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20212026
most citedPersonalized Adversarial Data Augmentation for Dysarthric and Elderly Speech Recognition

38 citations · 88 across the 46 of their papers we have counts for

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11 papers · 1 filter

eess.AS2024

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…

eess.AS2024

k2SSL: A Faster and Better Framework for Self-Supervised Speech Representation Learning

Yifan Yang, Jianheng Zhuo, Zengrui Jin +9

Self-supervised learning (SSL) has achieved great success in speech-related tasks. While Transformer and Conformer architectures have dominated SSL backbones, encoders like Zipform…

eess.AS2024

CR-CTC: Consistency regularization on CTC for improved speech recognition

Zengwei Yao, Wei Kang, Xiaoyu Yang +7

Connectionist Temporal Classification (CTC) is a widely used method for automatic speech recognition (ASR), renowned for its simplicity and computational efficiency. However, it of…

cs.SD2024

LibriheavyMix: A 20,000-Hour Dataset for Single-Channel Reverberant Multi-Talker Speech Separation, ASR and Speaker Diarization

Zengrui Jin, Yifan Yang, Mohan Shi +10

The evolving speech processing landscape is increasingly focused on complex scenarios like meetings or cocktail parties with multiple simultaneous speakers and far-field conditions…

eess.AS2024

Advancing Multi-talker ASR Performance with Large Language Models

Mohan Shi, Zengrui Jin, Yaoxun Xu +6

Recognizing overlapping speech from multiple speakers in conversational scenarios is one of the most challenging problem for automatic speech recognition (ASR). Serialized output t…

cs.SD2024

Empowering Whisper as a Joint Multi-Talker and Target-Talker Speech Recognition System

Lingwei Meng, Jiawen Kang, Yuejiao Wang +4

Multi-talker speech recognition and target-talker speech recognition, both involve transcription in multi-talker contexts, remain significant challenges. However, existing methods…

cs.SD2024

Homogeneous Speaker Features for On-the-Fly Dysarthric and Elderly Speaker Adaptation

Mengzhe Geng, Xurong Xie, Jiajun Deng +7

The application of data-intensive automatic speech recognition (ASR) technologies to dysarthric and elderly adult speech is confronted by their mismatch against healthy and nonaged…

eess.AS2024

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…

cs.SD2024

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…

cs.SD2024

Joint Speaker Features Learning for Audio-visual Multichannel Speech Separation and Recognition

Guinan Li, Jiajun Deng, Youjun Chen +8

This paper proposes joint speaker feature learning methods for zero-shot adaptation of audio-visual multichannel speech separation and recognition systems. xVector and ECAPA-TDNN s…

cs.SD2024★ 1 cited

Enhancing Pre-trained ASR System Fine-tuning for Dysarthric Speech Recognition using Adversarial Data Augmentation

Huimeng Wang, Zengrui Jin, Mengzhe Geng +5

Automatic recognition of dysarthric speech remains a highly challenging task to date. Neuro-motor conditions and co-occurring physical disabilities create difficulty in large-scale…