Sound pattern recognition supports automatic inspection

Sensor Review ◽  
1985 ◽  
Vol 5 (1) ◽  
pp. 13-17 ◽  
Author(s):  
Karl Beuter ◽  
Rainer Weiß
2019 ◽  
Vol 4 (2) ◽  
pp. 294 ◽  
Author(s):  
Rusydi Umar ◽  
Imam Riadi ◽  
Abdullah Hanif

Sound is a part of the human body that is unique and can be distinguished, so its application can be used in sound pattern recognition technology, one of which is used for sound biometrics. This study discusses the analysis of the form of a sound pattern that aims to determine the shape of the sound pattern of a person's character based on the spoken voice input. This study discusses the analysis of the form of a sound pattern that aims to determine the shape of the sound pattern of a person's character based on the spoken voice input. This study uses the Melf-Frequency Cepstrum Coefficients (MFCC) method for feature extraction process from speaker speech signals. The MFCC process will convert the sound signal into several feature vectors which will then be displayed in graphical form. Analysis and design of sound patterns using Matlab 2017a software. Tests were carried out on 5 users consisting of 3 men and 2 women, each user said 1 predetermined "LOGIN" word, which for 15 words said. The results of the test are the form of a sound pattern between the characteristics of 1 user with other users. Keywords—Voice, Pattern, Feature Extraction, MFCC


1977 ◽  
Vol 24 (8) ◽  
pp. 811-825 ◽  
Author(s):  
Fanny Viénot ◽  
Claudine Bainier ◽  
Bernard Carquille ◽  
Michel Guignard

1990 ◽  
Vol 34 (4) ◽  
pp. 313-329 ◽  
Author(s):  
A FENG ◽  
J HALL ◽  
D GOOLER

2003 ◽  
Vol 45 (7) ◽  
pp. 475-483 ◽  
Author(s):  
D Mery ◽  
R R da Silva ◽  
L P Calôba ◽  
J M A Rebello

Author(s):  
Hendro Nugroho ◽  
Wahyu Widodo ◽  
Andy Rachman

To know the type of bird, most people know from the shape of bird species and the sound of birds. In this study, it identified the pattern of bird sounds. The bird sounds studied were Canary Trills, Vulture and Crow birds. In the introduction of the type of bird sound pattern in this study using the Discrete Cosine Transform (DCT) method and Gaussian value. The researcher conducted several steps to get the sound model of birds, among others, namely (1) bird sound input in the form of WAV file, (2) Hamming Windowing, (3) DFT / FFT, (4) Mel Bank Filter, (5) DCT, and (6) Value Gaussian. The output obtained is in the form of vector values and represented in graphical form. The results obtained in the study of pattern recognition of bird sound types get the results of observations in the same bird sound duration and frequency of the same, then the same pattern is obtained in the same bird as evidenced by calculating the closest distance value with Bray Curtis method. For the same duration of time and the length of the frequency that is not the same; it found that the pattern of bird sounds is not the same.


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