• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.799-800
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• 2006

This thesis implemented security systems of voice awareness which is higher accessible than existing security system using biological authentication system and is inexpensive in module of security device, and has an advantage in usability. Proposed the security systems of voice awareness implemented algorithm for characteristic extraction of inputted speaker's voice signal verification, and also implemented database of access control that is founded on extractible output. And a security system of voice awareness has a function of an authority of access control to system.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.137-140
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• 2003

In this paper, we propose a robust endpoint detection algorithm for speaker verification. Proposed algorithm uses energy and cepstral distance parameters, and it replaces the detected endpoints with endpoints of voiced speech, when the estimated signal-to-noise ratio (SNR) is low. Experimental results show that proposed algorithm is superior to energy-based endpoint detection algorithm.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.158-162
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• 2006

This paper presents a speaker recognition system intended for use in human-robot interaction. The proposed speaker recognition system can achieve significantly high performance in the Ubiquitous Robot Companion (URC) environment. The URC concept is a scenario in which a robot is connected to a server through a broadband connection allowing functions to be performed on the server side, thereby minimizing the stand-alone function significantly and reducing the robot client cost. Instead of giving a robot (client) on-board cognitive capabilities, the sensing and processing work are outsourced to a central computer (server) connected to the high-speed Internet, with only the moving capability provided by the robot. Our aim is to enhance human-robot interaction by increasing the performance of speaker recognition with multiple microphones on the robot side in adverse distant-talking environments. Our speaker recognizer provides the URC project with a basic interface for human-robot interaction.

• The Journal of the Acoustical Society of Korea
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• v.22 no.3
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• pp.182-187
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• 2003

In this thesis, we propose the algorithm to improve the performance of speaker verification that is mapping feature parameters by using RBF neural network. There is a big difference between wire vector region and wireless one which comes from the same speaker. For wire/wireless speakers model production, speaker verification system should distinguish the wire/wireless channel that based on speech recognition system. And the feature vector of untrained channel models is mapped to the feature vector(LPC Cepstrum) of trained channel model by using RBF neural network. As a simulation result, the proposed algorithm makes 0.6%∼10.5% performance improvement compared to conventional method such as cepstral mean subtraction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.739-743
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• 2006

In this paper, development of voice activated Universal Remote Control using the Neural Networks. A speaker dependent system is developed to operate for a single speaker. These systems are usually easier to develop, cheaper to buy and more accurate, but not as flexible as speaker adaptive or speaker independent systems. A speaker independent system is developed to operate for any speaker of a particular type (e.g. American English). These systems are the most difficult to develop, most expensive and accuracy is lower than speaker dependent systems. However, they are more flexible. A speaker adaptive system is developed to adapt its operation to the characteristics of new speakers. It's difficulty lies somewhere between speaker independent and speaker dependent systems. This paper is developed Speaker Adaptation using the Neural Networks.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1471-1479
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• 2008

In this paper, we propose a technique to improve Out-Of-Vocabulary(OOV) rejection algorithms in variable vocabulary recognition system which is much used in ASR(Automatic Speech Recognition). The rejection system can be classified into two categories by their implementation method, keyword spotting method and utterance verification method. The utterance verification method uses the likelihood ratio of each phoneme Viterbi score relative to anti-phoneme score for deciding OOV. In this paper, we add speaker verification system before utterance verification and calculate an speaker verification probability. The obtained speaker verification probability is applied for determining the proposed variable-confidence threshold. Using the proposed method, we achieve the significant performance improvement; CA(Correctly Accepted for keyword) 94.23%, CR(Correctly Rejected for out-of-vocabulary) 95.11% in office environment, and CA 91.14%, CR 92.74% in noisy environment.

• The Journal of the Acoustical Society of Korea
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• v.22 no.4E
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• pp.176-182
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• 2003

As the needs for wireless Internet service is increasing, the needs for secure m-commerce is also increasing. Conventional security techniques are reinforced by biometric security technique. This paper utilized the voice as biometric security techniques. We developed speaker verification system for m-commerce (mobile commerce) via wireless internet and wireless application protocol (WAP). We named this system the mVprotek. We implemented the system as client-server architecture. The clients are mobile phone simulator and personal digital assistant (PDA). The verification results are obtained by integrating the mVprotek system with SK Telecom's code dimension multiple access (CDMA) system. Utilizing f-ratio weighting and virtual cohort model normalization showed much better performance than conventional background model normalization technique.

• The Journal of the Acoustical Society of Korea
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• v.18 no.5
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• pp.12-20
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• 1999

In this paper, we compared speaker verification performance of the speech data collected in clean environment and in channel environment. For the improvement of the performance of speaker verification gathered in channel, we have studied on the efficient feature parameters in channel environment and on the preprocessing. Speech DB for experiment is consisted of Korean doublet of numbers, considering the text-prompted system. Speech features including LPCC(Linear Predictive Cepstral Coefficient), MFCC(Mel Frequency Cepstral Coefficient), PLP(Perceptually Linear Prediction), LSP(Line Spectrum Pair) are analyzed. Also, the preprocessing of filtering to remove channel noise is studied. To remove or compensate for the channel effect from the extracted features, cepstral weighting, CMS(Cepstral Mean Subtraction), RASTA(RelAtive SpecTrAl) are applied. Also by presenting the speech recognition performance on each features and the processing, we compared speech recognition performance and speaker verification performance. For the evaluation of the applied speech features and processing methods, HTK(HMM Tool Kit) 2.0 is used. Giving different threshold according to male or female speaker, we compare EER(Equal Error Rate) on the clean speech data and channel data. Our simulation results show that, removing low band and high band channel noise by applying band pass filter(150～3800Hz) in preprocessing procedure, and extracting MFCC from the filtered speech, the best speaker verification performance was achieved from the view point of EER measurement.

• The Journal of the Acoustical Society of Korea
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• v.19 no.8
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• pp.63-67
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• 2000

This paper deals with text-prompt speaker recognition based on dynamic time warping (DTW). The Genetic Algorithm was applied to the creation of reference patterns for suitable reflection of the speaker characteristics, one of the most important determinants in the fields of speaker recognition. In order to overcome the weakness of text-dependent and text-independent speaker recognition, the text-prompt type was suggested. Performed speaker identification and verification in close and open set respectively, hence the Genetic algorithm-based reference patterns had been proven to have better performance in both recognition rate and speed than that of conventional reference patterns.

• The Journal of the Acoustical Society of Korea
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• v.22 no.1
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• pp.42-47
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• 2003

This paper proposes the method to generate new test data using the sample shift of the start frame for SPRT(sequential probability ratio test) in speaker verification. The SPRT method is a effective algorithm that can reduce the test computational complexity. However, in making the decision procedure, SPRT can be executed on the assumption that the input samples are usually to be i.i.d. (Independent and Identically Distributed) samples from a probability density function (pdf), also it's not suitable method to apply for the short utterance. The proposed method can achieve SPRT regardless of the utterance length of the test data because it is method to generate the new test data through the sample shift of start frame. Also, the correlation property of data to be considered in the SPRT method can be effectively removed by employing the principal component analysis. Experimental results show that the proposed method increased the computational complexity of data for sample shift a little, but it has a good performance result more than a conventional method above the average 0.7% in EER (equal error rate).