most citedImproving Streaming End-to-End ASR on Transformer-based Causal Models with Encoder States Revision Strategies

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eess.AS2026

Balancing ASR and diarization in end-to-end LLMs for multi-talker speech recognition

Naijun Zheng, Yuke Lin, Sanli Tian +4

Multi-talker speech recognition is often addressed by combining automatic speech recognition (ASR) and speaker diarization in a pipeline system. Recently, LLM-based approaches have…

eess.AS2022★ 1 cited

Improving Streaming End-to-End ASR on Transformer-based Causal Models with Encoder States Revision Strategies

Zehan Li, Haoran Miao, Keqi Deng +4

There is often a trade-off between performance and latency in streaming automatic speech recognition (ASR). Traditional methods such as look-ahead and chunk-based methods, usually…