• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.63-69
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• 2010

Today, Internet Telephony Services based on VoIP are gaining tremendous popularity for general user. Therefore a various demands of the user keep up increase, the most important requirements of these is voice security about telephony system. It is needed to ensure secret of voice call in a special situation. Due to the fact that many users can connect to the internet at the same time, VoIP can always be in a defenseless state by hackers. Therefore, in this paper, we have developed VPN IP-PBX for the voice security and measured conversation quality by adopting VPN IPsec based on SIP and using tunnel method in transmitting voice data to prevent eavesdrop of voice data. This VPN IP-PBX that is connected Soft-phone provide various optional services.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.8
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• pp.901-906
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• 2015

We presented a method for Vad(Voice Activity Detection) using Bi-level HMM. Conventional methods need to do an additional post processing or set rule-based delayed frames. To cope with the problem, we applied to VAD a Bi-level HMM that has an inserted state layer into a typical HMM. And we used posterior ratio of voice states to detect voice period. Considering MFCCs(: Mel-Frequency Cepstral Coefficients) as observation vectors, we performed some experiments with voice data of different SNRs and achieved satisfactory results compared with well-known methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.303-309
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• 2012

Energy expenditure values were estimated based on the voice signals and body activities. Voice signals and body activities were obtained using PVDF contact vibration sensor and 3-axis accelerometer, respectively. Vibration caused by voices, activity signals, and actual energy consumption were acquired using data acquisition system and gas analyzer. With the use of power values from the voice signals and weight as independent variables, R-square of 0.918 appeared to show the highest value. For activity outputs, use of signal vector magnitude, body mass index, height, and age as independent variables revealed to provide the highest correlation with actual energy expenditure. Estimation of energy expenditure based on voice and activity provides more accurate results than based on activity only.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.568-570
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• 2018

Currently, with rapid progress and supply of mobile communication technology, LTE(Long Term Evolution) technology is expanded and widely used to industrial and emergency communications beyond earlier smart-phone based service. In this paper, transmission performance of voice traffic, one of railway communication service based on LTE-R as an application field of LTE technology, is analyzed. This study is performed performance analysis with level of application service and consider effects of satisfaction level for users. Computer Simulation based on ns(Network Simulation)-3 is used for analysis and VoIP(Voice over Internet Protocol) specification is used for voice traffics. Results of this paper is used to implement LTE-R networks and develope application services over LTE-R network.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.26-30
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• 2019

This paper proposes a new voice activity detection (VAD) method which is based on SNR and non-intrusive speech intelligibility estimation. In the conventional SNR-based VAD methods, voice activity probability is obtained by estimating frame-wise SNR at each spectral component. However these methods lack performance in various noisy environments. We devise a hybrid VAD method that uses non-intrusive speech intelligibility estimation as well as SNR estimation, where the speech intelligibility score is estimated based on deep neural network. In order to train model parameters of deep neural network, we use MFCC vector and the intrusive speech intelligibility score, STOI (Short-Time Objective Intelligent Measure), as input and output, respectively. We developed speech presence measure to classify each noisy frame as voice or non-voice by calculating the weighted average of the estimated STOI value and the conventional SNR-based VAD value at each frame. Experimental results show that the proposed method has better performance than the conventional VAD method in various noisy environments, especially when the SNR is very low.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.862-865
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• 2002

VoIP was simply used to transfer voice call between IP host. VoIP provides efficiently end-to-end voice communication, however it needs to supply value-added services to users. This raper describes design of SIP communication for registering CPL.

• Phonetics and Speech Sciences
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• v.14 no.3
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• pp.77-86
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• 2022

In this study, we reported the validation results of the Korean Affective Voice Database (KAV DB), an affective voice database available for scientific and clinical use, comprising a total of 113 validated affective voice stimuli. The KAV DB includes audio-recordings of two actors (one male and one female), each uttering 10 semantically neutral sentences with the intention to convey six different affective states (happiness, anger, fear, sadness, surprise, and neutral). The database was organized into three separate voice stimulus sets in order to validate the KAV DB. Participants rated the stimuli on six rating scales corresponding to the six targeted affective states by using a 100 horizontal visual analog scale. The KAV DB showed high internal consistency for voice stimuli (Cronbach's α=.847). The database had high sensitivity (mean=82.8%) and specificity (mean=83.8%). The KAV DB is expected to be useful for both academic research and clinical purposes in the field of communication disorders. The KAV DB is available for download at https://kav-db.notion.site/KAV-DB-75 39a36abe2e414ebf4a50d80436b41a.

• 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.

• ETRI Journal
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• v.31 no.4
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• pp.451-453
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• 2009

This letter proposes the use of vowel sound detection for voice activity detection. Vowels have distinctive spectral peaks. These are likely to remain higher than their surroundings even after severe corruption. Therefore, by developing a method of detecting the spectral peaks of vowel sounds in corrupted signals, voice activity can be detected as well even in low signal-to-noise ratio (SNR) conditions. Experimental results indicate that the proposed algorithm performs reliably under various noise and low SNR conditions. This method is suitable for mobile environments where the characteristics of noise may not be known in advance.