Results 21 to 30 of about 6,514 (211)
Feature extraction method for reflective sound signal of high pressure water-jet target
In order to improve recognition rate of target materials by using reflective sound signal of high pressure water-jet, in view of four common targets of mine, stone, brick and wood block, different feature extraction methods were used to identify target ...
SUN Shuai +4 more
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The Mel-Frequency Cepstral Coefficients In The Context Of Singer Identification. [PDF]
[TODO] Add abstract here.
Annamaria Mesaros, Jaakko Astola
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MFCC-Based Sound Classification of Honey Bees [PDF]
—Smart beekeeping is a rapidly developing field. Automated detection and classification of honey bees opens many new opportunities for studies on their behavior.
Urszula Libal, Pawel Biernacki
doaj +1 more source
The speech signal within a sub-band varies at a fine level depending on the type, and level of dysarthria. The Mel-frequency filterbank used in the computation process of cepstral coefficients smoothed out this fine level information in the higher ...
Laxmi Priya Sahu +2 more
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Normal distribution analysis (mean±std) of the combined mel-frequency cepstral coefficients (MFCCs) using the shallow breathing dataset.
Mohanad Alkhodari (11944473) +1 more
core +1 more source
Footstep Recognition Using Mel Frequency Cepstral Coefficients and Artificial Neural Network
Footstep recognition is relatively new biometrics and based on the learning of footsteps signals captured from people walking on the sensing area.
Thasya Nurul Wulandari Siagian +2 more
doaj +1 more source
Normal distribution analysis (mean±std) of the combined mel-frequency cepstral coefficients (MFCCs) using the deep breathing dataset.
Mohanad Alkhodari (11944473) +1 more
core +1 more source
Discriminant Analysis of Voice Commands in the Presence of an Unmanned Aerial Vehicle
The aim of this study was to perform discriminant analysis of voice commands in the presence of an unmanned aerial vehicle equipped with four rotating propellers, as well as to obtain background sound levels and speech intelligibility.
Marzena Mięsikowska
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Emotion Recognition using Mel-Frequency Cepstral Coefficients
In this paper, we propose a new approach to emotion recognition. Prosodic features are currently used in most emotion recognition algorithms. However, emotion recognition algorithms using prosodic features are not sufficiently accurate. Therefore, we focused on the phonetic features of speech for emotion recognition.
Sato, Nobuo, Obuchi, Yasunari
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Wavelet based feature combination for recognition of emotions
In this paper, authors tried to develop reduced combinational features for emotional speech recognition. The spectral/cepstral features like wavelet coefficient, LPCC (linear prediction cepstral coefficient) and MFCC (mel-frequency cepstral coefficient ...
Hemanta Kumar Palo +1 more
doaj +1 more source

