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KSoF: The Kassel State of Fluency Dataset – A Therapy Centered Dataset of Stuttering
To be able to monitor speech behavior over a long time, the ability to detect stuttering events and modifications in speech could help PWSs and speech pathologists to track the level of fluency.
Classifying Dementia in the Presence of Depression: A Cross-Corpus Study
Automated dementia screening enables early detection and intervention, reducing costs to healthcare systems and increasing quality of life for those affected.
A Stutter Seldom Comes Alone -- Cross-Corpus Stuttering Detection as a Multi-label Problem
Most stuttering detection and classification research has viewed stuttering as a multi-class classification problem or a binary detection task for each dysfluency type; however, this does not match the nature of stuttering, in which one dysfluency seldom comes alone but rather co-occurs with others.
Dysfluencies Seldom Come Alone -- Detection as a Multi-Label Problem
This work explores an approach based on a modified wav2vec 2. 0 system for end-to-end stuttering detection and classification as a multi-label problem.
KSoF: The Kassel State of Fluency Dataset -- A Therapy Centered Dataset of Stuttering
To be able to monitor speech behavior over a long time, the ability to detect stuttering events and modifications in speech could help PWSs and speech pathologists to track the level of fluency.
Towards Automated Assessment of Stuttering and Stuttering Therapy
This paper introduces the Speech Control Index (SCI), a new method to evaluate the severity of stuttering.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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