Speech is critical for interpersonal communication, but not everyone has fluent
communication skills. Speech disfluency, including stuttering and interruptions, affects not …

Speech disfluency research is pivotal to accommodating atypical speakers in mainstream
conversational technology. However, the lack of publicly available labeled and unlabeled …

Spider dragline silk is known for its exceptional strength and toughness; hence
understanding the link between its primary sequence and mechanics is crucial. Here, we …

Stuttering is a prevalent speech disorder affecting millions worldwide. To provide an
automatic and objective stuttering assessment tool, Stuttering Event Detection (SED) is …

In recent years, advancements in the field of speech processing have led to cutting-edge
deep learning algorithms with immense potential for real-world applications. The automated …

Specially adapted speech recognition models are necessary to handle stuttered speech. For
these to be used in a targeted manner, stuttered speech must be reliably detected. Recent …

Monitoring and recognizing patterns in continuous sensing data is crucial for many practical
applications. These real-world time-series data are often nonstationary, characterized by …

Most existing speech disfluency detection techniques only rely upon acoustic data. In this
work, we present a practical multimodal disfluency detection approach that leverages …

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 …

The automated classification of stuttered speech has significant implications for timely
assessments providing assistance to speech language pathologists. Despite notable …