Unverified50% confidenceTradeoffExact time
在语码转换音频上微调模型效果最自然，但数据采集标注成本高，且对端侧小模型微调需注意灾难性遗忘问题
1
Sources
50%
Confidence
Long-term
Relevance
8/21/2026
First Seen
Sources
Related Claims
Unverified自回归模型（如VALL-E）逐token预测语音离散表征，能建模长程依赖和丰富韵律，但存在累积误差；非自回归模型（如FastSpeech）并行生成速度快但表现力受限77% similarUnverifiedFull multimodal large models that support voice input and output score far lower on agent benchmark datasets than mainstream reasoning models.75% similarUnverifiedVoice drift is a known technical challenge in autoregressive speech generation models, where accumulated errors during step-by-step generation cause the timbre to deviate from the target speaker.74% similar
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