By converting audio into discrete tokens, the system allows a large language model (LLM) to generate speech just as it generates text. This simplifies architecture by leveraging existing model capabilities, avoiding the need for entirely separate speech synthesis systems.
The technical report introduces an innovative token-based architecture but lacks crucial validation. It omits comparative quality metrics, latency measurements, and human evaluation scores, leaving practitioners unable to assess its real-world performance against existing systems.
The system offers two tokenizer options: 25 Hz for high-detail audio and 12 Hz for faster generation. This practical approach acknowledges that different applications have different needs, prioritizing either computational efficiency or acoustic fidelity rather than forcing a one-size-fits-all solution.