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VoxCPM1.5 - ModelBest's Open-Source End-to-End Speech Synthesis Model

Author: AI小集 · Original source: AI工具集

What is VoxCPM1.5

VoxCPM 1.5 is an advanced end-to-endtext-to-speech(TTS) model launched by ModelBest, focusing on context-aware speech generation and realistic voice cloning. The model generates continuous speech directly from text through an end-to-end diffusion autoregressive architecture, supports 44.1kHz high-sampling-rate audio cloning, and produces more refined generation results. At the same time, the model's generation efficiency is doubled, requiring only 6.25 tokens to generate 1 second of audio, and stability is enhanced with fewer artifacts. VoxCPM 1.5 provides deep customization features, supports LoRA and full fine-tuning, and helps developers build personalized speech models.

VoxCPM1.5

Main Features of VoxCPM1.5

  • High-Sampling-Rate Audio Cloning: Supports a 44.1kHz sampling rate and can clone more detailed voices from high-quality audio.
  • Efficient Speech Synthesis: The model's generation efficiency is improved, requiring only 6.25 tokens to generate 1 second of audio, with doubled speed and higher quality.
  • Context-Aware Speech Generation: Automatically adjusts intonation and style according to the text content to generate natural and fluent speech.
  • Deep Customization Capabilities: Adds LoRA and full fine-tuning scripts, supporting developers in personalized training and optimization.
  • Enhanced Stability: Reduces audio artifacts and optimizes speech generation for long texts.

Technical Principles of VoxCPM1.5

  • Tokenizer-Free Architecture: VoxCPM 1.5 adopts a tokenizer-free end-to-end architecture that directly generates continuous speech signals from text, avoiding the limitations brought by discrete tokenization in traditional TTS.
  • Diffusion Autoregressive Model: Based on an autoregressive architecture of a diffusion model, it achieves high-quality speech synthesis by gradually generating continuous representations of speech signals.
  • Hierarchical Language Modeling: Combines MiniCPM-4 language models and achieves implicit decoupling of semantics and acoustics through hierarchical modeling, improving the naturalness and expressiveness of speech.
  • FSQ Constraint: Uses technologies such as Flow Matching to optimize the stability of speech generation and ensure high-quality output of speech synthesis.
  • Efficient Real-Time Synthesis: Supports streaming synthesis, with RTF as low as 0.15, enabling low-latency real-time speech synthesis on consumer-grade GPUs.

VoxCPM1.5 Project Address

  • GitHub Repository：https://github.com/OpenBMB/VoxCPM
  • HuggingFace Model Library：https://huggingface.co/openbmb/VoxCPM1.5

Application Scenarios of VoxCPM1.5

  • Smart Home: Provides natural and fluent voice interaction for smart speakers, smart home appliances, and other devices, improving the user experience.
  • Audiobooks: Quickly converts text content into high-quality speech for producing audiobooks and podcasts.
  • Language Learning: Through voice cloning, it imitates the pronunciation of different languages and helps learners practice language pronunciation.
  • Game Character Voice Acting: Generates personalized voices for characters in games, enhancing the immersion of the game.
  • Brand Promotion: Through voice cloning, it generates the voice of brand spokespersons for advertising and promotion.