Results 61 to 70 of about 10,198 (208)

Multi-Accent Speaker Detection Using Normalize Feature MFCC Neural Network Method

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2023
Speaker recognition is a field of research that continues to this day. Various methods have been developed to detect the human voice with greater precision and accuracy. Research on human speech recognition that is quite challenging is accent recognition.
Kristiawan Nugroho, Edy Winarno, Eri Zuliarso, Sunardi   +3 more
doaj   +1 more source

Machine Learning for Autism Spectrum Disorder Prediction: A Review of Data Augmentation and Feature Selection Techniques

Health Care Science, Volume 5, Issue 5, Page 514-531, October 2026.
Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by persistent difficulties in social communication, social interaction, and repetitive behaviors. Early diagnosis is often hindered by subjective clinical assessments and limited data availability.
Sahar Alkhaibari, Feng Dong
wiley   +1 more source

Soft Active Electromyography Interface for Machine Learning‐Enabled Silent Speech Recognition

Advanced Intelligent Systems, Volume 8, Issue 9, September 2026.
A soft, hand‐worn electromyography interface enables intent‐driven silent speech recognition without continuous facial attachment. The device integrates liquid‐metal interconnects, a transparent flexible circuit, and elastomer encapsulation with a fingertip electrode that contacts perioral muscles only on demand.
Yuta Kurotaki, Shusuke Yamakoshi, Reitaro Yoshida, Yutaka Isoda, Tamami Takano, Yuji Isano, Yusuke Miyake, Kentaro Kuribayashi, Hiroki Ota   +8 more
wiley   +1 more source

Modifikasi Metode MFCC untuk Identifikasi Pembicara di Lingkungan Ber-Noise [PDF]

, 2019
Beberapa metode ekstraksi fitur untuk sistem identifikasi pembicara memiliki kelemahan yaitu ketika dilingkungan berderau hasil akurasinya menurun. Metode ekstraksi fitur Mel-Frequency Cepstral Coefficient (MFCC) merupakan metode ekstraksi sinyal suara ...
Prayogi, Yanuar Risah, Prayogi, Y. R. (Yanuar)   +1 more
core   +1 more source

Performance Analysis of Feature Mel Frequency Cepstral Coefficient and Short Time Fourier Transform Input for Lie Detection using Convolutional Neural Network

JOIV: International Journal on Informatics Visualization
This study aims to determine which model is more effective in detecting lies between models with Mel Frequency Cepstral Coefficient (MFCC) and Short Time Fourier Transform (STFT) processes using Convolutional Neural Network (CNN). MFCC and STFT processes
Dewi Kusumawati, Amil Ahmad Ilham, Andani Achmad, Ingrid Nurtanio   +3 more
doaj   +1 more source

CNN AND LSTM FOR THE CLASSIFICATION OF PARKINSON'S DISEASE BASED ON THE GTCC AND MFCC

Applied Computer Science, 2023
Parkinson's disease is a recognizable clinical syndrome with a variety of causes and clinical presentations; it represents a rapidly growing neurodegenerative disorder.
Nouhaila BOUALOULOU , Taoufiq BELHOUSSINE DRISSI, Benayad NSIRI   +2 more
doaj   +1 more source

Multi‐Modal AI Approach in Depression Detection and Treatment: A Systematic Review of Last Decade

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 3, September 2026.
Overview of multimodal approaches for depression detection and treatment. ABSTRACT Depression is a common and devastating mental health illness with serious personal and societal consequences. Despite advancing treatment techniques, there are still hurdles in the effective diagnosis and treatment of depression, such as prompt diagnosis, personalized ...
Smith K. Khare, Esmaeil S. Nadimi, U. Rajendra Acharya, Victoria Blanes‐Vidal   +3 more
wiley   +1 more source

Extraction of Novel Features Based on Histograms of MFCCs Used in Emotion Classification from Generated Original Speech Dataset

Elektronika ir Elektrotechnika, 2020
This paper introduces two significant contributions: one is a new feature based on histograms of MFCC (Mel-Frequency Cepstral Coefficients) extracted from the audio files that can be used in emotion classification from speech signals, and the other – our
Muhammet Pakyurek, Mahir Atmis, Selman Kulac, Umut Uludag   +3 more
doaj   +1 more source

A Systematic Review of Data Science in Early Voice‐Based Detection of Parkinson's and Amyotrophic Lateral Sclerosis Neurodegenerative Diseases

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 3, September 2026.
Seven‐stage AI‐powered voice biomarker pipeline for neurodegenerative disease diagnosis and clinical decision support. ABSTRACT Recent studies have shown that voice analysis provides a feasible, non‐invasive diagnostic alternative for the early detection of neurodegenerative diseases (NDs), such as Parkinson's disease (PD) and Amyotrophic Lateral ...
Abdulazeez Mousa, Fatih Özyurt, Ridwan Boya Marqas Shamoun, Laszlo Barna Iantovics   +3 more
wiley   +1 more source

Diversity of Botryosphaeriaceae Species Associated With Grapevine Dieback in France: Life Traits and Aggressiveness

Plant Pathology, Volume 75, Issue 5, September‐October 2026.
This study provides a molecular and biological characterisation of Botryosphaeriaceae species found in French vineyards. It is the first substantial description of their diversity, distribution and life history traits, as well as a description of their associated virome.
Gwenaëlle Comont, Marie Laurens, Chantal Faure, Philippe Larignon, Thierry Candresse, Armelle Marais, Marie‐France Corio‐Costet   +6 more
wiley   +1 more source