[PDF] Top 20 Speaker Identification System based on PLP Coefficients and Artificial Neural Network

... 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

... the speaker recognition rate to some ...for speaker recognition because of its advantages over the other features and seems difficult to beat in practice ...a speaker model is trained and stored into ... See full document

... This paper has presented a new PI method by using the BV regions of retinal fundus images. In this work a number of challenges were encountered during implementation phase to implement it efficiently retinal scanners are ... See full document

... each speaker, 5 samples are taken for feature extraction and ...the network is of size 200 × 65 for a cluster size of ...the system for various clusters are shown in ...this system is ... See full document

... the system identification. An online maximum-likelihood based identification algorithm is developed for the air conditioner ...estimated system it was reliable for the future study ... See full document

... [19]. Speaker recognition can be classified into two parts in term of the data which are text-dependent and ...builds based on the one or some specific phrases that the speaker says such as password, ... See full document

... on neural networks in on-line fault detection processes has been developed during the few last ...backpropagation neural network for vibration parameters prediction of a rotating mechanical ... See full document

... Biometrics Identification is the recent used technology used authenticate the person's ...Biometric identification has eventually a much broader relevance as computer interface becomes more ...Biometrics ... See full document

... categorize based on its range classification and every products testing 50 ...a system that can identify, sort and separate the ...the system will not be covered in this ... See full document

... automatic identification without human expertise. The method is based on the use of Multi Layer Perceptron (MLP) for analysis of specific types of microscopic wear ... See full document

... language identification system. Based on the information extracted from the speech signal, it can have three different recognition systems itself: Speaker Recognition, Language Recognition and ... See full document

... recognition system with using Artificial Neural Network (ANN) that can recognize the type of image based on the features extracted from the choose ...of neural network. ... See full document

... of neural network models for the prediction of water resources ...the Artificial Neural Network-Geostatic methodology for spatiotemporal prediction of groundwater levels in a coastal ... See full document

... Immune System (HIS) which is robust, decentralized, error tolerant, and adaptive in ...the Artificial Immune System appears to be precisely tuned to the problem of detecting and eliminating ... See full document

... and Neural network approach is automatic credit card fraud detection system and type of artificial intelligence programming which is based on variety of methods including machine ... See full document

... positions) and ‘3s.45u’ dataset (‘3s.15u’ dataset × 3 posi- tions). From Table 6, the use of 15 pairs of utterances as NN training data (‘15u’) seems enough for our method to perform well. So, one possibility that may ... See full document

... The variability of the speech signal caused by different factors like speaker identity, gender, transmission channel, utterance length, session or speaking style make this task difficult. That’s why compensation ... See full document

... model is simpler than LDA model. The high number of PCs in LDA model can explain the differences between the tea varieties, but too high a number of PCs might include ‘specific information’ in the calibrating model, and ... See full document

... In the spectral domain, two pass effect is used to eliminate the background noise. An initial pass is implemented through the noise and this is obtained via signal via the speech. The FFT is computed for all frequency ... See full document

... designing Artificial Neural Network modeling system which will be used to determine and recognize the pattern in predicting the villages becoming the priority of installation of BTS USO for ... See full document