[PDF] Top 20 Bi-level Speaker Identification System: Impac...

... of speaker recognition, there are still many problems for which solutions have to be ...Utterance Speaker Recognition ...the speaker can be useful to deal a new approach for speaker ... See full document

... security system of controlling the access to secure data or information from being accessed by ...(2009) speaker recognition is the process of automatically recognizing the speaker voice according to ... See full document

... 1) Artificial Neural Network (ANN): The most elementary unit of a neural system is a neuron in both biological and artificial networks. Synapses correspond to the connections between neurons and are responsible ... See full document

... multilingual speaker recognition using neural networks with the back prop- agation ...tilingual speaker recognition system for eight Indian languages (Hindi, English, Assami, Telugu, Punjabi, ... See full document

... [7]. Speaker identification has recently become an important research and development ...[4]. Speaker identification can be classified into two types, based on ...for identification, ... See full document

... Md. Rabiul Islam was born in Rajshahi, Bangladesh, on December 26, 1981. He received his B.Sc. degree in Computer Science & Engineering and M.Sc. degrees in Electrical & Electronic Engineering in 2004, 2008, ... See full document

... the identification and localization were achieved simultaneously for mobile speakers depend on binaural signals from the robot in noisy and echoic ...interaural level (ILD) was used to implement it, the ... See full document

... For a small number of neurons (5 to 10) in the hidden layer we observed large MSE, solow accuracy. The MLP generalize poorly. After ~25 neurons, MSE came back to the levels of a system with only 5 neurons in the ... See full document

... Our system is a deep neural network consisting of a bidirectional Gated Recurrent Unit (GRU) network at the upper level, and a Deep Residual Network (ResNet) at the lower level (Figure ...our ... See full document

... Among above feature extraction methods the mostly used ones are the MFCC and LPCC. Traditional MFCC coefficient is affected by noise equivalently in MFCC feature vector. In practical, each coefficient is affected ... See full document

... nonlinear system identification namely (NARXENN) was adopted in first stage of this survey to model the flexible dynamics of wiper blade with acquired experimental ...wiper system extracted from ... See full document

... difference hybrid pattern classification approach for text independent speaker identification.. system; in these approaches, we combined a hybrid decision tree, GMM and VQ model.[r] ... See full document

... An important finding in our study is that GFCC features outperform conventional MFCC features under noisy conditions. We have conducted an in-depth study on the noise robustness of GFCC and MFCC features. Our experiments ... See full document

... 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

... , Speaker identification using mel-frequency cepstrul coefficients, 3rd International Conference on Electrical & Computer Engineering ICECE 2004, 28-30 December 2004, Dhaka, Bangladesh ISBN ... See full document

... Dr. H. B. Kekre has received B.E. (Hons.) in Telecomm. Engg. from Jabalpur University in 1958, M.Tech (Industrial Electronics) from IIT Bombay in 1960, M.S.Engg. (Electrical Engg.) from University of Ottawa in 1965 and ... See full document

... text-independent speaker identi- fication results described, based on average performance of typical ...ond system uses very noisy data from military radios and microphones with 30 seconds of training data ... See full document

... of speaker recognition have been conducted for more than five decades, and this field is still an active area of speech signal processing (Furui, 2005, Nengheng, ...in speaker recognition has used a ... See full document

... Artificial Neural Networks (ANNs) have been investigated for many years in automatic speech/speaker recognition. These ANNs consists of many neurons divided in two or more layers. These neurons are non-linear ... See full document

... These results indicate that even though there is some discrimination using the MER, it would become impossible to have close to a 99% accuracy rate in the open-set case. The open-set case will be the most important case ... See full document