This paper proposes a hybrid wavelet-neural network approach to classify speech for multifunctional control applications. The classification of the consonants (b,d,g) is the focus of this work. MultiResolution Wavelet Analysis (MRWA) was used to extract utterance features while a modular Artificial Neural Network (ANN) was used for classification. The performance of the proposed method was comp...

Cepstrum coefficients are widely used as features for both speech and music. In this paper, the use of discrete cepstrum coefficients is considered, which are computed from sinusoidal peaks in the short time spectrum. These coefficients are very interesting as features for pattern recognition applications since they allow to represent spectra by points in a multidimensional vector space. A new ...

In this study, an investigation over digestive diseases has been done in which the sound acts as a detector medium. Pursue to the preprocessing the extracted signal in cepstrum domain is registered. After classification of digestive diseases, the system selects random samples based on their features and generates the interest nonstationary, long-term signals via inverse transform in cepstral do...

This paper proposed a low-cost dual-ALU processor for speech recognition. It does not give an emphasis on sophistication but on low-cost solution. The dual-ALU architecture provides parallel calculation capability. For the consideration of chip size, the area of the second ALU is only half of the first ALU. We use hardware-software codesign method to implement the speech recognition. The featur...

As telephony services are being supported on Internet the focus is now on multiplexing many speech streams by exploiting the speech characteristics. The multiplexing gain is an important factor when applications such as teleconference service are ported on to the Internet. Here we discuss Voice Activity Detection (VAD) for Voice over Internet Protocol (VoIP) based on Cepstrum. VAD aids in savin...

This paper describes the principle of MFCC feature extraction and the knowledge of human auditory masking effect in order to introduce a modified-MFCC feature extraction that can improve the robustness of speech recognition systems.

In this paper, a drive-by damage detection methodology for high-speed railway (HSR) bridges is addressed, to appraise the application of Mel-frequency cepstral coefficients (MFCC) extract Damage Index (DI). A finite element (FEM) 2D VTBI model that incorporates train, ballasted track and bridge behavior presented. The formulation includes irregularities damaged condition induced in specified st...

In this project, Spectral Envelopes in Sound Analysis and Synthesis, various methods for estimation, representation, file storage, manipulation, and application of spectral envelopes to sound synthesis were evaluated, improved, and implemented. A prototyping and testing environment was developed, and a function library to handle spectral envelopes was designed and implemented. For the estimatio...