[PDF] Top 20 Speaker Recognition using Gaussian Mixture Model

Speaker Recognition using Gaussian Mixture Model

... The speaker recognition system was built using Alize- Liral ...female speaker. The universal back ground(UBM) model was modeled using all the speech ...25 speaker‟s speech ... See full document

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Speaker Recognition by Combining Gaussian Mixture Model (GMM) Spectral Representation and Phase Information

... text-independent speaker recognition, Gaussian mixture model (GMM) is known for its effectiveness and scalability in modeling the spectral distribution of ...conventional speaker ... See full document

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Text Independent Automatic Speaker Recognition System Using Mel Frequency Cepstrum Coefficient and Gaussian Mixture Models

... automatic speaker recognition (ASR) system, based on Mel-Frequency Cepstrum Coefficients (MFCC) and Gaussian Mixture Models (GMM), in or- der to develop a security control access ...improved ... See full document

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A SPEAKER RECOGNITION SYSTEM USING GAUSSIAN MIXTURE MODEL

... Abstract—Automatic speaker recognition system identifies a person from the information contained in the speech ...biometric recognition and are being used in applications like teleconferencing, ... See full document

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INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES MANAGEMENT TEXT-INDEPENDENT SPEAKER RECOGNITION USING GAUSSIAN MIXTURE MODEL Mamta Saraswat Tiwari

... when using a single threshold for ...different speaker models, again resulting in better performance when using speaker-independent thresholds as in the NIST ...estimating speaker and ... See full document

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EMOTION DETECTION IN SPEECH USING GAUSSIAN MIXTURE MODEL

... A Gaussian Mixture Model (GMM) is a parametric probability density function represented as a weighted sum of Gaussian component ...parametric model of the probability distribution of ... See full document

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Speech based Emotion Recognition with Gaussian Mixture Model

... by using the features like strength of excitation, characteristics of glottal volume velocity waveform, shapes of the glottal pulse, characteristics of open and closed phases of glottis and so ...message, ... See full document

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Speaker identification using distributed vector quantization and Gaussian mixture models

... Speaker recognition can be based on text-dependent or text-independent utterances, depending on whether the recognition process is constrained to a pre-defined text or not (Gish and Schmidt, ...the ... See full document

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Text Independent Speaker Modeling and Identification Based On MFCC Features

... automatic speaker recognition technology, with an emphasis on text- independent ...recognition. Speaker recognition has been studied actively for several ...automatic speaker ... See full document

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A Framework for Improving the Interpersonal Relationship of the Elderly with Mild Cognitive Impairment by Using Speaker Recognition and Social Network Platforms

... the speaker recognition technique and association functionality of social network ...the speaker recognition units based on the Gaussian Mixture Model (GMM) and ... See full document

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An Overview on Speaker Identification Technologies

... proposed Gaussian mixture modeling (GMM) classifier for speaker recognition task ...in speaker recognition. The GMM needs sufficient data to model the speaker, and ... See full document

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SPEAKER RECOGNITION USING GMM

... (Speaker Recognition [4] Project) is to implement a recognizer using Matlab which can identify a person by processing his/her ...by using the process of feature extraction using ...by ... See full document

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An Emotion Recognition System based on Right Truncated Gaussian Mixture Model

... emotion recognition system based on the Truncated Gaussian mixture model ...emotion recognition database In the recent past, many models have been listed in the literature based on the ... See full document

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Multilingual Blended Speech Recognition using Gaussian Mixture Model for Non-Dictionary Words

... estimated using the well known Baum-Welch (BW) algorithm [Baum et ...For model, in our English ASR framework, there are just 39 telephones, however up to 393 = 59319 special ...hand Gaussian blends ... See full document

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A Review on Text-Independent Speaker Verification Techniques in Realistic World

... (ML) level. The basic idea is to adapt the UBM to each context-dependent phone rather than to each speaker. The context-dependent phones are not an unstructured collection of phones but are related via a tree ... See full document

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Low-dimensional representation of Gaussian mixture model supervector for language recognition

... Table 2 shows the results of the combination of the MMI system, the GMM-SVM system, the TV system, and the MTV system, in terms of EER and minDCF. As we know, system fusion can exploit partial error decorr- elations ... See full document

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Face Recognition Algorithm based on Doubly Truncated Gaussian Mixture Model using DCT Coefficients

... these model based face recognition systems the feature vector is characterized through a probability ...a Gaussian mixture model. The Gaussian mixture model has ... See full document

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EMOTION RECOGNITION FROM SPEECH WITH GAUSSIAN MIXTURE MODELS AND VIA BOOSTED GMM

... emotion recognition from the speech signal has been prevailing topic of ...emotion recognition is an important issue which affects the human machine ...Automatic recognition of human emotion in ... See full document

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Comprehensive design and development of time efficiency speaker recognition model from front end to back end

... mixture model based speaker identification on increasing speaker data from 10-50.. Thus, our implementation[r] ... See full document

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Evaluation of Phonetic System for Speech Recognition on Smartphone

... Speech recognition is one of the most significant application areas of digital signal ...Speech recognition systems have divided into two levels, the first level of ASR system is the feature extraction ... See full document

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