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Found 7 papers, 0 papers with code
StyleSpeech: Self-supervised Style Enhancing with VQ-VAE-based Pre-training for Expressive Audiobook Speech Synthesis
Both objective and subjective evaluations demonstrate that our proposed method can effectively improve the naturalness and expressiveness of the synthesized speech in audiobook synthesis especially for the role and out-of-domain scenarios.
Large-Scale Automatic Audiobook Creation
In this work, we present a system that can automatically generate high-quality audiobooks from online e-books.
MuLanTTS: The Microsoft Speech Synthesis System for Blizzard Challenge 2023
In this paper, we present MuLanTTS, the Microsoft end-to-end neural text-to-speech (TTS) system designed for the Blizzard Challenge 2023.
ContextSpeech: Expressive and Efficient Text-to-Speech for Paragraph Reading
Experiments show that ContextSpeech significantly improves the voice quality and prosody expressiveness in paragraph reading with competitive model efficiency.
ParaTTS: Learning Linguistic and Prosodic Cross-sentence Information in Paragraph-based TTS
To alleviate the difficulty in training, we propose to model linguistic and prosodic information by considering cross-sentence, embedded structure in training.
Self-supervised Context-aware Style Representation for Expressive Speech Synthesis
In this paper, we propose a novel framework for learning style representation from abundant plain text in a self-supervised manner.
The NNI Query-by-Example System for MediaEval 2015
This paper describes the system developed by the NNI team for the Query-by-Example Search on Speech Task (QUESST) in the MediaEval 2015 evaluation.
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