Proposes cross-talk reduction task with CTRnet and pseudo-label far-field separation (PuLSS) to train on real close-talk/far-field pairs, achieving SOTA ASR on CHiME-6 and outperforming guided source separation.
arXiv preprint arXiv:2509.14128 , year =
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A new multi-accent long-form call-center dialogue dataset for English ASR evaluation shows substantial performance variation across accents and segmentation methods.
Contextual Earnings-22 is a new benchmark dataset showing that scaled keyword prompting and boosting both deliver significantly better accuracy on custom vocabularies than standard academic tests.
Cascaded systems remain the most reliable for speech translation overall, but recent SpeechLLMs match or outperform them in many conditions while standalone speech models lag.
ASPIRin decouples speaking timing from token content via binary action space projection and applies GRPO with rule-based rewards to optimize interactivity in SLMs without semantic collapse or repetition.
Symphony is a medical-grade speech recognition system that decomposes transcription into specialized components and outperforms existing systems in clinical settings while matching them in general domains.
Classical codecs prove more robust to noise than neural codecs, speech enhancement significantly helps noise-affected codecs, and listening effort plus ASR-based metrics add useful nuance beyond basic intelligibility scores.
BUT's CHiME-9 MCoRec system conditions Parakeet-v2 ASR on AV-HuBERT visuals for 33.7% WER and uses Qwen3.5 LLM for hierarchical clustering to reach 0.97 F1, beating the baseline by 16.2% WER and 0.15 F1 on the development set.
citing papers explorer
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Cross-Talk Speech Reduction, by Separation, for Separation
Proposes cross-talk reduction task with CTRnet and pseudo-label far-field separation (PuLSS) to train on real close-talk/far-field pairs, achieving SOTA ASR on CHiME-6 and outperforming guided source separation.
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Assessing the Impact of Noise and Speech Enhancement on the Intelligibility of Speech Codecs
Classical codecs prove more robust to noise than neural codecs, speech enhancement significantly helps noise-affected codecs, and listening effort plus ASR-based metrics add useful nuance beyond basic intelligibility scores.
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BUT System Description for CHiME-9 MCoRec Challenge
BUT's CHiME-9 MCoRec system conditions Parakeet-v2 ASR on AV-HuBERT visuals for 33.7% WER and uses Qwen3.5 LLM for hierarchical clustering to reach 0.97 F1, beating the baseline by 16.2% WER and 0.15 F1 on the development set.