5 citations · 7 across the 9 of their papers we have counts for
10 papers
Navigating Speech Enhancement for Real-Time MRI: A Systematic Assessment of Signal Quality, Source Preservation, and Downstream Tasks
Huang-Cheng Chou, Sean Foley, Haley Hsu +10
Audio recorded during real-time magnetic resonance imaging (rtMRI) is heavily contaminated by scanner noise, but it remains unclear whether general-purpose speech enhancement impro…
Advancing automatic speech recognition using feature fusion with self-supervised learning features: A case study on Fearless Steps Apollo corpus
Szu-Jui Chen, John H. L. Hansen
Using self-supervised learning (SSL) models has significantly improved performance for downstream speech tasks, surpassing the capabilities of traditional hand-crafted features. Th…
Emotion-Aware Prefix: Towards Explicit Emotion Control in Voice Conversion Models
Haoyuan Yang, Mu Yang, Jiamin Xie +2
Recent advances in zero-shot voice conversion have exhibited potential in emotion control, yet the performance is suboptimal or inconsistent due to their limited expressive capacit…
Bridging the Modality Gap: Softly Discretizing Audio Representation for LLM-based Automatic Speech Recognition
Mu Yang, Szu-Jui Chen, Jiamin Xie +1
One challenge of integrating speech input with large language models (LLMs) stems from the discrepancy between the continuous nature of audio data and the discrete token-based para…
Acoustic modeling for Overlapping Speech Recognition: JHU Chime-5 Challenge System
Vimal Manohar, Szu-Jui Chen, Zhiqi Wang +3
This paper summarizes our acoustic modeling efforts in the Johns Hopkins University speech recognition system for the CHiME-5 challenge to recognize highly-overlapped dinner party…
Language Agnostic Data-Driven Inverse Text Normalization
Szu-Jui Chen, Debjyoti Paul, Yutong Pang +2
With the emergence of automatic speech recognition (ASR) models, converting the spoken form text (from ASR) to the written form is in urgent need. This inverse text normalization (…
FeaRLESS: Feature Refinement Loss for Ensembling Self-Supervised Learning Features in Robust End-to-end Speech Recognition
Szu-Jui Chen, Jiamin Xie, John H. L. Hansen
Self-supervised learning representations (SSLR) have resulted in robust features for downstream tasks in many fields. Recently, several SSLRs have shown promising results on automa…
Scenario Aware Speech Recognition: Advancements for Apollo Fearless Steps & CHiME-4 Corpora
Szu-Jui Chen, Wei Xia, John H. L. Hansen
In this study, we propose to investigate triplet loss for the purpose of an alternative feature representation for ASR. We consider a general non-semantic speech representation, wh…
Building state-of-the-art distant speech recognition using the CHiME-4 challenge with a setup of speech enhancement baseline
Szu-Jui Chen, Aswin Shanmugam Subramanian, Hainan Xu +1
This paper describes a new baseline system for automatic speech recognition (ASR) in the CHiME-4 challenge to promote the development of noisy ASR in speech processing communities…
Student-Teacher Learning for BLSTM Mask-based Speech Enhancement
Aswin Shanmugam Subramanian, Szu-Jui Chen, Shinji Watanabe
Spectral mask estimation using bidirectional long short-term memory (BLSTM) neural networks has been widely used in various speech enhancement applications, and it has achieved gre…