Improving the user's hearing ability to understand speech in noisy environments is critical to
the development of hearing aid (HA) devices. For this, it is important to derive a metric that …

Recently, deep learning (DL)-based non-intrusive speech assessment models have
attracted great attention. Many studies report that these DL-based models yield satisfactory …

In recent years, separating effective target signals from mixed signals has become a hot and
challenging topic in signal research. The SI-BSS (Blind source separation (BSS) based on …

In terms of subjective evaluations, speech quality has been generally described by a mean
opinion score (MOS). In recent years, non-intrusive speech quality assessment shows an …

Speech quality is one of the main foci of speech-related research, where it is frequently
studied with speech intelligibility, another essential measurement. Band-level perceptual …

Acoustic Signals such as speech and sound are easily degraded by interferences present in
our surroundings. The present work explores the usage of the Pixel CNN architecture for the …

Speech quality is best evaluated by human feedback using mean opinion scores (MOS).
However, variance in ratings between listeners can introduce noise in the true quality label …

Noise suppression (NS) algorithms are effective in improving speech quality in many cases.
However, aggressive noise suppression can damage the target speech, reducing both …

The basic features extracted by traditional methods for speech quality evaluation are not
clear, which leads to the small correlation coefficient of subjective and objective evaluation …

This paper explores entropy-controlled dithering techniques in audio compression,
examining the application of standard and modified TPDFs, combined with noise shaping …