[PDF] Top 20 Vector Quantization Approach for Speaker Recognition using MFCC and Inverted MFCC
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Vector Quantization Approach for Speaker Recognition using MFCC and Inverted MFCC
... VQ-based approach the speaker models are formed by clustering the speaker’s feature vectors in K non-overlapping ...code vector ci, which is the centroid ...VQ-based speaker recognition ... See full document
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Text Independent Automatic Speaker Recognition System Using Mel Frequency Cepstrum Coefficient and Gaussian Mixture Models
... proach, PLP (Perceptual Linear Predictive cepstrum) and MF-PLP (Mel Frequency PLP) achieved 91% accuracy rate with 50 speakers randomly chosen from TIMIT da- tabase [38]. In 2009 Chakroborty and Saha [39] combin- ing ... See full document
6
IJCSMC, Vol. 4, Issue. 5, May 2015, pg.394 – 400 RESEARCH ARTICLE A MFCC Integrated Vector Quantization Model for Speaker Recognition
... and recognition is common biometric application area adapted by different ...integrated approach for complex speech signal ...based approach to transform the speech in feature using HMM ... See full document
7
Learning Vector Quantization (LVQ) Neural Network Approach for Multilingual Speech Recognition
... pattern recognition feature extraction plays a key role. In speech recognition it is the key step so that it is necessary to keep more attention to feature extraction ...Learning Vector ... See full document
7
Speaker recognition with hybrid features from a deep belief network
... system using selected speech files from NIST 2004 and NIST 2005 SRE ...learning speaker-specific characteristics from speech data with unsupervised model offers great ...our approach which include ... See full document
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Speech Recognition System with Speaker Verification using HMM, LPC & MFCC
... speech recognition techniques including commercially available ones like Nuance, Siri, Microsoft Speech SDK depends upon the clarity of spoken words and phrases for recognition accuracy, such systems cannot ... See full document
7
Speaker Recognition and Gender Identification using Artificial Neural Network and Support Vector Machine
... the speaker recognition rate to some ...system. MFCC modeled on the filter bank technique is the most popular feature for speaker recognition because of its advantages over the other ... See full document
6
Speaker Recognition using MFCC front end analysis and VQ Modeling Technique for Hindi words using MATLAB
... feature vector models includes the Hidden Markov Model (HMM), Dynamic Time Warping (DTW)neural networks (NN) and Vector quantization ...pattern recognition techniques in speech and ... See full document
5
Speaker Recognition System and Algorithms
... a speaker recognition system (SRS) using Mel-Frequency Cepstrum Coefficients (MFCC), Linear Prediction writing (LPC) as feature extraction techniques and Vector quantisation (VQ) as ... See full document
5
Real Time Speaker Recognition using Mel-Frequency Cepstral Coefficients (MFCC) ,VQLBG & GMM Techniques
... Vector quantization (VQ in short) is one of feature matching algorithm. It takes a large set of feature vectors of a registereduser and produce a smaller set of feature vectors that represent the centroids ... See full document
8
Speech Recognition using MFCC and Neural Networks
... speech recognition has gained a lot of ...speech recognition exist like Dynamic Time Warping (DTW), Hidden Markov Model ...speech recognition and also investigates its performance in speech ... See full document
8
Accent Recognition using MFCC and LPC with Acoustic Features
... speech recognition for accent ...extracted using linear predictive coding (LPC), formant and log energy feature ...a speaker is predicated using K-Nearest Neighbors (KNN) ...developed ... See full document
7
Design of An Intelligent Speaker Recognition System using Mel Frequency Cepstrum Coefficients and Vector Quantization for Biometric Authentication
... automatic speaker recognition system consists of 2 phases: enrollment and testing ...trained using MFCC and Vector ...the recognition is made. Speaker identification and ... See full document
9
Accuracy of MFCC-Based Speaker Recognition in Series 60 Device
... feature vector set. We use the vector quantization (VQ) model to represent the statistical distribution of the features of each ...feature vector set is replaced by a code- book, which is a ... See full document
12
DWT and LPC based feature extraction methods for isolated word recognition
... speech recognition system has two major compo- nents, namely, feature extraction and ...parametric approach such as linear prediction [1], which is developed to closely match the resonant structure of human ... See full document
7
Speaker Identification by using Vector Quantization
... of speaker recognition is to extract the identity of the person ...speaking. Speaker recognition technology makes it possible to use the speaker's voice to control access to restricted ... See full document
7
Speaker identification system using MFCC procedure and noise reduction method
... of Speaker Recognition has proposed a method in removing background ...Then, using 3 rd order Butterworth low-pass filter which is also an IIR filer, the higher frequency signal will be ... See full document
28
Text Independent Speaker Modeling and Identification Based On MFCC Features
... of speaker-specific information with statistical ...particular speaker, whereas they can be non-informative for another ...for speaker-specific processing and for adaptability to the environment ... See full document
9
A Natural Human-Machine Interaction via an Efficient Speech Recognition System
... extracted MFCC, dynamic features of MFCC, HFCC, and their dynamic ...feature vector is also proposed of MFCC, HFCC, and their dynamic features, named as, INTEGRATED STATIC AND DYNAMIC CEPSTRAL ... See full document
7
Significance of Joint Features Derived from the Modified Group Delay Function in Speech Processing
... for recognition of syllables on the DBIL Tamil and Telugu databases ...baseline recognition system uses hidden Markov models trained apriori for 320 sylla- bles for Tamil and 265 syllables for Telugu ... See full document
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