The objective of this work is to study the speaker-specific nature of analytic phase of speech signals. Since computation of analytic phase suffers from phase wrapping problem, we have used its derivativethe instantaneous frequency for feature extraction. The cepstral coefficients extracted from smoothed subband instantaneous frequencies (IFCC) are used as features for speaker verification. The...

In this paper, we investigate the noise-robustness of features based on the cepstral time coefficients (CTC). By cepstral time coefficients, we mean the coefficients obtained from applying the discrete cosine transform to the commonly used mel-frequency cepstral coefficients (MFCC). Furthermore, we apply temporal filters used for computing delta and acceleration dynamic features to the CTC, res...

In the analysis of musical acoustics, we usually use the power spectrum to describe the difference between timbres from two music instruments. However, according to our experiments, the power spectrum cannot be used as effective features for erhu instrument identification. In this paper, we use MFCC (mel-scale frequency cepstral coefficients) as features for music instrument identification usin...

Javanese is an Indonesian culture which needs to be preserved, but many students make mistakes in the pronunciation of letters and find it difficult analyze errors by human teachers because limited time subjective assessment, so a system needed detect incorrect letters. Mispronunciation detection has been widely applied foreign languages, not implemented for carakan This research develops mispr...

In this paper we propose a filter bank structure derived by using admissible wavelet packet transform. These filters have Mel scale spacing and have an advantage of easy implementation with higher resolution in time-frequency domain because of wavelet transform. The features are obtained by first calculating the energy in each filter band and then applying the Discrete Cosine Transform (DCT) to...

This paper presents the robust front-end algorithm that was submitted by Motorola to the ETSI STQ-Aurora DSR working group as a proposal for the Advanced DSR front-end in January 2001. The algorithm consists of a two-stage melwarped Wiener filter, a waveform processor, a channelnormalized mel-frequency cepstral calculation and a subsystem of post-cepstral processing according to the reliability...

Speech Synthesis (SS) and Voice Conversion (VC) presents a genuine risk of attacks for Automatic Speaker Verification (ASV) technology. In this paper, we use our recently proposed unsupervised filterbank learning technique using Convolutional Restricted Boltzmann Machine (ConvRBM) as a frontend feature representation. ConvRBM is trained on training subset of ASV spoof 2015 challenge database. A...

This paper presents a novel low complexity, frequency domain algorithm for reconstruction of speech from the melfrequency cepstral coe cients (MFCC), commonly used by speech recognition systems, and the pitch frequency values. The reconstruction technique is based on the sinusoidal speech representation. A set of sine-wave frequencies is derived using the pitch frequency and voicing decisions, ...

Existing standard speech coders can provide speech communication of high quality while they degrade the performance of speech recognition systems that use the reconstructed speech by the coders. The main cause of the degradation is that the spectral envelope parameters in speech coding are optimized to speech quality rather than to the performance of speech recognition. For example, mel-frequen...

This study proposes a new set of feature parameters based on subband analysis of the speech signal for classi cation of speech under stress. The new speech features are Scale Energy (SE), Autocorrelation-Scale-Energy (ACSE), Subband based cepstral parameters (SC), and Autocorrelation-SC (ACSC). The parameters' ability to capture di erent stress types is compared to widely used Mel-scale cepstru...