Unverified50% confidenceTradeoffExact time
Jointly predicting speaker labels and time boundaries requires additional transcription corpora with speaker and time boundary annotations for training, and joint decoding may slightly affect the accuracy of plain text recognition.
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50%
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Long-term
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10/29/2026
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UnverifiedTraditional keyword matching or rule engines can only process literal signals, whereas large language models have acquired a holistic understanding of semantics and sentiment through pre-training on massive amounts of human text.72% similarUnverifiedSpeaker diarization results depend on voiceprint clustering and are prone to errors with overlapping speech, short interjections, similar voices, or mid-utterance speaker changes, and the labels themselves contain no true identity information.71% similarUnverifiedKeyword routing relies on a preset vocabulary to match intents and is fragile to synonymous rewording and colloquial expressions; semantic routing is implemented through vector similarity or LLM classification, at the cost of added latency and expense.70% similarUnverifiedThe improvements from strengthening language differentiation capability are measured on continuous phonetic and higher-level linguistic metrics, and whether they extend to actual downstream tasks warrants attention.70% similarUnverified当训练数据中某些文本出现频率极高时，大语言模型可能产生记忆化（Memorization）现象，能够近乎逐字输出特定段落70% similar
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