93 citations · 114 across the 37 of their papers we have counts for
11 papers · 1 filter
Structured Speaker-Deficiency Adaptation of Foundation Models for Dysarthric and Elderly Speech Recognition
Shujie Hu, Xurong Xie, Mengzhe Geng +8
Data-intensive fine-tuning of speech foundation models (SFMs) to scarce and diverse dysarthric and elderly speech leads to data bias and poor generalization to unseen speakers. Thi…
A Comparative Study of Discrete Speech Tokens for Semantic-Related Tasks with Large Language Models
Dingdong Wang, Mingyu Cui, Dongchao Yang +2
With the rise of Speech Large Language Models (Speech LLMs), there has been growing interest in discrete speech tokens for their ability to integrate with text-based tokens seamles…
Improving Grapheme-to-Phoneme Conversion through In-Context Knowledge Retrieval with Large Language Models
Dongrui Han, Mingyu Cui, Jiawen Kang +3
Grapheme-to-phoneme (G2P) conversion is a crucial step in Text-to-Speech (TTS) systems, responsible for mapping grapheme to corresponding phonetic representations. However, it face…
Exploring SSL Discrete Tokens for Multilingual ASR
Mingyu Cui, Daxin Tan, Yifan Yang +5
With the advancement of Self-supervised Learning (SSL) in speech-related tasks, there has been growing interest in utilizing discrete tokens generated by SSL for automatic speech r…
Disentangling Speakers in Multi-Talker Speech Recognition with Speaker-Aware CTC
Jiawen Kang, Lingwei Meng, Mingyu Cui +4
Multi-talker speech recognition (MTASR) faces unique challenges in disentangling and transcribing overlapping speech. To address these challenges, this paper investigates the role…
Exploring SSL Discrete Speech Features for Zipformer-based Contextual ASR
Mingyu Cui, Yifan Yang, Jiajun Deng +7
Self-supervised learning (SSL) based discrete speech representations are highly compact and domain adaptable. In this paper, SSL discrete speech features extracted from WavLM model…
Self-supervised ASR Models and Features For Dysarthric and Elderly Speech Recognition
Shujie Hu, Xurong Xie, Mengzhe Geng +8
Self-supervised learning (SSL) based speech foundation models have been applied to a wide range of ASR tasks. However, their application to dysarthric and elderly speech via data-i…
One-pass Multiple Conformer and Foundation Speech Systems Compression and Quantization Using An All-in-one Neural Model
Zhaoqing Li, Haoning Xu, Tianzi Wang +7
We propose a novel one-pass multiple ASR systems joint compression and quantization approach using an all-in-one neural model. A single compression cycle allows multiple nested sys…
GigaSpeech 2: An Evolving, Large-Scale and Multi-domain ASR Corpus for Low-Resource Languages with Automated Crawling, Transcription and Refinement
Yifan Yang, Zheshu Song, Jianheng Zhuo +13
The evolution of speech technology has been spurred by the rapid increase in dataset sizes. Traditional speech models generally depend on a large amount of labeled training data, w…
Towards Effective and Efficient Non-autoregressive Decoding Using Block-based Attention Mask
Tianzi Wang, Xurong Xie, Zhaoqing Li +9
This paper proposes a novel non-autoregressive (NAR) block-based Attention Mask Decoder (AMD) that flexibly balances performance-efficiency trade-offs for Conformer ASR systems. AM…
Cross-Speaker Encoding Network for Multi-Talker Speech Recognition
Jiawen Kang, Lingwei Meng, Mingyu Cui +4
End-to-end multi-talker speech recognition has garnered great interest as an effective approach to directly transcribe overlapped speech from multiple speakers. Current methods typ…