• Title/Summary/Keyword: Real-time Masking Effect

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Fast Convolution Method Using Real-time Masking Effects in Sound Reverberator (잔향 생성기에서 실시간 마스킹 효과를 이용한 고속 컨벌루션 방법)

  • Shin, Min-Cheol;Wang, Se-Myung
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.18 no.2
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    • pp.231-237
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    • 2008
  • With the advent of sound field simulator, many sound fields have been reproduced by obtaining the impulse responses of specific acoustic spaces like famous concert hall, opera house. This sound field reproduction has been done by the linear convolution operation between the sound input signal and the impulse response of certain acoustic space. However, the conventional finite impulse response based linear convolution operation always makes real-time implementation of sound field generator impossible due to the large amount of computational burden. This paper introduces the fast convolution method using perceptual redundancy in the processed signals, input audio signal and room impulse response. Temporal and spectral real-time masking blocks are implemented in the proposed convolution structure. It reduces the computational burden of convolution methods for real-time implementation of a sound field generator. The conventional convolutions are compared with the proposed one in views of computational burden and sound quality. In the proposed method, a considerable reduction in the computational burden was realized with acceptable changes in sound quality.

On-line model compensation using noise masking effect for robust speech recognition (잡음 차폐를 이용한 온라인 모델 보상)

  • Jung Gue-Jun;Cho Hoon-Young;Oh Yung-Hwan
    • Proceedings of the KSPS conference
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    • 2003.05a
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    • pp.215-218
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    • 2003
  • In this paper we apply PMC (parallel model combination) to speech recognition system online. As a representative of model based noise compensation techniques, PMC compensates environmental mismatch by combining pretrained clean speech models and real-time estimated noise information. This is very effective approach for compensating extreme environmental mismatch but is inadequate to use in on-line system for heavy computational cost. To reduce the computational cost and to apply PMC online, we use a noise masking effect - the energy in a frequency band is dominated either by clean speech energy or by noise energy - in the process of model compensation. Experiments on artificially produced noisy speech data confirm that the proposed technique is fast and effective for the on-line model compensation.

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A Technique of Applying Embedded Sensors to Intuitive Adjustment of Image Filtering Effect in Smart Phone (스마트폰에서 이미지 필터링 효과의 직관적 조정을 위한 내장센서의 적용 기법)

  • Kim, Jiyeon;Kwon, Sukmin;Jung, Jongjin
    • Journal of Korea Multimedia Society
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    • v.18 no.8
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    • pp.960-967
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    • 2015
  • In this paper, we propose a user interface technique based on embedded sensors applying to apps in smart phone. Especially, we implement avata generation application using image filtering technique for photo image in smart phone. In the application, The embedded sensors are used as intuitive user interface to adjust the image filtering effect for making user satisfied effect in real time after the system produced the image filtering effect for avatar. This technique provides not a simple typed method of parameter values adjustment but a new intuitively emotional adjustment method in image filtering applications. The proposed technique can use sound values from embedded mike sensor for adjusting key values of sketch filter effect if the smart phone user produces sound. Similiarly the proposed technique can use coordinate values from embedded acceleration sensor for adjusting masking values of oil painting filter effect and use brightness values from embedded light sensor for adjusting masking values of sharp filter effect. Finally, we implement image filtering application and evaluate efficiency and effectiveness for the proposed technique.

Performance Evaluation of Monitoring System for Sargassum horneri Using GOCI-II: Focusing on the Results of Removing False Detection in the Yellow Sea and East China Sea (GOCI-II 기반 괭생이모자반 모니터링 시스템 성능 평가: 황해 및 동중국해 해역 오탐지 제거 결과를 중심으로)

  • Han-bit Lee;Ju-Eun Kim;Moon-Seon Kim;Dong-Su Kim;Seung-Hwan Min;Tae-Ho Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.6_2
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    • pp.1615-1633
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    • 2023
  • Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.