4 papers
LCS-CTC: Leveraging Soft Alignments to Enhance Phonetic Transcription Robustness
Zongli Ye, Jiachen Lian, Akshaj Gupta +18
Phonetic speech transcription is crucial for fine-grained linguistic analysis and downstream speech applications. While Connectionist Temporal Classification (CTC) is a widely used…
Seamless Dysfluent Speech Text Alignment for Disordered Speech Analysis
Zongli Ye, Jiachen Lian, Xuanru Zhou +14
Accurate alignment of dysfluent speech with intended text is crucial for automating the diagnosis of neurodegenerative speech disorders. Traditional methods often fail to model pho…
Dysfluent WFST: A Framework for Zero-Shot Speech Dysfluency Transcription and Detection
Chenxu Guo, Jiachen Lian, Xuanru Zhou +13
Automatic detection of speech dysfluency aids speech-language pathologists in efficient transcription of disordered speech, enhancing diagnostics and treatment planning. Traditiona…
Time and Tokens: Benchmarking End-to-End Speech Dysfluency Detection
Xuanru Zhou, Jiachen Lian, Cheol Jun Cho +10
Speech dysfluency modeling is a task to detect dysfluencies in speech, such as repetition, block, insertion, replacement, and deletion. Most recent advancements treat this problem…