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Harish, P.
- Optimizing Voice Recognition Using Various Techniques
Authors
1 Department of ECE, KL University, Vijayawada, A.P, IN
Source
Digital Signal Processing, Vol 4, No 4 (2012), Pagination: 135-141Abstract
Voice recognition is a process of recognizing a person on the basis of their speech sample. This paper describes various techniques that are used for voice recognition in order to optimize the recognition rate. The different techniques that are described in this paper are Linear Predictive Coding (LPC), Neural Networks (NN), Mel Frequency Cepstrum Coefficients (MFCC), Vector quantization (VQ), Euclidean Distance. MFCC and LPC are used to extract speaker specific characteristics from voice signal. Neural Networks and Euclidean Distance are used for matching the characteristics extracted using MFCC and LPC. The recognition rates are calculated in each method and they are compared. Mel Frequency Cepstrum Coefficients gives better recognition rate when compared with the other two techniques. Various other approaches for implementing voice recognition are Hidden Markov Modeling (HMM), Gaussian Mixture Modeling (GMM), and Dynamic Time Warping etc. The Voice Recognition system has potential applications in various fields. Some of them are access control to computers, telephone banking, forensics, speech recognition etc.Keywords
Linear Predictive Coding (LPC), Mel Frequency Cepstral Coefficients (MFCC), Neural Networks( NN), Vector Quantization (VQ).
- A Linear Transform Approach for PAPR Reduction in OFDM Signals by PTS using Segmented and Iterative Phase Weighting Factors
Authors
1 Department of Communication Systems, Rajalakshmi Engineering College, Chennai, IN
2 Department of ECE, Rajalakshmi Engineering College, Chennai, IN
3 Rajalakshmi Engineering College, Chennai, IN
Source
Digital Signal Processing, Vol 4, No 6 (2012), Pagination: 238-244Abstract
Orthogonal Frequency Division Multiplexing (OFDM) is one of the attractive technology for wireless communications with Multi-Carrier Modulation (MCM) technique offers a considerable multipath delay spread tolerance, high spectral efficiency, immunity to the frequency selective fading channels and power efficiency. High Peak-to-Average Power Ratio (PAPR) of the transmit signal is a major drawback of multicarrier transmission such as OFDM. Partial Transmit Sequence (PTS) is one of the commonly used schemes to reduce the PAPR. Conventional Partial Transmit Sequence (C-PTS) requires an exhaustive searching over all combinations of the given phase factors, which results in exponential increase to the computational complexity with the number of sub blocks. In this paper, we aim to obtain the desirable PAPR reduction with the low computational and phase search complexity. PTS based phase weighting techniques with low computational complexity, named Segmented Phase Weighting (SPW) and Iterative Phase Weighting (IPW), are proposed. On applying one of the linear transformation techniques called circular time shift to the candidate sequences obtained by SPW and IPW method, high PAPR reduction can be obtained. This system will slightly increase the computational complexity but greater reduction in PAPR. At the receiver, by utilizing the natural diversity of phase constellation for different candidates, the detector can successfully recover the original signal without Side Information (SI). PAPR reduction performance of both proposed schemes are analyzed, the simulation results show that the proposed Circular Time Shifted- Segmented Phase Weighting (CTS-SPW) and Circular Time Shifted- Iterative Phase Weighting (CTS-IPW) schemes achieve better PAPR reduction compared to the C-PTS scheme.