Results 61 to 70 of about 28,361 (199)

The Capacity Of Mel Frequency Cepstral Coefficients For Speech Recognition

, 2017
Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output.
Al-Anzi, Fawaz S., Dia AbuZeina
openaire   +2 more sources

Shouted speech detection using hidden markov model with rahmonic and mel-frequency cepstrum coefficients [PDF]

, 2016
In recent years, crime prevention systems have been developed to detect various hazardous situations. In general, the systems utilize the image information recorded by a camera to monitor the situations.
Masato Nakayama, Nishiura, Takanobu, Nanjo, Hiroaki, Takanobu Nishiura, Hiroaki Nanjo, Nakayama, Masato, Takahiro Fukumori, Fukumori, Takahiro   +7 more
core   +1 more source

Performance of using Mel-Frequency Cepstrum Based Features in Nonlinear Classifiers for Phonocardiography Recordings

, 2023
Cardiovascular system diseases can be identified by using a specialized diagnostic process utilizing a digital stethoscope. Digital stethoscopes provide phonocardiography (PCG) recordings for further inspection, besides filtering and amplification of ...
Yilmaz, Atila, Ozkan, Ibrahim
core   +2 more sources

Detection of Laryngeal Pathologies from Voice using EMD-based Mel-Spectrograms and Scalograms with AlexNet

Measurement Science Review
In this paper, a novel method for detecting of laryngeal pathologies using deep neural networks and time–frequency signal processing techniques is presented.
Cherif Sofiane, Kaddour Abdelhafid, Benkada Abdelmoudjib, Karoui Said   +3 more
doaj   +1 more source

Hybrid Log-Mel and HPSS-Aided Convolutional Neural Network for Underwater Very-Low-Frequency Remote Passive Sonar Detection

Journal of Marine Science and Engineering
Very-low-frequency (VLF) passive sonar detection is one of the core technologies for maritime surveillance, although its performance is often severely affected by strong impulsive ocean ambient noise interference. This paper, for the first time, proposes
Haitao Dong, Lijian Yang, Yuan Liu, Siyuan Li   +3 more
doaj   +1 more source

Mel Frequency Cepstral Coefficients (MFCC) Method and Multiple Adaline Neural Network Model for Speaker Identification

, 2023
Speech recognition technology makes human contact with the computer more accessible. There are two phases in the speaker recognition process: capturing or extracting voice features and identifying the speaker's voice pattern based on the voice ...
Ch, Syafaruddin, Ariessaputra, Suthami, Sasongko, Sudi Mariyanto Al, Tsaury, Shofian   +3 more
core   +2 more sources

ANALISIS EMOSI MANUSIA DENGAN DETEKSI SUARA MENGGUNAKAN MEL-FREQUENCY CEPSTRAL COEFFICIENT DAN ANN-SELF ORGANIZING MAP [PDF]

, 2018
Emosi manusia pada umumnya dapat dengan mudah diketahui dengan melihat raut wajah yang dapat berubah-ubah berdasarkan perasaan seseorang. Banyak peneliti yang telah melakukan pendeteksian emosi berdasarkan raut wajah.
RAHMAT HARYADI
core  

Automatic Hypernasal Detection Based on Acoustic Analysis in Cleft Palate Speech

工程科学与技术, 2014
:In order to detect hypernasal automatically for cleft palate patients, based on Shannon energy and Mel frequency cepstrum coefficient acoustic features and by combining with Gaussian mixture model classifier, an automatic hypernasal detection algorithm ...
何凌, 袁亚南, 尹恒, 张桠童, 张劲, 刘奇, 李杨   +6 more
doaj  

Voice spoofing detection using a neural networks assembly considering spectrograms and mel frequency cepstral coefficients. [PDF]

PeerJ Comput Sci, 2023
Hernández-Nava CA, Rincón-García EA, Lara-Velázquez P, de-Los-Cobos-Silva SG, Gutiérrez-Andrade MA, Mora-Gutiérrez RA.   +5 more
europepmc   +1 more source

Optimal Feature Selection Technique for Mel Frequency Cepstral Coefficient Feature Extraction in Classifying Infant Cry with Asphyxia

, 2017
<p>Mel Frequency Cepstral Coefficient is an efficient feature representation method for extracting human-audible audio signals. However, its representation of features is large and redundant.
A. Zabidi, Mansor, W., Y. Lee, Khuan, Zabidi, A., W. Mansor, Khuan Y. Lee   +5 more
core   +2 more sources