With the recent research developments, deep learning models are powerful alternatives for
speech enhancement and recognition in many real-world applications. Although state-of-the …

In this study, a compact smart-sensor tag is developed for estimating pork freshness. The
smart sensor tag can be placed in areas where packaged meat is stored or displayed …

Temporal modulation processing is a promising technique for improving the intelligibility and
quality of speech in noise. We propose a speech enhancement algorithm that constructs the …

Current augmented Kalman filter (AKF)-based speech enhancement algorithms utilise a
temporal convolutional network (TCN) to estimate the clean speech and noise linear …

The performance of speech coding, speech recognition, and speech enhancement systems
that rely on the augmented Kalman filter (AKF) largely depend upon the accuracy of clean …

Although cochlear implants work well for people with hearing impairment in quiet conditions,
it is well-known that they are not as effective in noisy environments. Noise reduction …

This paper presents a novel self-adaptive approach for speech enhancement in the context
of highly nonstationary noise. A two-stage deep neuroevolutionary technique for speech …

Machine learning, a part of artificial intelligence, is recently used in speech enhancement
algorithms (SE). The primary focus of SE is finding the original speech signal from the …

Speech recognition is a common task in various everyday user systems; however, its
effectiveness is limited in noisy environments such as moving vehicles, homes with ambient …

Minimum mean-square error (MMSE) approaches have been shown to achieve state-of-the-
art performance on the task of speech enhancement. However, MMSE approaches lack the …