Unverified50% confidenceFactExact time
Whisper、SoundStorm、AudioLM等语音基础模型推动了端到端范式走向成熟
1
Sources
50%
Confidence
Long-term
Relevance
7/20/2026
First Seen
Sources
Related Claims
VerifiedEnd-to-end voice models take audio directly as input and output, performing understanding and generation at the audio token level while preserving acoustic features such as intonation, speaking rate, sighs, and laughter.80% similarUnverifiedThe new end-to-end voice model is trained directly at the audio level, without first converting speech to text, and can directly capture acoustic features and emotions.75% similarVerifiedThe new generation of voice interaction has shifted to an end-to-end multimodal model architecture that understands and generates directly at the speech signal level, compressing latency and preserving paralinguistic information.75% similarVerifiedSpeech recognition technology has evolved from hidden Markov models (HMMs) to recurrent neural networks (RNNs) and then to end-to-end models.75% similarUnverified标准Whisper模型在处理歌声时准确率会下降，社区开发了whisper-timestamped等变体实现逐词级别时间轴对齐74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/572581API
curl https://kongchang.com/api/v1/knowledge/claims/572581MCP
get_claim(id=572581)