• Journal of Platform Technology
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• v.8 no.4
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• pp.20-28
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• 2020

In this paper, a voice, object, and optical character recognition platform including voice recognition-based smart wearable devices, smart devices, and web AI servers was proposed as an appropriate technology to help the visually impaired to live independently by learning the life cycle of the visually impaired in advance. The wearable device for the visually impaired was designed and manufactured with a reverse neckband structure to increase the convenience of wearing and the efficiency of object recognition. And the high-sensitivity small microphone and speaker attached to the wearable device was configured to support the voice recognition interface function consisting of the app of the smart device linked to the wearable device. From experimental results, the voice, object, and optical character recognition service used open source and Google APIs in the web AI server, and it was confirmed that the accuracy of voice, object and optical character recognition of the service platform achieved an average of 90% or more.

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.132-140
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• 2023

In this paper, we propose a method for performance enhancement of speech declipping using clipping detector. Clipping occurs when the input speech level exceeds the dynamic range of microphone, and it significantly degrades the speech quality. Recently, many methods for high-performance speech declipping based on machine learning have been developed. However, they often deteriorate the speech signal because of degradation in signal reconstruction process when the degree of clipping is not high. To solve this problem, we propose a new approach that combines the declipping network and clipping detector, which enables a selective declipping operation depending on the clipping level and provides high-quality speech in all clipping levels. We measured the declipping performance using various metrics and confirmed that the proposed method improves the average performance over all clipping levels, compared with the conventional methods, and greatly improves the performance when the clipping distortion is small.

• Journal of Animal Science and Technology
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• v.51 no.5
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• pp.421-426
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• 2009

This study was conducted to clarify the characteristics of vocalization of laying hen related with space in battery cage. The size of cages were classified into control (0.30 m ${\times}$ 0.14 m ${\times}$ 0.55 m, length ${\times}$ width ${\times}$ height), small (0.21 m ${\times}$ 0.14 m ${\times}$ 0.55 m) and large (0.30 m ${\times}$ 0.30 m ${\times}$ 0.55 m) size. Vocalization of 16 individuals of laying hen in each group of Hy-Line Brown (80 week old) were recorded 3 hours per day (10:00am~11:00am, 3:00pm~4:00pm and 7:00pm~8:00pm) using digital recorder and microphone during October 2008 and February 2009. Characteristics of frequency, intensity and duration of vocalization were analyzed by GLM (general linear model) and Duncan's multi-test. There were differences in basic and maximum frequency, and intensity based on analysis of spectrogram and spectrum among different cage sizes. Vocalization of laying hen would be one of the indicators to understand the stress caused by rearing space in batter cage.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.3
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• pp.304-315
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• 2001

In this paper, we peformed the real-time implementation of AMR(Adaptive Multi-Rate) speech coding algorithm which is adopted for IMT-2000 service using TMS320C6201, i.e., a Texas Instrument´s fixed-point DSP. With the ANSI C source code released from ETSI, optimization is performed to make it run in real-time with memory as small as possible using the C compiler and assembly language. Implemented AMR speech codec has the size of 32.06 kWords program memory, 9.75 kWords data RAM memory, and 19.89 kWords data ROM memory. And, The time required for processing one frame of 20 ms length speech data is about 4.38 ms, and it is short enough for real-time operation. It is verified that the decoded result of the implemented speech codec on the DSP is identical with the PC simulation result using ANSI C code for test sequences. Also, actual sound input/output test using microphone and speaker demonstrates its proper real-time operation without distortions or delays.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.617-626
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• 2023

This study aims to investigate the preferred sound level of water sound for various levels of open-plan-office noise regarding soundscape quality and speech privacy. And assessment of the work efficiency of the water sound. For the laboratory experiment, office noise was recorded using a binaural microphone in a real open-plan office. For the assessment of the soundscape quality and speech privacy, Overall Soundscape Quality (OSQ) and Listening Difficulty (LD) were evaluated under three different sound levels (55 dBA, 60 dBA, and 65 dBA) and five different signal-to-noise ratios (SNR -10 dB, -5 dB, 0 dB, +5 dB, and +10 dB). After the evaluation, the preferred SNR was proposed according to OSQ and LD. For the assessment of to work efficiency of water sound, this study evaluated the cognitive performance of both of the condition noise only and combine the water sound with office noise. The results showed that LD increased as the water sound level increased, but OSQ decreased. When the water sound level was more than the office noise level, the OSQ decreased from noise only. Therefore, considering OSQ and LD, the preferred SNR of water sound was -5 dB for all noise levels. At the preferred level of water sound, the cognitive performance results were shown to decrease at 55 dBA compared to noise only, but at 60 dBA and 65 dBA combine the water sound results were increased than the noise only.