arXiv: cs.AI preprintsInternational6 November 2026
Murmur: Efficient Long-Context ASR Inference with Hierarchical Chunking
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arXiv:2606.01483v2 Announce Type: replace-cross Abstract: Long-form automatic speech recognition (ASR) requires both high accuracy and low inference latency, but existing systems fall short of handling the trade-off between the two. Chunk-based approaches process audio in parallel windows for low latency, but lose cross-chunk context and need brittle heuristics to align speakers and timestamps at boundaries. Long-context ASR models transcribe everything in a single pass for better accuracy, but run several times slower, and a single repetition loop can corrupt the entire output. In this paper,
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