Results 21 to 30 of about 3,875,284 (170)

Unsupervised Classification of Hydrophone Signals With an Improved Mel-Frequency Cepstral Coefficient Based on Measured Data Analysis

IEEE Access, 2019
Recently, passive detection technology has developed the ability to detect surface ships based on the noise emissions recorded by hydrophones, making it possible in some cases to classify surface ships.
Kunde Yang, Xingyue Zhou
doaj   +1 more source

Drone classification using RF signal based spectral features

Engineering Science and Technology, an International Journal, 2022
Drone detection and classification, important in military and civilian applications, are performed using different sensor signals. Proposed study handles this task using Radio Frequency (RF) signals utilizing basic machine learning methods.
Rabiye Kılıç, Nida Kumbasar, Emin Argun Oral, Ibrahim Yucel Ozbek   +3 more
doaj   +1 more source

Speech Emotion Recognition Using Cepstral Features Extracted With Gammatone Filter Banks Realized Based on ERB and Mel Frequency Scales

IEEE Access
Speech emotion recognition (SER) involves identifying a speaker’s emotional state from their speech utterance. Prior research has explored various cepstral features for developing SER systems. Among these, Mel-frequency cepstral coefficients (MFCC)
Nagarajan Sugan, Lakshmi Sutha Kumar, Nettimi Satya Sai Srinivas   +2 more
doaj   +1 more source

Automatic Detection of Laryngeal Pathology on Sustained Vowels Using Short-Term Cepstral Parameters: Analysis of Performance and Theoretical Justification [PDF]

, 2008
The majority of speech signal analysis procedures for automatic detection of laryngeal pathologies mainly rely on parameters extracted from time domain processing.
Juan Ignacio Godino-Llorente, Víctor Osma-Ruiz, Sáenz Lechón, Nicolas, Fraile Muñoz, Rubén, Nicolás Sáenz-Lechón, Gómez Vilda, Pedro, Pedro Gómez-Vilda, Godino Llorente, Juan Ignacio, Rubén Fraile, Osma Ruiz, Víctor   +9 more
core   +1 more source

Nonlinear acoustic analysis in the evaluation of occupational voice disorders

Medycyna Pracy, 2013
Background: Over recent years numerous papers have stressed that production of voice is subjected to the nonlinear processes, which cause aperiodic vibrations of vocal folds.
Ewa Niebudek-Bogusz, Jacek Grygiel, Paweł Strumiłło, Mariola Śliwińska-Kowalska   +3 more
doaj   +1 more source

Speech and Language Markers of Bipolar Disorder: Challenges and Opportunities. [PDF]

Bipolar Disord
ABSTRACT Background Clinicians aspire to predict the emergence of Bipolar Disorder (BD) in a timely manner. To accomplish this, markers reflecting mental states that can be gathered non‐invasively and at large scale are needed. Here, we systematically evaluate evidence relating speech‐based markers to mood states in BD.
Zaher F, Ahrens J, Raucher-Chéné D, Voppel A, Palaniyappan L.   +4 more
europepmc   +2 more sources

Ekstraksi Ciri Pelafalan Huruf Hijaiyyah Dengan Metode Mel-Frequency Cepstral Coefficients [PDF]

, 2019
Huruf hijaiyyah merupakan huruf penyusun ayat dalam Al Qur’an. Setiap hurufhijaiyyah memiliki karakteristik pelafalan yang berbeda. Tetapi dalam praktiknya,ketika membaca huruf hijaiyyah terkadang tidak memperhatikan kaidah bacaanmakhorijul huruf ...
INDRAWATY, YOULLIA, LUKMAN, RIZKI, DEWI, IRMA AMELIA   +2 more
core   +1 more source

Interfacial Polarization Dynamics of Nitrile Dipoles in Organic Synaptic Transistors for Acoustic Reservoir Computing

Advanced Science, EarlyView.
Interfacial nitrile dipoles unlock tunable memory in organic synaptic transistors through competing polarization and relaxation. Their finite time dynamics are directly harnessed for acoustic reservoir computing, delivering 97.17% spoken digit recognition, reliable speech emotion and snoring recognition, and an ultralow event energy of only 50 aJ ...
Yutian Liu, Jiale Huang, Haoran Fang, Jichen Zhao, Fan Ye, Bo Huang, Ruibin Liang, Jintao Xu, Fanqi Wang, Mingjun Huang, Zhiming Lin, Shuguang Zhang, Linfeng Lan, Junbiao Peng   +13 more
wiley   +1 more source

Feature selection for emotion recognition in speech: a comparative study of filter and wrapper methods [PDF]

PeerJ Computer Science
Feature selection is essential for enhancing the performance and reducing the complexity of speech emotion recognition models. This article evaluates various feature selection methods, including correlation-based (CB), mutual information (MI), and ...
Alaa Altheneyan, Aseel Alhadlaq
doaj   +2 more sources

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

JOIV: International Journal on Informatics Visualization, 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 ...
Sudi Mariyanto Al Sasongko, Shofian Tsaury, Suthami Ariessaputra, Syafaruddin Ch   +3 more
doaj   +1 more source