audio generation methods struggle to generate podcast-like audio programs effectively. The key challenges lie in in-depth content generation, appropriate and expressive voice production. This paper proposed PodAgent, a comprehensive framework for creating audio programs. PodAgent…
A trajectory tiling based, hybrid TTS is revisited in this study for improving its synthesis performance. A combination of Transformer encoder and RNN based decoder architecture where two-level, at both word and Chinese phonetic alphabet letter levels, linguistic representation is exploited to gener…
A frame-unit-selection based voice conversion system proposed earlier by us is revisited here to enhance its performance in both speech naturalness and speaker similarity. Speaker independent, bilingual (Mandarin Chinese and American English) deep neural net (DNN) acoustic model’s output, frame-leve…
We propose a Kullback-Leibler divergence (KLD) and deep neural net (DNN) based approach to cross-lingual TTS (CL-TTS) training. A speaker independent DNN (SI-DNN) ASR is used to equalize the speaker difference between a source speaker in L1 and a reference speaker in L2. Two speaker dependent GMM-HM…