Results 81 to 90 of about 6,219 (212)

Automatic Speaker Recognition Based on Mel-Frequency Cepstral Coefficients and Gaussian Mixture Models [PDF]

Mehran University Research Journal of Engineering and Technology, 2013
This paper investigates the task of SR (Speaker Recognition) for the state-of-the-art techniques. The paper initially presents the technical description of automatic SR, followed by the comparative analysis of a number of methods available for feature ...
Sheeraz Memon, Sania Bhatti, Farzana Rauf Abro   +2 more
doaj  

A Wireless, Battery‐Free Artificial Throat Patch with Deep Learning for Emotional Speech Recognition

Advanced Science, Volume 13, Issue 19, 2 April 2026.
In this work, Xu and co‐workers develop a wireless, battery‐free artificial throat patch system (ATPS) consisting of a carbon nanotube‐based thin‐film strain sensor and a miniaturized flexible printed circuit board, to enable real‐time sensing of throat signals.
Bingxin Xu, Guanming Lin, Xiaohui Hong, Chuting Liu, Xinyi Qu, Kangjian Jiao, Lei Zhang, Bingzhe Xu, Jun Yan, Yancong Qiao, Xudong Lin   +10 more
wiley   +1 more source

Automated classification of vowel category and speaker type in the high-frequency spectrum

Audiology Research, 2016
The high-frequency region of vowel signals (above the third formant or F3) has received little research attention. Recent evidence, however, has documented the perceptual utility of high-frequency information in the speech signal above the traditional ...
Jeremy J. Donai, Saeid Motiian, Gianfranco Doretto   +2 more
doaj   +1 more source

Predicting fundamental frequency from mel-frequency cepstral coefficients to enable speech reconstruction [PDF]

, 2005
This work proposes a method to reconstruct an acoustic speech signal solely from a stream of mel-frequency cepstral coefficients (MFCCs) as may be encountered in a distributed speech recognition (DSR) system.
Xu Shao, Shao, Xu, Ben Milner, Milner, Ben P.   +3 more
core   +1 more source

A dual-stream CNN-based ConvMixer for durian ripeness classification using magnitude and phase features from knocking sounds

Results in Engineering
Knocking-sound analysis provides a non-destructive method for assessing durian ripeness; however, most convolutional neural network methods mainly emphasize magnitude information while disregarding phase information that reflects the overall signal ...
Khomdet Phapatanaburi, Khwanjit Orkweha, Watcharakorn Pinthurat, Chaiwat Makhonpas, Wongsathon Pathonsuwan, Patikorn Anchuen, Monthippa Uthansakul, Peerapong Uthansakul   +7 more
doaj   +1 more source

Comparison of cepstral coefficients to other voice evaluation parameters in patients with occupational dysphonia

Medycyna Pracy, 2013
Background: Special consideration has recently been given to cepstral analysis with mel-frequency cepstral coefficients (MFCCs). The aim of this study was to assess the applicability of MFCCs in acoustic analysis for diagnosing occupational dysphonia in ...
Ewa Niebudek-Bogusz, Paweł Strumiłło, Justyna Wiktorowicz, Mariola Śliwińska-Kowalska   +3 more
doaj   +1 more source

Machine Vision–Based Insect Recognition in Agriculture: A Comprehensive Review

Engineering Reports, Volume 8, Issue 4, April 2026.
This study explores machine vision for automated insect recognition in agriculture, leveraging deep learning and IoT integration. The review highlights real‐time pest detection methods, enhancing crop protection with minimal pesticide use. Comparative analysis of classifiers provides insights into performance and future advancements in sustainable ...
Mohammad Monirul Islam, Morium Akter, Mohammad Shorif Uddin, Md. Ataur Rahman, Md. Tarek Habib   +4 more
wiley   +1 more source

EKSTRAKSI CIRI EMOSI MANUSIA BERDASARKAN UCAPAN MENGGUNAKAN MEL-FREQUENCY CEPSTRAL COEFFICIENTS (MFCC) [PDF]

, 2018
Emosi merupakan perilaku manusia yang dapat diungkapkan dengan tingkah laku berupa raut wajah dan suara. Suara adalah suatu gelombang longitudinal yang merambat di udara. Pada kehidupan sehari-hari manusia berkomunikasi dengan menggunakan suara. Baik itu
Helmiyah, Siti, Yudhana, Anton, Fadlil, Abdul   +2 more
core  

Dysphonia detection based on modulation spectral features and cepstral coefficients [PDF]

, 2010
In this paper, we combine modulation spectral features with mel-frequency cepstral coefficients for automatic detection of dysphonia. For classification purposes, dimensions of the original modulation spectra are reduced using higher or-der singular ...
J. D. Arias-londoño, M. Markaki, J.D. Arias-Londono, J. I. Godino-llorente, J.I. Godino-Llorente, Y. Stylianou   +5 more
core   +4 more sources

PEMODELAN SPEECH RECOGNITION SPEECH-TO-TEXT DALAM BAHASA INDONESIA MENGGUNAKAN MEL FREQUENCY CEPSTRAL COEFFICIENTS (MFCC) DAN HIDDEN MARKOV MODEL (HMM) Speech Recognition Modeling Speech-to-Text in Bahasa Using Mel Frequency Cepstral Coefficients (MFCC) a [PDF]

, 2013
ABSTRAKSI: Speech recognition merupakan salah satu teknologi yang mempermudah pekerjaan manusia dalam berinteraksi dengan komputer. Oleh karena itu, penelitian mengenai speech recognition merupakan kunci pengembangan teknologi tersebut.
SITI KHODIJAH F N F
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