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eess.AS2024
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…
eess.AS2024
Stutter-Solver: End-to-end Multi-lingual Dysfluency Detection
Xuanru Zhou, Cheol Jun Cho, Ayati Sharma +9
Current de-facto dysfluency modeling methods utilize template matching algorithms which are not generalizable to out-of-domain real-world dysfluencies across languages, and are not…
eess.AS2024
YOLO-Stutter: End-to-end Region-Wise Speech Dysfluency Detection
Xuanru Zhou, Anshul Kashyap, Steve Li +9
Dysfluent speech detection is the bottleneck for disordered speech analysis and spoken language learning. Current state-of-the-art models are governed by rule-based systems which l…