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In this paper, we mainly paying attention on mechanization of Infant's Cry. For this implementation we use LFCC for feature extraction and VQ codebook for toning samples using LBG algorithm. The newborn crying samples composed from various crying baby having 0–6 months age. There are 27 babie's sound as training data, each of which represents the 7 hungry infant cries, 4 sleepy infant cries, 10 in...
Statistical pattern recognition has been considered to be one of the most successful approaches in the recent advancement of speech and speaker recognition. Out of all the approaches Hidden Markov Models, Gaussian mixture models and Vector Quantization has been considered to be one of the most successful techniques in regards to the performance of the speaker recognition systems. However the performance...
The performance of speaker identification systems has improved due to recent advances in speech processing techniques but there is still need of improvement in term of text-independent speaker identification and suitable modelling techniques for voice feature vectors. It becomes difficult for person to recognize a voice when an uncontrollable noise adds in to it. In this paper, feature vectors from...
In this work, we present a multimodal biometric system using face, speech and signature features which is robust to noise. Face recognition is done using subspace, principal component analysis (PCA) and linear discriminant analysis (LDA) techniques. Speaker recognition system is built using mel frequency cepstral coefficients (MFCC) for feature extraction and vector quantization (VQ) for pattern matching...
In this work, we present a multimodal biometric system using speech and signature features. Speaker recognition system is built using Mel frequency cepstral coefficients (MFCC) for feature extraction and vector quantization (VQ) for modeling. An offline signature recognition system is also built using vertical and horizontal projection profiles (VPP and HPP) and discrete cosine transform (DCT) for...
This work demonstrates the development of Keyword Spotting (KWS) system using Vowel Onset Point (VOP), Vector Quantization (VQ) and Hidden Markov Model(HMM) based techniques. The goal of KWS system is to spot the keywords present in the test speech signal, while neglecting rest of the words. In this work, first independent KWS systems will be developed using VOP, VQ and HMM techniques. Each of these...
Generally, the code excited linear predictive (CELP) coding is known as one of the best algorithms for bit rate between 4 kbps and 16 kbps. Recently, the algebraic CELP (ACELP) algorithm has been widely adopted in standard speech coders such as G.729 and Adaptive multi rate (AMR) and AMR Wide Band (AMR-WB).In order to improve the speech quality based on CELP algorithm, harmonic Pitch pre-emphasis...
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