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Qwen-ASR-1.7B adapted for multilingual two-speaker speech recognition · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a system for the MLC-SLM 2026 Challenge that adapts the Qwen3-ASR-1.7B model for multilingual, two-speaker conversational speech. The system integrates a speaker diarization front end with the adapted ASR model, processing voice activity, speaker embeddings, and audio segmentation. Adaptation techniques include supervised fine-tuning, LoRA fine-tuning with synthetic speech, and GRPO reinforcement learning, which collectively reduced the word error rate by 6.83 points on the development set and achieved 17.97 tcpMER on the evaluation set. AI

IMPACT Improves accuracy for multilingual conversational AI systems handling multiple speakers.

RANK_REASON The cluster contains an academic paper detailing a new system and adaptation techniques for speech recognition.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Qwen-ASR-1.7B adapted for multilingual two-speaker speech recognition · 2 sources tracked

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The cluster contains an academic paper detailing a new system and adaptation techniques for speech recognition.
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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Hao Wu, RongQi Han, Zhen Wang, Wei Liang, Wei Xu ·

    Diarization-Guided Qwen-ASR Adaptation for Multilingual Two-Speaker Conversational Speech

    arXiv:2607.08208v1 Announce Type: new Abstract: This paper describes our self-designed system for Task 1 of the MLC-SLM 2026 Challenge for multilingual two-speaker conversational speech. The system combines a modular speaker diarization front end with a challenge-adapted Qwen3-AS…

  2. arXiv cs.CL TIER_1 English(EN) · Wei Xu ·

    Diarization-Guided Qwen-ASR Adaptation for Multilingual Two-Speaker Conversational Speech

    This paper describes our self-designed system for Task 1 of the MLC-SLM 2026 Challenge for multilingual two-speaker conversational speech. The system combines a modular speaker diarization front end with a challenge-adapted Qwen3-ASR-1.7B recognizer. The diarization front end per…

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