A New Cepstrum Coefficients Applied to Acoustic Target Recognition
Cheng Zhang
Abstract
Cheng Zhang
Abstract
A kind of cepstrum coefficients based on new feature was presented.Compared with Mel-frequency cepstral coefficients(MFCC) used extensively at present,it was improved for computing the new cepstrum feature in acoustic target recognition that 1) the bank of triangular filters was improved based on cochlear model;2) the log-compressed was replaced by the exp-compressed which is the function of frequency;3) the adaptive mechanism was introduced into the process of transformation from frequency domain to perceptual domain.Simulations of the four acoustic target recognition were carried out.The simulated results show that the proposed features have strong anti-noise ability.
OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
A kind of cepstrum coefficients based on new feature was presented.Compared with Mel-frequency cepstral coefficients(MFCC) used extensively at present,it was improved for computing the new cepstrum feature in acoustic target recognition that 1) the bank of triangular filters was improved based on cochlear model;2) the log-compressed was replaced by the exp-compressed which is the function of frequency;3) the adaptive mechanism was introduced into the process of transformation from frequency domain to perceptual domain.Simulations of the four acoustic target recognition were carried out.The simulated results show that the proposed features have strong anti-noise ability.
Key concepts: Cepstrum, Mel-frequency cepstrum, Speech recognition, Frequency domain, Noise (video), Computer science, Pattern recognition (psychology), Feature (linguistics)