Results 101 to 110 of about 25,464 (256)

MEL frequency cepstral coefficients (MFCC) of original speakers and their imitators

Archives of Acoustics, 2014
The results of intra- and interspeaker distances between MFCC vectors obtained from speech samples of eight well-known Polish personalities and their imitations performed by cabaret entertainers are presented and discussed.
W. Majewski
doaj  

Snoring sound classification in patients with cerebrovascular stenosis based on an improved ConvNeXt model

Frontiers in Physiology
IntroductionSnoring is a common symptom of Obstructive Sleep Apnea (OSA) and has also been associated with an elevated risk of cerebrovascular disease. However, existing snoring detection studies predominantly focus on individuals with Obstructive Sleep ...
Caijian Hua, Zhihui Liu, Liuying Li, Xia Zhou, Caorong Xiang   +4 more
doaj   +1 more source

Raga Identification Using Mel Frequency Cepstral Coefficient

International Journal of Innovations in Engineering and Science, 2023
Kavita. S. Patil, Pramod J. Deore, V. S. Kharote   +2 more
openaire   +1 more source

Voice authentication module using mel-cepstral coefficients

Вестник Дагестанского государственного технического университета: Технические науки
Objective. The purpose of the study is to develop and apply a method for extracting information about the identity of users from recordings of their voices using the calculation of mel-cepstral coefficients.Method.
D. A. Elizarov, P. A. Ashaeva, E. A. Stepanova   +2 more
doaj   +1 more source

Sound Event Detection for Music Signals Using Gaussian Processes

TecnoLógicas, 2013
In this paper we present a new methodology for detecting sound events in music signals using Gaussian Processes. Our method firstly takes a time-frequency representation, i.e. the spectrogram, of the input audio signal. Secondly the spectrogram dimension
Pablo A. Alvarado-Durán, Mauricio A. Álvarez-López, Álvaro A. Orozco-Gutiérrez   +2 more
doaj  

TriSpectraKAN: a novel approach for COPD detection via lung sound analysis

Scientific Reports
This study aims to create an automated, accessible, and cost-effective diagnostic tool for chronic obstructive pulmonary disease (COPD). Traditional diagnostic methods are expensive, time-consuming, and require specialized equipment.
Abhinav Roy, Bhavesh Gyanchandani, Aditya Oza, Anurag Singh   +3 more
doaj   +1 more source

Cochleogram-Based Speech Emotion Recognition with the Cascade of Asymmetric Resonators with Fast-Acting Compression Using Time-Distributed Convolutional Long Short-Term Memory and Support Vector Machines

Biomimetics
Feature extraction is a crucial stage in speech emotion recognition applications, and filter banks with their related statistical functions are widely used for this purpose.
Cevahir Parlak
doaj   +1 more source

Speech Emotion Recognition Using Mel-Frequency Cepstral Coefficients

INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Abstract—Speech Emotion Recognition (SER) has multiple applications in computational psychology, as well as human- computer interaction, and it also plays a major role in these fields. The accuracy of any machine learning technique is greatly impacted by the extraction as well as the appearance of features.
Dev Ankit Kumar, Er. Disha Sharma, Suraj Kumar, Rishav Kumar, Ambuj Shukla, Amanjeet Kumar   +5 more
openaire   +1 more source

The mechanism of labor in nonhuman primates: A look inside

The Anatomical Record, EarlyView.
Abstract While in humans, the flexed position of the fetus and its rotating course down the birth canal are well documented, in other primates the mechanism of labor is unknown. Despite the lack of comparative data, it is commonly assumed that the human obstetric mechanism is unique, and anthropologists have disputed when and why the transition to the ...
Melissa K. Stoller
wiley   +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