Three simple speaker verification techniques based on vector quantization, sphericity models and dynamic time warping, respectively, are developed and tested using the same experimental protocol. Two types of feature vectors, the linear prediction derived cepstral coefficients and the melfrequency cepstral coefficients are considered. The efficiency of the combination of the type of acoustic an...

In this paper we consider the problem of modeling spectro-temporal behaviour of musical sounds, with applications for musical instrument recognition. Using instanteneous sound features, such as cepstral envelopes and cepstral derivatives, the temporal evolution of the sound is transcribed into a new representation as a sequence of spectral features. Applying information-theoretic sequence match...

Crop disease detection methods vary from traditional machine learning, which uses Hand-Crafted Features (HCF) to the current deep learning techniques that utilize features. In this study, a hybrid framework is designed for crop using feature fusion. Convolutional Neural Network (CNN) used high level features are fused with HCF. Cepstral coefficients of RGB images presented as one along other po...

In this paper we use a particular type of mutual information norm — the cepstral information norm — for anomaly detection at the router level in the Internet. We combine the cepstral norm with a state space Kalman filter to define two distance metrics to capture anomalous behaviour. These metrics are implemented using a subspace-based model-free paradigm to aid realtime analysis. We infer a top...

A method is described for designing speaker recognition features that are robust to telephone handset distortion. The approach transforms features such as mel-cepstral features, log spectrum, and prosody-based features with a non-linear arti®cial neural network. The neural network is discriminatively trained to maximize speaker recognition performance speci®cally in the setting of telephone han...

The goal of speech parameterization is to extract the relevant information about what is being spoken from the audio signal. In speech recognition systems Mel-Frequency Cepstral Coefficients (MFCC) and Relative Spectral Mel-Frequency Cepstral Coefficients (RASTA-MFCC) are the two main techniques used. It will be shown in this paper that it presents some modifications to the original MFCC method...

Time delay estimation (TDE) between the signals received by two or more spatially separated microphones can be used as a means for the passive localization of the dominant talker in applications such as audio-conference. However, in a recent study, it has been shown that reverberation can have disastrous eeects on TDE performance. In this paper , we develop and evaluate a new cepstral preelteri...

This paper introduces a new articulation rate filter and reports its combination with recently proposed constant Q cepstral coefficients (CQCCs) in their first application to automatic speaker verification (ASV). CQCC features are extracted with the constant Q transform (CQT), a perceptually-inspired alternative to Fourier-based approaches to time-frequency analysis. The CQT offers greater freq...