Automatic Parkinson's disease detection based on the combination of long-term acoustic features and Mel frequency cepstral coefficients (MFCC)

S Hawi, J Alhozami, R AlQahtani, D AlSafran… - … Signal Processing and …, 2022 - Elsevier
In recent years, acoustic signals have found increasing popularity among the scientific
community as biomarkers for detecting Parkinson's disease. Literature highlights that 90% of …

A New Method for Heart Disease Detection: Long Short-Term Feature Extraction from Heart Sound Data

M Guven, F Uysal - Sensors, 2023 - mdpi.com
Heart sounds have been extensively studied for heart disease diagnosis for several
decades. Traditional machine learning algorithms applied in the literature have typically …

Voice-quality Features for Deep Neural Network Based Speaker Verification Systems

A Woubie, L Koivisto… - 2021 29th European Signal …, 2021 - ieeexplore.ieee.org
Jitter and shimmer are voice-quality features which have been successfully used to detect
voice pathologies and classify different speaking styles. In this paper, we investigate the …

[HTML][HTML] Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network

G Korvel, P Treigys, B Kostek - The Journal of the Acoustical Society of …, 2021 - pubs.aip.org
The goal of this research is to find a way of highlighting the acoustic differences between
consonant phonemes of the Polish and Lithuanian languages. For this purpose, similarity …

Unsupervised quasi-silence based speech segmentation for speaker diarization

AK Bhuyan, H Dutta, S Biswas - 2022 IEEE 9th International …, 2022 - ieeexplore.ieee.org
This paper presents a computationally efficient and accurate speech segmentation
framework suitable for speaker diarization. The proposed approach solves the problem of …

Heart diseases diagnose via mobile application

M Güven, F Hardalaç, K Özışık, F Tuna - Applied Sciences, 2021 - mdpi.com
Featured Application The design and verification result of a mobile application that can
detect heart abnormalities is presented within the scope of this work. Abstract One of the …

Unsupervised Speaker Diarization in Distributed IoT Networks Using Federated Learning

AK Bhuyan, H Dutta, S Biswas - arXiv preprint arXiv:2404.10842, 2024 - arxiv.org
This paper presents a computationally efficient and distributed speaker diarization
framework for networked IoT-style audio devices. The work proposes a Federated Learning …

Investigation of spoken-language detection and classification in broadcasted audio content

R Kotsakis, M Matsiola, G Kalliris, C Dimoulas - Information, 2020 - mdpi.com
The current paper focuses on the investigation of spoken-language classification in audio
broadcasting content. The approach reflects a real-word scenario, encountered in modern …

Prediction of Gender and Emotion Using Acoustic Features

S Sathyavathi, H Deksha, A Krishnan… - … on Advancements in …, 2023 - ieeexplore.ieee.org
Detecting gender and emotion from voice data is a challenging issue in machine learning.
This paper presents a novel approach for detecting gender and emotion from voice data …

Automatic speech recognition for Ukrainian broadcast media transcribing

MM Sazhok, RA Seliukh, DY Fedoryn… - Control systems & …, 2019 - dspace.nbuv.gov.ua
AUTOMATIC SPEECH RECOGNITION FOR UKRAINIAN BROADCAST MEDIA
TRANSCRIBING Page 1 46 ISSN 2706-8145, Системи керування та комп’ютери, 2019, № 6 …