Transsion的说话人归属多语言ASR系统，用于MLC-SLM 2026挑战赛

# Transsion's Speaker-Attributed Multilingual ASR System for the MLC-SLM 2026 Challenge
Source: [https://arxiv.org/abs/2609.20833](https://arxiv.org/abs/2609.20833)
[View PDF](https://arxiv.org/pdf/2609.20833)

> Abstract:This paper presents the Transsion Speech Team submission to Task 1 of the MLC\-SLM 2026 Challenge, which focuses on speaker\-attributed transcription for multilingual conversational speech\. We propose a cascaded framework consisting of three components: a speaker diarization module, a long\-form multilingual ASR module, and a speaker\-transcription fusion module\. The diarization module is built upon DiariZen and produces speaker\-homogeneous segments through local speaker activity estimation and global speaker clustering\. The ASR module is based on Qwen3\-Omni and generates multilingual transcriptions, while an external CTC\-based alignment model provides precise word\- and character\-level timestamps\. Finally, the fusion module combines diarization outputs with timestamped transcriptions to generate speaker\-attributed STM outputs\. Experimental results on the official evaluation set demonstrate the effectiveness of the proposed framework\. The submitted system achieves a tcpMER of 15\.41% and ranks second among all participating teams\.

## Submission history

From: Xiaoxiao Li \[[view email](https://arxiv.org/show-email/0272dffc/2609.20833)\] **\[v1\]**Fri, 24 Jul 2026 09:42:54 UTC \(1,072 KB\)