• Journal of Industrial Technology
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• v.33 no.A
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• pp.55-60
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• 2013

In this paper, we proposed an efficient method for implementing a voice recognition elevator. Unlike the existing ones, the proposed system is based on the bluetooth communication and smartphones equipped with the google speech recognition software, which makes it possible that the speech recognition capability can be added to the previously installed elevators. In order to improve the recognition accuracy, instead of using the result of the google recognizer, we built a web server where the user data are accumulated and they are used for recognition error correction.

• Knowledge Management Research
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• v.19 no.1
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• pp.147-174
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• 2018

Recently, firms have been putting forth significant efforts to fulfill various demands and high expectations of customers. The role and importance of customer centers as a direct contact point for customer relationship management are more emphasized than previously. A customer center draws attention as a new alternative to secure corporate competitiveness as it contributes to sales increase, being in a position to satisfy customers' needs by ensuring customers' access to information. A customer center is an aggregation of various information and communication technologies. In particular, a voice recognition/analysis technology based on big data can elaborate customer services further, enhance customer satisfaction, and trigger constant interactions with customers. A customer center can be transformed to a hub of customer knowledge and the embodiment of business intelligence in the front line of business. This article is a case study on how the customer center of the K life insurance company regarding customer center operation collects and analyzes customer information and how it has established its voice recognition/analysis system based on big data to improve customer experience management. Factors affecting the successful introduction and implementation of voice recognition/analysis system to a firm, are examined.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.55-60
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• 2021

As the smart factory progresses, the use of automation facilities and robots is increasing. Also, with the development of IT technology, the utilization of the system using voice recognition is also increasing. Voice recognition technology is a technology that stands out in smart home and various IoT technologies, but it is difficult to apply to factories due to the specificity of factories. Therefore, in this study, a method to control an industrial articulated robot was designed using voice recognition technology that considers the situation at the manufacturing site. It was confirmed that the robot could be controlled through network protocol and command conversion after receiving voice commands for robot operation through mobile.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.611-614
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• 2001

Voice is one of the most efficient communication media and it includes several kinds of factors about speaker, context emotion and so on. Human emotion is expressed is expressed in the speech, the gesture, the physiological phenomena(the breath, the beating of the pulse, etc). In this paper, the emotion recognition method model using neuro-fuzzy in order to have cognizance of emotion from voice signal is presented and simulated.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1089-1094
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• 2022

In this paper, a human coexistence-type companion robot that can communicate with people in daily life and alleviate the gap in care personnel was studied. Based on the voice recognition module, servo motor, and Arduino board, a companion robot equipped with a robot arm control function using voice recognition, a position movement function using RC cars, and a voice recognition function was tested and manufactured. As a result of the experiment, the speech recognition experiment according to distance showed the optimal recognition rate at a distance of 5 to 30 cm, and the speech recognition experiment according to gender showed a higher recognition rate in the first tone, monotonous tone. Through the evaluation results of these motion experiments, it was confirmed that a companion robot could be made.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.175-179
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• 2011

In this paper, we propose the MA(Model Adaption) HMM that to use speech enhancement and feature compensation. Normally voice reference data is not consider for real noise data. This method is not to use estimated noise but we use real life environment noise data. And we applied this contaminated data for recognition reference model that suitable for noise environment. MAHMM is combined with surround noise when generating reference patten. We improved voice recognition rate at mobile environment to use MAHMM.

• Journal of the Ergonomics Society of Korea
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• v.10 no.1
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• pp.3-10
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• 1991

The teach pendant and keyboard have been used as an input device of control command in human-robot sustem. But, many problems occur in case that the usef is a novice. So, speech recognition system is required to communicate between a human and the robot. In this study, Korean voice commands, eitht robot commands, and ten digits based on the broad phonetic analysis are described. Applying broad phonetic analysis, phonemes of voice commands are divided into phoneme groups, such as plosive, fricative, affricative, nasal, and glide sound, having similar features. And then, the feature parameters and their ranges to detect phoneme groups are found by minimax method. Classification rules are consisted of combination of the feature parameters, such as zero corssing rate(ZCR), log engery(LE), up and down(UD), formant frequency, and their ranges. Voice commands were recognized by the classification rules. The recognition rate was over 90 percent in this experiment. Also, this experiment showed that the recognition rate about digits was better than that about robot commands.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.83-86
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• 2002

This paper intends to provide convenience to the disabled, losing the use of their limbs, through voice recognition technology. The voice recognition part of this system recognizes voice by DTW (Dynamic Time Warping) Which is most Widely used in Speaker dependent system. Specially, S/N rate was improved through Wiener filter in the pre-treatment phase while considering real environmental conditions; the result values of 12th order feature pattern per frame are extracted by DTW algorithm using LPC and Cepsturm in feature extraction process. Furthermore, miniaturization is pursued using TMS320C32, 71's the floating-point DSP, for the hardware part. Currently, 90% of hardware porting has been completed, but we can confirm that the recognition rate was 96% as a result of performing the DTW algorithm in PC.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.176-181
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• 2004

This paper introduces a Web site login system that uses user's native voice to improve the bother of remembering the ID and password in order to login the Web site. The DTW method that applies fuzzy inference is used as the speaker recognition algorithm. We get the ACC(Average Cepstrum Coefficient) membership function by each degree, by using the LPC that models the vocal chords, to block the recorded voice that is problem for the speaker recognition. We infer the existence of the recorded voice by setting on the basis of the number of zeros that is the value of the ACC membership function, and on the basis of the average value of the ACC membership function. We experiment the six Web sites for the six subjects and get the result that protects the recorded voice about 98% that is recorded by the digital recorder.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.346-353
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• 2021

In this proposal, we aim to enhance the security of systems accounts by improving the authentication techniques. We mainly intend to enhance the accuracy of the one-time passwords via including voice biometric and recognition techniques. The recognition will be performed on the server to avoid redirecting voice signatures by hackers. Further, to enhance the privacy of data and to ensure that the active user is legitimate, we propose to periodically update the activated sessions using a user-selected biometric factor. Finally, we recommend adding a pre-transaction re-authentication which will guarantee enhanced security for sensitive operations. The main novelty of this proposal is the use of the voice factor in the verification of the one-time password and the various levels of authentications for a full-security guarantee. The improvement provided by this proposal is mainly designed for sensitive applications. From conducted simulations, findings prove the efficiency of the proposed scheme in reducing the probability of hacking users' sessions.