A novel adaptive artifacts wavelet Denoising for EEG artifacts removal using deep learning with Meta-heuristic approach

A Narmada, MK Shukla - Multimedia Tools and Applications, 2023 - Springer
Electroencephalogram (EEG) is said to be a common tool to control neurological disorders,
performed medical diagnoses, and cognitive research. But, EEG is generally polluted …

The effectiveness of time stretching for enhancing dysarthric speech for improved dysarthric speech recognition

L Prananta, BM Halpern, S Feng… - arXiv preprint arXiv …, 2022 - arxiv.org
In this paper, we investigate several existing and a new state-of-the-art generative
adversarial network-based (GAN) voice conversion method for enhancing dysarthric speech …

Machine Learning Approaches for Whisper to Normal Speech Conversion: A Survey

MA Oliveira - U. Porto Journal of Engineering, 2022 - ijooes.fe.up.pt
Whispered speech is a mode of speech that differs from normal speech due to the absence
of a periodic component, namely the Fundamental Frequency that characterizes the pitch …

A novel attention-guided generative adversarial network for whisper-to-normal speech conversion

T Gao, Q Pan, J Zhou, H Wang, L Tao, HK Kwan - Cognitive Computation, 2023 - Springer
Whispered speech is a special voicing style of speech that is employed publicly to protect
speech information. It is also the primary pronunciation form for aphonic individuals with …

Intelligibility improvement of dysarthric speech using mmse discogan

M Purohit, M Patel, H Malaviya, A Patil… - 2020 International …, 2020 - ieeexplore.ieee.org
Dysarthria is a manifestation of the disordering in articulatory parts that are used during
speech production, which results in uneven, slow, slurred, monotone speech or speech in …

[图书][B] Machine learning and deep learning in natural language processing

AS Pillai, R Tedesco - 2023 - books.google.com
Natural Language Processing (NLP) is a sub-field of Artificial Intelligence, linguistics, and
computer science and is concerned with the generation, recognition, and understanding of …

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 …

Novel adaptive generative adversarial network for voice conversion

M Patel, M Parmar, S Doshi, NJ Shah… - 2019 Asia-Pacific …, 2019 - ieeexplore.ieee.org
Voice Conversion (VC) converts the speaking style of a source speaker to the speaking style
of a target speaker by preserving the linguistic content of a given speech utterance …

CinC-GAN for Effective F0 prediction for Whisper-to-Normal Speech Conversion

M Patel, M Purohit, J Shah… - 2020 28th European Signal …, 2021 - ieeexplore.ieee.org
Recently, Generative Adversarial Networks (GAN) based methods have shown remarkable
performance for the Voice Conversion and WHiSPer-to-normal SPeeCH (WHSP2SPCH) …

Attention-guided generative adversarial network for whisper to normal speech conversion

T Gao, J Zhou, H Wang, L Tao, HK Kwan - arXiv preprint arXiv:2111.01342, 2021 - arxiv.org
Whispered speech is a special way of pronunciation without using vocal cord vibration. A
whispered speech does not contain a fundamental frequency, and its energy is about 20dB …