Oct 9, 2026J/K move · Enter open · S save
Yushi Wang, Zeyan Song, Xiaobin Rong, Chengwei Liu+2
Key Laboratory of Modern Acoustics, Nanjing University, Nanjing, China · NJU-Horizon Intelligent Audio Lab, Horizon Robotics, Beijing, China · Qwen Business Unit of Alibaba, Hangzhou, China
This paper describes our systems for the Track 1 time-stamped speaker-attributed ASR task of the SmartGlasses Challenge. To handle overlapping speech, background noise and far-field conditions in two-person conversations, we employ SoulX-Transcriber, a multimodal large language model that takes full-length audio as input and generates structured transcriptions. In addition, we investigate the effect of speech frontend processing, including a rule-based Guided Source Separation method and a data-driven speech separation model, both of which improve performance on the validation set. Considering inference stability, our final submission uses the fine-tuned SoulX-Transcriber system, achieving a tcpCER of 6.22 on the test set.