yhytoto12/revert-Qwen2.5-3B
yhytoto12/revert-Qwen2.5-3B is a 3.1 billion parameter Qwen2.5-3B-Instruct fine-tuned model developed by Sang Hoon Woo, Sehun Lee, Kang-wook Kim, and Gunhee Kim. This model functions as a latency-efficient verbalizer, translating complex LLM thoughts into natural, concise, and speech-ready text. It is a core component of the Think-Verbalize-Speak (TVS) framework, designed to enhance speech naturalness and conciseness in spoken dialogue systems with minimal impact on reasoning. The model supports a context length of 32768 tokens and is optimized for intermediate text generation for speech synthesis.
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Model Overview
yhytoto12/revert-Qwen2.5-3B is a 3.1 billion parameter model, fine-tuned from Qwen/Qwen2.5-3B-Instruct, developed by Sang Hoon Woo, Sehun Lee, Kang-wook Kim, and Gunhee Kim. It serves as a verbalizer within the Think-Verbalize-Speak (TVS) framework, designed to bridge the gap between complex LLM reasoning and comprehensible spoken delivery. The model's primary function is to convert intricate "thoughts" generated by an LLM into natural, concise, and speech-ready text, which can then be processed by a Text-to-Speech (TTS) system.
Key Capabilities
- Verbalization: Translates complex LLM outputs into text optimized for verbal delivery.
- Latency-efficient: Implements incremental and asynchronous summarization for efficient processing.
- Speech Naturalness: Enhances the naturalness and conciseness of speech outputs from LLMs.
- Reasoning Preservation: Designed to maintain the full reasoning capacity of the underlying LLM by decoupling reasoning from verbal delivery.
Use Cases
- Spoken Dialogue Systems: Ideal for integrating advanced LLM reasoning into conversational AI.
- Intermediate Text Generation: Specifically for preparing LLM outputs for Text-to-Speech (TTS) systems.
Limitations
- Not intended for direct end-to-end reasoning or standalone speech synthesis.
- Performance is influenced by the base LLM (Qwen2.5) and training datasets (GSM8k, 2WikiMultihopQA).
- Effectiveness is contingent on integration within the complete TVS framework, including a "Think" model and speech synthesizer.
For detailed evaluation and methodology, refer to the associated paper: Think, Verbalize, then Speak: Bridging Complex Thoughts and Comprehensible Speech.