13 citations · 44 across the 18 of their papers we have counts for
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cs.CL2019★ 6 cited
A New GAN-based End-to-End TTS Training Algorithm
Haohan Guo, Frank K. Soong, Lei He +1
End-to-end, autoregressive model-based TTS has shown significant performance improvements over the conventional one. However, the autoregressive module training is affected by the…
cs.CL2019★ 2 cited
Exploiting Syntactic Features in a Parsed Tree to Improve End-to-End TTS
Haohan Guo, Frank K. Soong, Lei He +1
The end-to-end TTS, which can predict speech directly from a given sequence of graphemes or phonemes, has shown improved performance over the conventional TTS. However, its predict…
cs.SD2019★ 13 cited
Feature reinforcement with word embedding and parsing information in neural TTS
Huaiping Ming, Lei He, Haohan Guo +1
In this paper, we propose a feature reinforcement method under the sequence-to-sequence neural text-to-speech (TTS) synthesis framework. The proposed method utilizes the multiple i…