Accurately predicting carbon trading prices using deep learning models can help
enterprises understand the operational mechanisms and regulations of the carbon market …

A robust and language agnostic Voice Activity Detection (VAD) is crucial for Digital
Entertainment Content (DEC). Primary examples of DEC include movies and TV series …

The rapid progress of multimodal signal processing in recent years has cleared the way for
novel applications in human-computer interaction, surveillance, and telecommunication …

Speech activity detection (SAD) is an essential component of automatic speech recognition
systems impacting the overall system performance. This paper investigates an optimization …

Voice activity detection is an essential pre-processing component for speech-related tasks
such as automatic speech recognition (ASR). Traditional supervised VAD systems obtain …

With the hyperconnectivity and ubiquity of the Internet, the fake news problem now presents
a greater threat than ever before. One promising solution for countering this threat is to …

Code-switching (CS) is a multilingual phenomenon where a speaker uses different
languages in an utterance or between alternating utterances. Developing large-scale …

Self-supervised learning approaches have lately achieved great success on a broad
spectrum of machine learning problems. In the field of speech processing, one of the most …

In the subject of pattern recognition, speech recognition is an important study topic. The
authors give a detailed assessment of voice recognition strategies for several majority …

Traditional supervised voice activity detection (VAD) methods work well in clean and
controlled scenarios, with performance severely degrading in real-world applications. One …