Speech dysfluency modeling is the core module for spoken language learning, and speech
therapy. However, there are three challenges. First, current state-of-the-art solutions~~\cite …

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 …

Current de-facto dysfluency modeling methods [1, 2] utilize template matching algorithms
which are not generalizable to out-of-domain real-world dysfluencies across languages, and …

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

Clinical diagnosis of stuttering requires an assessment by a licensed speech-language
pathologist. However, this process is time-consuming and requires clinicians with training …

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 …

Human emotion understanding is pivotal in making conversational technology mainstream.
We view speech emotion understanding as a perception task which is a more realistic …

Smart glasses are emerging as a popular wearable computing platform potentially
revolutionizing the next generation of human-computer interaction. The widespread …

Stuttering is a complex speech disorder that affects people's fluent expression. People who
stutter may exhibit various types of speech disfluencies. Speech-language pathologists …

Anomaly detection in time-series data is crucial for identifying faults, failures, threats, and
outliers across a range of applications. Recently, deep learning techniques have been …