• The Journal of the Acoustical Society of Korea
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• 제31권5호
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• pp.332-339
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• 2012

Beamspace transform algorithm transforms spatial-domain data - such as x, y, z dimension - into incidence-angle-domain data, which is called beamspace-domain data. The beamspace transform method is generally used in source localization and tracking, and adaptive beamforming problem. When the beamspace transform method is used in multichannel audio source separation, the inverse beamspace transform is also important because the source image have to be reconstructed. This paper studies the beamspace transform and inverse transform algorithms for multichannel audio source separation system, especially for the beamspace-domain multichannel NMF algorithm.

• Journal of Advanced Navigation Technology
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• 제16권4호
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• pp.649-656
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• 2012

The Global Positioning System (GPS) is widely utilized for commercial and military applications to estimate the location of the user or object. The GPS suffers from various intentional or unintentional interferers and it requires estimating the accurate angle-of-arrival (AOA) of the GPS signal to suppress interference signals and to efficiently detect GPS data. Since the power of GPS signal is very low comparing with the noise and interference signals, it is extremely difficult to estimate GPS AOA before despreading. Although AOA of GPS signal is usually estimated after despreading, it requires choosing the GPS AOA among results of AOA estimation because they include AOAs of interference and GPS signals when existing high-power interferers. In this paper, we propose the efficient choosing algorithm of the GPS signal among the estimated AOAs. The proposed algorithm compares the estimated results before despreading and after despreading for choosing AOA of GPS signal. Computer simulation examples are presented to illustrate the performance of the proposed algorithm.

• The Journal of the Acoustical Society of Korea
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• 제40권5호
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• pp.439-451
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• 2021

We propose a deep learning-based beamformer combined with spectral subtraction for continuous speech recognition operating in noisy environments. Conventional beamforming systems were mostly evaluated by using pre-segmented audio signals which were typically generated by mixing speech and noise continuously on a computer. However, since speech utterances are sparsely uttered along the time axis in real environments, conventional beamforming systems degrade in case when noise-only signals without speech are input. To alleviate this drawback, we combine online beamforming algorithm and spectral subtraction. We construct a Continuous Speech Enhancement (CSE) evaluation set to evaluate the online beamforming algorithm in noisy environments. The evaluation set is built by mixing sparsely-occurring speech utterances of the CHiME3 evaluation set and continuously-played CHiME3 background noise and background music of MUSDB. Using a Kaldi-based toolkit and Google web speech recognizer as a speech recognition back-end, we confirm that the proposed online beamforming algorithm with spectral subtraction shows better performance than the baseline online algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• 제49권9호
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• pp.155-163
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• 2012

The geometrical and electrical errors of array sensors can severely degrade the performance of array sensor system. Various calibration techniques are developed to alleviate this problem. In this paper, two different calibration methods with respect to location, gain and phase of array sensors are presented. One method applies the first-order Taylor series expansion to approximate the true steering vector from the nominal values of array sensors. Then a set of equations is formed by using the null characteristics of the MUSIC spectrum to estimate errors of location, gain and phase of array sensors. Another method estimates these errors based on the data covariance matrix of pilot sources. From the simulations, it is demonstrated that two calibration algorithms calibrated an array system successfully. In addition to that, Fistas and Manikas's algorithm is more robust against noise than Ng and Lie's one when SNR is from 10dB to 50dB.

• Journal of Advanced Navigation Technology
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• 제6권3호
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• pp.181-187
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• 2002

In this paper, we propose a resolution enhancement method for estimating direction-of-arrival(DOA) of narrowband incoherent signals incident on a general array. The resolution of DOA algorithm is dependent on the aperture size of antenna array. But it is very impractical to increase the physical size of antenna array in real environment. We propose the method that improves resolution performance by virtually expanding the sensor spacing of original antenna array and then averaging the spatial spectrum of each virtual array which has a different aperture size. Superior resolution capabilities achieved with this method are shown by simulation results in comparison with the standard MUSIC for incoherent signals incident on a uniform circular array.

• Journal of the Institute of Electronics Engineers of Korea SP
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• 제42권3호
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• pp.115-120
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• 2005

In this paper, we propose a new robust content-based musical genre classification algorithm using multi-feature clustering(MFC) method. In contrast to previous works, this paper focuses on two practical issues of the system dependency problem on different input query patterns(or portions) and input query lengths which causes serious uncertainty of the system performance. In order to solve these problems, a new approach called multi-feature clustering(MFC) based on k-means clustering is proposed. To verify the performance of the proposed method, several excerpts with variable duration were extracted from every other position in a queried music file. Effectiveness of the system with MFC and without MFC is compared in terms of the classification accuracy. It is demonstrated that the use of MFC significantly improves the system stability of musical genre classification performance with higher accuracy rate.

• Journal of Internet Computing and Services
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• 제8권1호
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• pp.15-23
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• 2007

Wireless LAN (IEEE 802.11) uses traditional TCP for reliable data transmission, But it brings the unintentional packet loss which is not congestion loss caused by handoff, interference, and fading in wireless LAN. In wireless LAN, TCP experiences performance degradation because it consumes that the cause of packet loss is congestion, and it decrease the sending rate by activating congestion control algorithm. This paper analyzes that correlation of throughput and buffer size for wireless buffer tuning. We find MBT (Maximum Buffer Threshold) which does not increase the throughput through the analysis, For calculation of MBT, we experiment the throughput by using high volume music data which is creased by real-time performance of piano. The experiment results is shown that buffer tuing based on MBT shows 20.3%, 21.4%, and 45.4% throughput improvement under 5ms RTT, 10ms RTT, and 20ms RTT, respectively, comparing with the throughput of operation system default buffer size, In addition, we describe that The setting of TCP buffer size by exceeding MBT does not have an effect on the performance of TCP.

• Journal of the Institute of Electronics Engineers of Korea CI
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• 제43권5호
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• pp.48-56
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• 2006

In this paper, we proposed the high quality audio watermarking algorithm using MDCT/IMDCT (Modified DCT/Inverse Modified DCT) with psychoacoustic model. Generally, a digital audio watermark is embedding the frequency domain after frequency transform of the digital audio data but the digital audio quality is affected by watermarking. In our scheme, the digital audio data is spread with PN((Pseudo Noise) code and then audio watermark is embedded in MDCT processing that refers psychoacoustic model. In MDCT processing, according to the shape of filter bank output, the block switching selects a window sequence that has 256, 1,024 or 2,048 points interval for high quality audio. The author confirm that when watermark weight ${\alpha}$ is 2.5 below, the detection ratio of watermark is a satisfied to SDMI's(Secure Digital Music Initiative) recommendation 50% above and SM is $50{\sim}68dB$ range with mainly 4 kind of attacks(Compression, Cropping, FFT and Echo).

• The Journal of the Korea institute of electronic communication sciences
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• 제13권6호
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• pp.1207-1212
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• 2018

The signal intelligence (SIGINT) technology is actively used for collecting various data, in a number of fields, including a military industry. In order to collect the signal information and data and to transmit/receive the collected data efficiently, the accurate angle-of-arrival (AOA) information is required and communication disturbance from the interference or jamming signal should be minimized. In this paper, we present the structure of an adaptive beam-forming satellite system based on the planar array antenna, for collecting and transmitting/receiving the signal information and data efficiently. The presented adaptive beam-forming system consists of an antenna in the form of a planar array, an AOA estimator based on the Multiple Signal Classification (MUSIC) algorithm, an adaptive Minimum Variance Distortionless Response (MVDR) interference canceler, a signal processing and D/B unit, and a transmission beamformer based on Minimum mean Square Error (MMSE). In addition, through the computer simulation, we evaluate and analyze the performance of the proposed system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• 제14권3호
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• pp.215-222
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• 2021

As the importance of human-computer interaction (Human Computer Interface) technology grows and research on HCI is progressing, it is inferred about the research emotion inference or the computer reaction according to the user's intention, not the computer reaction by the standard input of the user. Stress is an unavoidable result of modern human civilization, and it is a complex phenomenon, and depending on whether or not there is control, human activity ability can be seriously changed. In this paper, we propose an intelligent emotional recommendation system using music as a way to relieve stress after measuring heart rate variability (HRV) and acceleration photoplethymogram (APG) increased through stress as part of human-computer interaction. The differential evolution algorithm was used to extract reliable data by acquiring and recognizing the user's biometric information, that is, the stress index, and emotional inference was made through the semantic web based on the obtained stress index step by step. In addition, by searching and recommending a music list that matches the stress index and changes in emotion, an emotional recommendation system suitable for the user's biometric information was implemented as an application.