Unverified50% confidenceFactExact time
Mainstream ASR systems typically require thousands to tens of thousands of hours of human-annotated audio to achieve usable accuracy.
1
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50%
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Long-term
Relevance
10/1/2026
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Related Claims
UnverifiedTraining modern neural network speech models typically requires hundreds or even thousands of hours of high-quality annotated audio.72% similarVerifiedTraditional speech synthesis systems required hours of annotated recordings to simulate a specific person's voice.71% similarUnverified现代主流ASR系统多基于Transformer架构，通过在海量音频-文本对上进行监督学习建立声学特征与文字序列的映射关系70% similarUnverified该设备本地ASR模块将语音转录为文字，语义理解与答案生成依赖上传云端的LLM完成，云端推理往返延迟通常在500ms至2秒之间68% similar
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