Electroencephalogram (EEG) signals have been utilized in a variety of medical as well as
engineering applications. However, one of the challenges associated with recording EEG …

Generative adversarial networks (GANs) have seen remarkable progress in recent years.
They are used as generative models for all kinds of data such as text, images, audio, music …

Recognizing whispered speech and converting it to normal speech creates many
possibilities for speech interaction. Because the sound pressure of whispered speech is …

Epilepsy is a chronic neurological disorder affecting more than 65 million people worldwide
and manifested by recurrent unprovoked seizures. The unpredictability of seizures not only …

The speech enhancement task usually consists of removing additive noise or reverberation
that partially mask spoken utterances, affecting their intelligibility. However, little attention is …

This work adapts two recent architectures of generative models and evaluates their
effectiveness for the conversion of whispered speech to normal speech. We incorporate the …

Simple Summary This paper introduces a new method for cleaning impaired speech by
combining Pareto-optimized deep learning with Non-negative Matrix Factorization (NMF) …

Whisper-to-speech conversion is motivated by laryngeal disorders, in which malfunction of
the vocal folds leads to loss of voicing. Many patients with laryngeal disorders can still …

Introduction The Autonomous Sensory Meridian Response (ASMR) is a combination of
sensory phenomena involving electrostatic-like tingling sensations, which emerge in …

Interactions based on automatic speech recognition (ASR) have become widely used, with
speech input being increasingly utilized to create documents. However, as there is no easy …