Results 171 to 180 of about 3,610,992 (210)

A Smartphone-Based Acoustic Machine Learning Pipeline for Detecting Suicidal Ideation: Case-Control Model Development and Validation Study. [PDF]

JMIR Form Res
Lyu M, Tan L, Xiao J, Huang H, Liu F, Qi J, Huang T, Lei J, Zhao Z, Jiang T, Liu Z, Wang X, Zhong J, Feng Z.   +13 more
europepmc   +1 more source

Fault Diagnosis of Motor Bearing Transmission System Based on Acoustic Characteristics. [PDF]

Sensors (Basel)
Ma L, Zhang Y, Wang Z.
europepmc   +1 more source

Distinguishing Between Healthy and Unhealthy Newborns Based on Acoustic Features and Deep Learning Neural Networks Tuned by Bayesian Optimization and Random Search Algorithm. [PDF]

Entropy (Basel)
Lahmiri S, Tadj C, Gargour C.
europepmc   +1 more source

Predicting competitive outcomes in professional e-sports from 60-second pre-match voice acoustics using machine learning. [PDF]

Front Psychol
Kadri G, Santos RIM, Aguiar FO, Otani VHO, Uchida RR, Marques LM.   +5 more
europepmc   +1 more source

A comparative between Mel Frequency Cepstral Coefficients (MFCC) and Inverse Mel Frequency Cepstral Coefficients (IMFCC) features for an Automatic Bird Species Recognition System

2018 IEEE Latin American Conference on Computational Intelligence (LA-CCI), 2018
In this paper a comparative between Mel Frequency Cepstral Coefficients (MFCC) and Inverse Mel Frequency Cepstral Coefficients (IMFCC) features for an automatic bird species recognition system is proposed with the aim to validate IMFCC as a feature that can also be extracted for bird species recognition.
Aldonso Becerra
exaly   +4 more sources

Mel-frequency Cepstral Coefficients for Eye Movement Identification

2012 IEEE 24th International Conference on Tools with Artificial Intelligence, 2012
Human identification is an important task for various activities in society. In this paper, we consider the problem of human identification using eye movement information. This problem, which is usually called the eye movement identification problem, can be solved by training a multiclass classification model to predict a person's identity from his or ...
Viet Cuong Nguyen, Vu C. Dinh, Lam Si Tung Ho   +2 more
openaire   +3 more sources

Drive-by bridge damage detection using Mel-frequency cepstral coefficients and support vector machine

Structural Health Monitoring, 2023
Bridge damage detection using vibration data has been confirmed as a promising approach. Compared to the traditional method that typically needs to install sensors or systems directly on bridges, the drive-by bridge damage detection method has gained ...
Weiwei Lin, Zhenkun Li, Youqi Zhang
exaly   +2 more sources

Some of the next articles are maybe not open access.

Related searches:

Computing Mel-frequency cepstral coefficients on the power spectrum

2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002
We present a method to derive Mel-frequency cepstral coefficients directly from the power spectrum of a speech signal. We show that omitting the filterbank in signal analysis does not affect the word error rate. The presented approach simplifies the speech recognizers front end by merging subsequent signal analysis steps into a single one.
Sirko Molau, Michael Pitz, Ralf Schlüter, Hermann Ney   +3 more
openaire   +2 more sources