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arXiv · 2309.13509

Coco-Nut: Corpus of Japanese Utterance and Voice Characteristics Description for Prompt-based Control

Aya Watanabe·Shinnosuke Takamichi·Yuki Saito·Wataru Nakata·Detai Xin·Hiroshi Saruwatari
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Abstract

In text-to-speech, controlling voice characteristics is important in achieving various-purpose speech synthesis. Considering the success of text-conditioned generation, such as text-to-image, free-form text instruction should be useful for intuitive and complicated control of voice characteristics. A sufficiently large corpus of high-quality and diverse voice samples with corresponding free-form descriptions can advance such control research. However, neither an open corpus nor a scalable method is currently available. To this end, we develop Coco-Nut, a new corpus including diverse Japanese utterances, along with text transcriptions and free-form voice characteristics descriptions. Our methodology to construct this corpus consists of 1) automatic collection of voice-related audio data from the Internet, 2) quality assurance, and 3) manual annotation using crowdsourcing. Additionally, we benchmark our corpus on the prompt embedding model trained by contrastive speech-text learning.

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Aya Watanabe, Shinnosuke Takamichi, Yuki Saito, Wataru Nakata, Detai Xin, Hiroshi Saruwatari. 2023-09-24. Coco-Nut: Corpus of Japanese Utterance and Voice Characteristics Description for Prompt-based Control. https://arxiv.org/abs/2309.13509

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