Generative adversarial networks in EEG analysis: an overview

AG Habashi, AM Azab, S Eldawlatly, GM Aly - … of NeuroEngineering and …, 2023 - Springer
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 for speech processing: A review

A Wali, Z Alamgir, S Karim, A Fawaz, MB Ali… - Computer Speech & …, 2022 - Elsevier
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 …

Epilepsygan: Synthetic epileptic brain activities with privacy preservation

D Pascual, A Amirshahi, A Aminifar… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
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 …

WESPER: Zero-shot and realtime whisper to normal voice conversion for whisper-based speech interactions

J Rekimoto - Proceedings of the 2023 CHI Conference on Human …, 2023 - dl.acm.org
Recognizing whispered speech and converting it to normal speech creates many
possibilities for speech interaction. Because the sound pressure of whispered speech is …

Towards generalized speech enhancement with generative adversarial networks

S Pascual, J Serrà, A Bonafonte - arxiv preprint arxiv:1904.03418, 2019 - arxiv.org
The speech enhancement task usually consists of removing additive noise or reverberation
that partially mask spoken utterances, affecting their intelligibility. However, little attention is …

DualVoice: Speech Interaction That Discriminates between Normal and Whispered Voice Input

J Rekimoto - Proceedings of the 35th Annual ACM Symposium on …, 2022 - dl.acm.org
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 …

Glottal flow synthesis for whisper-to-speech conversion

O Perrotin, IV McLoughlin - IEEE/ACM Transactions on Audio …, 2020 - ieeexplore.ieee.org
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 …

Pareto-Optimized Non-Negative Matrix Factorization Approach to the Cleaning of Alaryngeal Speech Signals

R Maskeliūnas, R Damaševičius, A Kulikajevas… - Cancers, 2023 - mdpi.com
Simple Summary This paper introduces a new method for cleaning impaired speech by
combining Pareto-optimized deep learning with Non-negative Matrix Factorization (NMF) …

Generative models for improved naturalness, intelligibility, and voicing of whispered speech

D Wagner, SP Bayerl, HAC Maruri… - 2022 IEEE Spoken …, 2023 - ieeexplore.ieee.org
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 …

Generative adversarial networks for whispered to voiced speech conversion: a comparative study

D Wagner, I Baumann, T Bocklet - International Journal of Speech …, 2024 - Springer
Abstract Generative Adversarial Networks (GANs) have demonstrated promising results as
end-to-end models for whispered to voiced speech conversion. Leveraging non …