32 citations · 60 across the 13 of their papers we have counts for
13 papers
Serial-Parallel Dual-Path Architecture for Speaking Style Recognition
Guojian Li, Qijie Shao, Zhixian Zhao +3
Speaking Style Recognition (SSR) identifies a speaker's speaking style characteristics from speech. Existing style recognition approaches primarily rely on linguistic information,…
OSUM-EChat: Enhancing End-to-End Empathetic Spoken Chatbot via Understanding-Driven Spoken Dialogue
Xuelong Geng, Qijie Shao, Hongfei Xue +20
Empathy is crucial in enabling natural interactions within spoken dialogue systems, allowing machines to recognize and respond appropriately to paralinguistic cues such as age, gen…
OSUM: Advancing Open Speech Understanding Models with Limited Resources in Academia
Xuelong Geng, Kun Wei, Qijie Shao +18
Large Language Models (LLMs) have made significant progress in various downstream tasks, inspiring the development of Speech Understanding Language Models (SULMs) to enable compreh…
DQ-Data2vec: Decoupling Quantization for Multilingual Speech Recognition
Qijie Shao, Linhao Dong, Kun Wei +2
Data2vec is a self-supervised learning (SSL) approach that employs a teacher-student architecture for contextual representation learning via masked prediction, demonstrating remark…
Ideal-LLM: Integrating Dual Encoders and Language-Adapted LLM for Multilingual Speech-to-Text
Hongfei Xue, Wei Ren, Xuelong Geng +6
Integrating audio encoders with LLMs through connectors has enabled these models to process and comprehend audio modalities, significantly enhancing speech-to-text tasks, including…
HDMoLE: Mixture of LoRA Experts with Hierarchical Routing and Dynamic Thresholds for Fine-Tuning LLM-based ASR Models
Bingshen Mu, Kun Wei, Qijie Shao +2
Recent advancements in integrating Large Language Models (LLM) with automatic speech recognition (ASR) have performed remarkably in general domains. While supervised fine-tuning (S…
Decoupling and Interacting Multi-Task Learning Network for Joint Speech and Accent Recognition
Qijie Shao, Pengcheng Guo, Jinghao Yan +2
Accents, as variations from standard pronunciation, pose significant challenges for speech recognition systems. Although joint automatic speech recognition (ASR) and accent recogni…
SSHR: Leveraging Self-supervised Hierarchical Representations for Multilingual Automatic Speech Recognition
Hongfei Xue, Qijie Shao, Kaixun Huang +3
Multilingual automatic speech recognition (ASR) systems have garnered attention for their potential to extend language coverage globally. While self-supervised learning (SSL) model…
TranUSR: Phoneme-to-word Transcoder Based Unified Speech Representation Learning for Cross-lingual Speech Recognition
Hongfei Xue, Qijie Shao, Peikun Chen +3
UniSpeech has achieved superior performance in cross-lingual automatic speech recognition (ASR) by explicitly aligning latent representations to phoneme units using multi-task self…
Linguistic-Acoustic Similarity Based Accent Shift for Accent Recognition
Qijie Shao, Jinghao Yan, Jian Kang +4
General accent recognition (AR) models tend to directly extract low-level information from spectrums, which always significantly overfit on speakers or channels. Considering accent…
WenetSpeech: A 10000+ Hours Multi-domain Mandarin Corpus for Speech Recognition
Binbin Zhang, Hang Lv, Pengcheng Guo +9
In this paper, we present WenetSpeech, a multi-domain Mandarin corpus consisting of 10000+ hours high-quality labeled speech, 2400+ hours weakly labeled speech, and about 10000 hou…
Auto-KWS 2021 Challenge: Task, Datasets, and Baselines
Jingsong Wang, Yuxuan He, Chunyu Zhao +5
Auto-KWS 2021 challenge calls for automated machine learning (AutoML) solutions to automate the process of applying machine learning to a customized keyword spotting task. Compared…
The NPU System for the 2020 Personalized Voice Trigger Challenge
Jingyong Hou, Li Zhang, Yihui Fu +4
This paper describes the system developed by the NPU team for the 2020 personalized voice trigger challenge. Our submitted system consists of two independently trained subsystems:…