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PromptTTS: Controllable Text-to-Speech with Text Descriptions
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Using a text description as prompt to guide the generation of text or images (e.g., GPT-3 or DALLE-2) has drawn wide attention recently. Beyond text and image generation, in this work, we explore the possibility of utilizing text descriptions to guide speech synthesis. Thus, we develop a text-to-speech (TTS) system (dubbed as PromptTTS) that takes a prompt with both style and content descriptions as input to synthesize the corresponding speech. Specifically, PromptTTS consists of a style encoder and a content encoder to extract the corresponding representations from the prompt, and a speech decoder to synthesize speech according to the extracted style and content representations. Compared with previous works in controllable TTS that require users to have acoustic knowledge to understand style factors such as prosody and pitch, PromptTTS is more user-friendly since text descriptions are a more natural way to express speech style (e.g., ''A lady whispers to her friend slowly''). Given that there is no TTS dataset with prompts, to benchmark the task of PromptTTS, we construct and release a dataset containing prompts with style and content information and the corresponding speech. Experiments show that PromptTTS can generate speech with precise style control and high speech quality. Audio samples and our dataset are publicly available.
Forward citations
Cited by 3 Pith papers
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ParaSpeechCLAP: A Dual-Encoder Speech-Text Model for Rich Stylistic Language-Audio Pretraining
Dual-encoder speech-text models trained on rich intrinsic and situational style captions outperform prior CLAP-style baselines on retrieval, classification, and inference-time TTS style guidance.
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RepeaTTS: Towards Feature Discovery through Repeated Fine-Tuning
PCA of repeated synthesized utterances with fixed inputs can reveal controllable prosodic features that can be enrolled as new prompts via fine-tuning.
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EmoNews: A Spoken Dialogue System for Expressive News Conversations
An emotional spoken dialogue system that uses a sentiment analyzer to pick an emotion tag and PromptTTS to synthesize matching speech outperforms a neutral baseline on perceived emotional appropriateness, but not sign...
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