5 accepted papers
The INTERSPEECH 2025 Challenge on Multilingual Conversational Speech Language Models (MLC-SLM) promotes multilingual conversational ASR with large language models (LLMs). Our previous SHNU-mASR system adopted a competitive parallel-speech-encoder architecture that integrated Whisper and mHuBERT with…
How to effectively use limited supervised accent data to improve the accented ASR is of paramount importance. In this work, we propose an accent-specific quantization for joint unsupervised and supervised training (AQ-JUST) of end-to-end ASR models to address this issue. Specifically, two variants o…
Multi-accent speech recognition is a key challenge in current speech recognition due to the pronunciation variations of different accents. In this study, we propose a Cross-modal Parallel Training (CPT) approach for improving the accent robustness of state-of-the-art Conformer-Transducer (Conformer-…
This paper proposes a new scoring calibration method named "Consistency-Aware Score Calibration", which introduces a Consistency Measure Factor (CMF) to measure the stability of audio voiceprints in similarity scores for speaker verification. The CMF is inspired by the limitations in segment scoring…
In this paper, we propose a new continual learning framework for few-shot bioacoustic event detection (BED). First, we modify the recently proposed dynamic few-shot learning (DFSL) and generalize it to the BED task. Then, we introduce a weight alignment loss to enhance the weight generator of modifi…