53 citations · 260 across the 63 of their papers we have counts for
12 papers · 1 filter
SQ-Whisper: Speaker-Querying based Whisper Model for Target-Speaker ASR
Pengcheng Guo, Xuankai Chang, Hang Lv +2
Benefiting from massive and diverse data sources, speech foundation models exhibit strong generalization and knowledge transfer capabilities to a wide range of downstream tasks. Ho…
Research on Domain-Specific Chinese Spelling Correction Method Based on Plugin Extension Modules
Xiaowu Zhang, Hongfei Zhao, Xuan Chang
This paper proposes a Chinese spelling correction method based on plugin extension modules, aimed at addressing the limitations of existing models in handling domain-specific texts…
Robust Audiovisual Speech Recognition Models with Mixture-of-Experts
Yihan Wu, Yifan Peng, Yichen Lu +3
Visual signals can enhance audiovisual speech recognition accuracy by providing additional contextual information. Given the complexity of visual signals, an audiovisual speech rec…
SynesLM: A Unified Approach for Audio-visual Speech Recognition and Translation via Language Model and Synthetic Data
Yichen Lu, Jiaqi Song, Xuankai Chang +3
In this work, we present SynesLM, an unified model which can perform three multimodal language understanding tasks: audio-visual automatic speech recognition(AV-ASR) and visual-aid…
The CHiME-8 DASR Challenge for Generalizable and Array Agnostic Distant Automatic Speech Recognition and Diarization
Samuele Cornell, Taejin Park, Steve Huang +6
This paper presents the CHiME-8 DASR challenge which carries on from the previous edition CHiME-7 DASR (C7DASR) and the past CHiME-6 challenge. It focuses on joint multi-channel di…
Towards Robust Speech Representation Learning for Thousands of Languages
William Chen, Wangyou Zhang, Yifan Peng +7
Self-supervised learning (SSL) has helped extend speech technologies to more languages by reducing the need for labeled data. However, models are still far from supporting the worl…
ML-SUPERB 2.0: Benchmarking Multilingual Speech Models Across Modeling Constraints, Languages, and Datasets
Jiatong Shi, Shih-Heng Wang, William Chen +8
ML-SUPERB evaluates self-supervised learning (SSL) models on the tasks of language identification and automatic speech recognition (ASR). This benchmark treats the models as featur…
The Interspeech 2024 Challenge on Speech Processing Using Discrete Units
Xuankai Chang, Jiatong Shi, Jinchuan Tian +7
Representing speech and audio signals in discrete units has become a compelling alternative to traditional high-dimensional feature vectors. Numerous studies have highlighted the e…
A Large-Scale Evaluation of Speech Foundation Models
Shu-wen Yang, Heng-Jui Chang, Zili Huang +18
The foundation model paradigm leverages a shared foundation model to achieve state-of-the-art (SOTA) performance for various tasks, requiring minimal downstream-specific modeling a…
LV-CTC: Non-autoregressive ASR with CTC and latent variable models
Yuya Fujita, Shinji Watanabe, Xuankai Chang +1
Non-autoregressive (NAR) models for automatic speech recognition (ASR) aim to achieve high accuracy and fast inference by simplifying the autoregressive (AR) generation process of…
TMT: Tri-Modal Translation between Speech, Image, and Text by Processing Different Modalities as Different Languages
Minsu Kim, Jee-weon Jung, Hyeongseop Rha +5
The capability to jointly process multi-modal information is becoming an essential task. However, the limited number of paired multi-modal data and the large computational requirem…
OWSM v3.1: Better and Faster Open Whisper-Style Speech Models based on E-Branchformer
Yifan Peng, Jinchuan Tian, William Chen +9
Recent studies have highlighted the importance of fully open foundation models. The Open Whisper-style Speech Model (OWSM) is an initial step towards reproducing OpenAI Whisper usi…