Solutions for realizing low latency response
To achieve low latency response in anthropomorphic speech dialogue systems, optimization is required at both technical architecture and data processing levels:
- Streaming Processing Architecture: SpeechGPT 2.0-preview uses an ultra-low bit rate streaming speech Codec with joint semantic-acoustic modeling to enable real-time codec processing of speech data.
- Lightweight modeling: The system is optimized based on a 7B-scale model to reduce computational complexity while maintaining linguistic power.
- preprocessing acceleration: The system is equipped with an efficient speech data crawling system and a multifunctional cleaning pipeline to ensure the quality and processing speed of the input data.
- hardware adaptation: The flash-attn optimization library, which requires special attention when installing, improves the efficiency of the graphics card's attention calculations.
Specifically: 1) deploy the Codec module correctly; 2) ensure that acceleration components such as flash-attn are installed according to the documentation; 3) optimize the server resource allocation. Through these measures can realize the hundred milliseconds response latency mentioned in the article.
This answer comes from the articleSpeechGPT 2.0-preview: an end-to-end anthropomorphic speech dialog grand model for real-time interactionThe
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