Results 131 to 140 of about 3,467 (180)

Explainable ResNet-long short-term memory model for the classification of bowel sounds frequency based on multifeature fusion. [PDF]

J Int Med Res
Zhang W, Wang Y, Zhu J, Wu Q, Xu C, Liu L, Zhu S, Liu X, Lin J, Yu C, Yin Q, Ding X, Xu Z.   +12 more
europepmc   +1 more source

Speech impairment detection in children using time frequency features of speech and deep learning techniques. [PDF]

Front Hum Neurosci
Manoswini M, Swain BR, Sahoo B, Gourisaria MK, Jha AV, Bizon N, Swetapadma A.   +6 more
europepmc   +1 more source

Robust Heart Sound Analysis With MFCC and Light Weight Convolutional Neural Network. [PDF]

IEEE Open J Eng Med Biol
Hasan A, Karim M.
europepmc   +1 more source

Advanced feature selection and temporal attention mechanisms with Bi-LSTM classifier for optimizing emotion recognition in Kashmiri speech. [PDF]

Front Artif Intell
Dar GM, Delhibabu R.
europepmc   +1 more source

The Utility of Speech and Language Analytics for Screening Alzheimer's Disease.

Neurodegener Dis
Siddiqui A, Kathiresan T, Opler M, Cohen A, Alber J, Snyder PJ, Vogel AP.   +6 more
europepmc   +1 more source

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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   +3 more sources

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   +1 more source

Audio Detection using Mel-frequency Cepstral Coefficients

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 2021
The lack of benchmark findings for comparison with any suggested approach is one of the most fundamental challenges in sound event detection research. Distinct research explore different sets of events and datasets, making it difficult to distinguish between new and existing methods.
Uppu Jithendra, Usha Mittal, Priyanka Chawla   +2 more
openaire   +1 more source

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   +1 more source