[PDF] Top 20 SPEAKER RECOGNITION IN NOISY ENVIRONMENT
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SPEAKER RECOGNITION IN NOISY ENVIRONMENT
... Speaker recognition can be used to verify one’s identity when the interface favors the use of a telephone or ...education, speaker verification has already proven to be the most natural yet very ... See full document
6
Robust speaker recognition in presence of non trivial environmental noise (toward greater biometric security)
... Robust Speaker Recognition in presence of non-trivial environmental noise 57 features theory (MFT) to model the noise ...simulated noisy data of simple noise characteristics and missing feature ... See full document
248
Acoustic Feature Extraction and Optimized Neural Network based Classification for Speaker Recognition
... Automatic recognition related to the speakers are the process of identifying speech signal with the corresponding ...biometric recognition system ...types: speaker verification and identification. ... See full document
10
The third 'CHiME' speech separation and recognition challenge: Analysis and outcomes
... STR environment), ii) speakers talking in a quieter ‘confidential’ style on the BUS where it was often quiet and other passengers were sitting in close prox- ...in noisy environments and a consequent ... See full document
33
Speaker tracking with a microphone array using Kalman filtering
... Abstract. In this publication a method for tracking a speaker with acoustical information by means of a microphone array is presented. A sound source localization algorithm based on the time delays of arrival of ... See full document
5
SPEAKER RECOGNITION IN REVERBERANT CONDITIONS: A REVIEW
... viz. speaker specific information, the message expressed as a sequence of words or phrases, information about the acoustic environment in which the speech is re-corded and transmitted, ...etc. ... See full document
10
Speech And Speaker Recognition: A Review
... 7. T OOLS FOR A UTOMATIC S PEECH R ECOGNITION Hidden Markov Toolkit (HTK): It is written in ANSI C and is mainly used for building and manipulating hidden markov models. Initially it is build for English language and ... See full document
7
Speech recognition in reverberant and noisy environments employing multiple feature extractors and i vector speaker adaptation
... triphone states and 40K Gaussians. The DNN is also trained on the LDA + STC + FMLLR [20, 37–40] trans- formed MFCC features. These features are globally nor- malized to have zero mean and unit variance. The input to the ... See full document
13
Speaker Independent Speech Recognition of Isolated Words in Room Environment
... After analyzing the ‘2 nd formant values’ of male and female speakers for the utterances ‘Go’, ‘Right’, ‘Left’ and ‘Halt’, it is seen that for a specific person like Male 2, values of 2nd formant are different for ... See full document
7
Robust Speaker Recognition for Large-scale data using PFA Dimensionality Reduction
... real-world speaker recognition systems is ever-increasing, large population speaker recognition systems pose challenges such as large training time, vast memory requirements and poor response ... See full document
11
Characterization of speaker recognition in noisy channels
... Speaker recognition is becoming more ubiquitous as reliance on biometrics for security and convenience ...increases. Speaker recognition systems have been used in both speaker ... See full document
97
Biometrics Security Technology with Speaker Recognition
... voice recognition in real ...voice recognition system in MATLAB ...voice recognition in security systems an accurate algorithm is required with minimum error ...voice recognition has many ... See full document
5
Speaker Recognition: A Survey
... adding noisy data to UBM and i-vector training have shown very small ...only noisy training data added into the LDA/PLDA ...i-vector speaker verification in the presence of high inter-session ...the ... See full document
9
SPEAKER RECOGNITION USING GMM
... text-independent speaker recognition ...of speaker specific training ...Mixture speaker model was specifically evaluated for identification tasks using short duration utterances from ... See full document
9
SCAN : learning speaker identity from noisy sensor data
... Limitations of Baseline Approach: The above method addresses the identification problem in two isolated steps: context observa- tions are firstly clustered and then matched to identities by min- imizing the combinatorial ... See full document
13
Speaker Identification in Network Environment
... a speaker in a networking environment. Automatic speaker identification is a fundamental task in speech ...intranet environment involves recording huge volume of data or frames of ...the ... See full document
7
Improved Hidden Markov Modeling for Speaker Independent Continuous Speech Recognition
... Improved Hidden Markov Modeling for Speaker Independent Continuous Speech Recognition Improved Hidden Markov Modeling for Speaker Independent Continuous Speech Recognition Xuedong Huang, Fil Alleva, S[.] ... See full document
5
Topic and Speaker Identification via Large Vocabulary Continuous Speech Recognition
... Topic and Speaker Identification via Large Vocabulary Continuous Speech Recognition Topic and Speaker Identification via Large Vocabulary Continuous Speech Recognition Barbara Peskin, Larry Gillick, Y[.] ... See full document
6
Studies on automatic speaker recognition
... Ther efore if the mism atch betw een the real distr ibuti on of a spea ker's data and the estim ated distr ibuti on with GM mod el form causes reco gniti on error s, thos e error s occu [r] ... See full document
146
Speaker recognition with hybrid features from a deep belief network
... For speaker recognition task, a first attempt on the use of RBMs has been reported by ...a speaker verification ...based speaker verification 3 ... See full document
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