This paper presents a method for enhancing speech signals in the root cepstral domain, typically in conjunction with the cepstral subtraction technique. The effect of the processing is similar to the spectral sharpening method performed in the time domain, but with a much lower computational requirement when combined with cepstral subtraction and with better performance. The portions of the sig...

Multi-resolution sub-band cepstral features strive to exploit discriminative cues in localised regions of the spectral domain by supplementing the full bandwith cepstral features with subband cepstral features derived from several levels of sub-band decomposition. Mult-iresolution feature vectors, formed by concatenation of the subband cepstral features into an extended feature vector, are show...

This paper presents an effective feature processing algorithm for robust speech recognition, based on combined spectral and cepstral processing. The spectral processing consists of FullWave Rectification Spectral Subtraction (FWR-SS) and Likelihood Controlled Instantaneous Noise Estimation (LCINE) while the cepstral processing is based on meanand variance normalisation. The combination is motiv...

Birds are excellent environmental indicators and may indicate sustainability of the ecosystem; birds be used to provide provisioning, regulating, supporting services. Therefore, birdlife conservation-related researches always receive centre stage. Due airborne nature dense tropical forest, bird identifications through audio a better solution than visual identification. The goal this study is fi...

By identifying highly speaker speciic aspects of cep-stral features, the task of speaker recognition can be potentially simpliied. The identiication process can be performed both phonetically and in the cepstral domain. The phonetic analysis aims to determine the temporal aspects of utterances which exhibit the highest degree of speaker speciicity, while the cepstral analysis examines individua...

Short-term cepstral features have long been chosen as standard features for speaker recognition thanks to their relevance and effectiveness. In contrast, discriminative features, calculated by a multi-layer perceptron (MLP) from much longer stretches of time, have been gradually adopted in automatic speech recognition (ASR). It has been shown that augmenting short-term cepstral features with lo...

An auditory-based feature extraction algorithm naming the Basilar-membrane Frequency-band Cepstral Coefficient (BFCC) is proposed to increase the robustness for automatic speech recognition. Compared to Fourier spectrogram based of the MelFrequency Cepstral Coefficient (MFCC) method, the proposed BFCC method engages an auditory spectrogram based on a gammachirp wavelet transform to simulate the...

Abstrtct. A new method for representation of speech spectra based on a pole-zero decomposition technique is proposed in this paper. In this method the parameters of a pole-zero model for the smoothed short-time spectrum of speech are determined by adopting a cepstral matching criterion. The cepstral coefficients of the impulse response of the model are equal to the cepstral coefficients of the ...

Explicit expressions for the second order statistics of cepstral components representing clean and noisy signal waveforms are derived. The noise is assumed additive to the signal, and the spectral components of each process are assumed statistically independent complex Gaussian random variables. The key result developed here is an explicit expression for the cross-covariance between the log-spe...