Seed-TTS
High-quality, versatile speech synthesis model series
Product Details
Seed-TTS is a series of large-scale autoregressive text-to-speech (TTS) models launched by ByteDance that can generate speech that is indistinguishable from human speech. It excels in speech context learning, speaker similarity, and naturalness, and can be fine-tuned to further improve subjective ratings. Seed-TTS also provides superior control over speech attributes such as emotion, and can generate highly expressive and diverse speech. Furthermore, a self-distillation method is proposed for speech decomposition, as well as a reinforcement learning method to enhance model robustness, speaker similarity, and controllability. Also presented is Seed-TTSDiT, a non-autoregressive (NAR) variant of the Seed-TTS model, which adopts a completely diffusion-based architecture and does not rely on pre-estimated phoneme durations for speech generation through end-to-end processing.
Main Features
How to Use
Target Users
Seed-TTS is suitable for enterprises and developers who require high-quality speech synthesis, such as smart assistants, audiobooks, virtual assistants, voice interaction systems, etc. Its high naturalness and controllability enable it to better meet user needs and improve user experience when providing voice services.
Examples
Smart assistant uses Seed-TTS to generate natural speech to communicate with users
Audiobook apps use Seed-TTS to provide smooth reading services for books
Virtual assistant delivers emotionally rich voice feedback via Seed-TTS
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