Results 81 to 90 of about 3,790,103 (166)
Abstract Distributed wireless acoustic sensors, such as accelerometers, in smart water networks are increasingly used to detect leaks before they escalate into pipe breaks. In addition to leak‐induced signals, these sensors also capture acoustic noise generated by pumping and valve operations, pedestrians, traffic, and other environmental sources ...
Wei Zeng +5 more
wiley +1 more source
Knocking-sound analysis provides a non-destructive method for assessing durian ripeness; however, most convolutional neural network methods mainly emphasize magnitude information while disregarding phase information that reflects the overall signal ...
Khomdet Phapatanaburi +7 more
doaj +1 more source
Automated classification of vowel category and speaker type in the high-frequency spectrum
The high-frequency region of vowel signals (above the third formant or F3) has received little research attention. Recent evidence, however, has documented the perceptual utility of high-frequency information in the speech signal above the traditional ...
Jeremy J. Donai +2 more
doaj +1 more source
On Compensating the Mel-Frequency Cepstral Coefficients
This paper describes a novel noise-robust automatic speech recognition (ASR) front-end that employs a combination of Mel-filterbank output compensation and cumulative distribution mapping of cepstral coefficients with truncated Gaussian distribution ...
For Noisy Speech, Eric H. C. Choi
core
Dysphonia Detection based on modulation spectral features and cepstral coefficients [PDF]
In this paper, we combine modulation spectral features with mel-frequency cepstral coefficients for automatic detection of dysphonia. For classification purposes, dimensions of the original modulation spectra are reduced using higher order singular value
Arias-Londoño, Julián David +3 more
core
Background: Special consideration has recently been given to cepstral analysis with mel-frequency cepstral coefficients (MFCCs). The aim of this study was to assess the applicability of MFCCs in acoustic analysis for diagnosing occupational dysphonia in ...
Ewa Niebudek-Bogusz +3 more
doaj +1 more source
Identification of voice signals can be used to command a computer system. Identification can be made of voice owner and spoken word. Identification of voice owner is used for security, while spoken word identification is often used to execute command on ...
Munggaran, Angga Kersana +2 more
core
Multilingual Speaker Identification by Combining Evidence from LPR and Multitaper MFCC
In this work, the significance of combining the evidence from multitaper mel-frequency cepstral coefficients (MFCC), linear prediction residual (LPR), and linear prediction residual phase (LPRP) features for multilingual speaker identification with the ...
Nagaraja B.G., Jayanna H.S.
doaj +1 more source
Voice source characteristics in different phonation types vary due to the tension of laryngeal muscles along with the respiratory effort. This study investigates the use of mel-frequency cepstral coefficients (MFCCs) derived from voice source waveforms ...
Kadiri, Sudarsana Reddy +3 more
core +1 more source
MEL-FREQUENCY CEPSTRAL COEFFICIENTS (MFCC) FEATURE FOR PUMP ANOMALY DETECTION IN NOISY ENVIRONMENTS
The continuity of a production process is supported by the availability of good assets. One of the efforts to support asset availability is through asset maintenance. One of the important assets in the industry is the pump. To detect anomalous conditions
Anindita Adikaputri Vinaya +1 more
doaj +1 more source

