ISSN: 2277-1891

Jornal Internacional de Inovações, Pensamentos e Ideias Avançadas

Acesso livre

Nosso grupo organiza mais de 3.000 Séries de conferências Eventos todos os anos nos EUA, Europa e outros países. Ásia com o apoio de mais 1.000 Sociedades e publica mais de 700 Acesso aberto Periódicos que contém mais de 50.000 personalidades eminentes, cientistas de renome como membros do conselho editorial.

Periódicos de acesso aberto ganhando mais leitores e citações
700 periódicos e 15 milhões de leitores Cada periódico está obtendo mais de 25.000 leitores

Abstrato

FFT and Wavelet-Based Feature Extraction for Acoustic Audio Classification.

A.K.M Fazlul Haque

Speech is one of the vital signals of acoustic classification. Speech recognition is also significant and very well known of audio processing. Speech contains very important frequency information of human being. The features of Audio, especially speech signal may be extracted using FFT (Fast Fourier Transform) and Wavelet to detect the frequency information of the signal. But it is difficult to extract the changes of small variation of speech signal with time-varying morphological characteristics. So, it is needed to be extracted by signal processing method because there are not visible of graphical audio signal. In this paper, an improved wavelet method has been proposed to extract the precise detection of small abnormalities of both original and noise corrupted speech signal which are taken empirically by writing MATLAB program. The proposed wavelet method found to be more summarized over conventional FFT and Wavelet in finding the small abnormalities of audio signal.