Source URL: https://arxiv.org/abs/2503.01710
Source: Hacker News
Title: Spark-TTS: Text-2-Speech Model Single-Stream Decoupled Tokens [pdf]
Feedly Summary: Comments
AI Summary and Description: Yes
Summary: The text discusses Spark-TTS, an innovative LLM-based text-to-speech model that contributes to advancements in zero-shot TTS synthesis. Its efficient design allows for customizable voice generation through a unique token representation and a substantial dataset, making it valuable for AI and speech processing professionals.
Detailed Description: The document introduces “Spark-TTS,” a new system that enhances the process of text-to-speech (TTS) synthesis by leveraging advancements in large language models (LLMs). Here are the major points of its significance:
– **Innovative Architecture**:
– Spark-TTS utilizes a single-stream speech codec known as BiCodec, which separates speech representation into two token types:
– Low-bitrate semantic tokens for linguistic content.
– Fixed-length global tokens for speaker attributes.
– This approach simplifies the model’s architecture compared to existing multi-stage systems, improving efficiency.
– **Control Upgrades**:
– The system supports coarse-grained control for broader attributes like gender and speaking style.
– It also allows fine-grained adjustments such as pitch values and speaking rates, enhancing its user-friendly capabilities.
– **Dataset Contribution**:
– The introduction of VoxBox, a 100,000-hour dataset with detailed attribute annotations, facilitates further research in controllable TTS, making it a vital resource for the community.
– **State-of-the-Art Achievements**:
– Experimental results show that Spark-TTS achieves leading performance in zero-shot voice cloning, signifying advances over previous reference-based synthesis methods.
– **Availability of Resources**:
– The source code, pre-trained models, and audio samples are made available for public access which fosters transparency and collaboration in research.
Overall, Spark-TTS demonstrates significant advancements in TTS technology, especially with its innovative architecture and extensive dataset, indicating potential implications for voice synthesis applications across various AI domains.