Excited to co-organize this special session at IEEE CASE 2026 with professor Bob Ziyue LI. We welcome submissions on LLMs and foundation models for spatiotemporal data, including representation ...

In a dual-center cross-sectional study (N = 202), Center 1 (Capital Center for Children’s Health, Capital Medical University, n = 161) served as the development cohort and Center 2 (College of ...

HTK is a respected toolkit used mainly by the speech community to perform research in speech recognition. Although quite old, many newer systems emulate the same feature extraction pipeline as used in ...

Despite advancements in technology such as applications like Shazam that can identify music within seconds, the trend mainly applies to well-known instruments. Cultural instruments are virtually ...

Speech is one of the most efficient methods of communication among humans, inspiring advancements in machine speech processing under Natural Language Processing (NLP). This field aims to enable ...

While speech biomarkers of disease have attracted increased interest in recent years, a challenge is that features derived from signal processing or machine learning approaches may lack clinical ...

Natural Language Processing (NLP) is a group of theoretically inspired computer structures for analyzing and modeling clearly going on texts at one or extra degrees of linguistic evaluation to acquire ...

Audio files contain various spectral features that are essential for audio data learning. The article provides an overview of important spectral features like MFCCs, spectral centroid, and ...

feature_extraction_functions.py: a set of feature extraction functions from RDShi-SpeakerCount. MFCC: Mel-frequency cepstral coefficients calculation. MFCC.py ...