• The Journal of the Acoustical Society of Korea
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• v.22 no.3
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• pp.169-174
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• 2003

A novel subspace speech enhancement using subband whitening filter is proposed. Previous subspace speech enhancement method either assumes additive white noise or uses whitening filter as a pre-processing for colored noise. The proposed method tries to minimize the signal distortion while reducing residual noise by processing the signal using subband whitening filter. By incorporating the notion of subband whitening filter, spectral resolution in Karhunen-Loeve(KL) domain is improved with the negligible additional computational load. The proposed method outperforms both the subspace method suggested by Ephraim and the spectral subtraction suggested by Boll in terms of segmental signal-to-noise ratio (SNRseg) and perceptual evaluation of speech quality (PESQ).

• The Journal of the Acoustical Society of Korea
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• v.23 no.2E
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• pp.56-67
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• 2004

Despite abundant research outcomes of blind source separation (BSS) in many types of simulated environments, their performances are still not satisfactory to be applied to the real environments. The major obstacle may seem the finite filter length of the assumed mixing model and the nonlinear sensor noises. This paper presents a two-step speech enhancement method with multiple microphone inputs. The first step performs a frequency-domain BSS algorithm to produce multiple outputs without any prior knowledge of the mixed source signals. The second step further removes the remaining cross-channel interference by a spectral cancellation approach using a probabilistic source absence/presence detection technique. The desired primary source is detected every frame of the signal, and the secondary source is estimated in the power spectral domain using the other BSS output as a reference interfering source. Then the estimated secondary source is subtracted to reduce the cross-channel interference. Our experimental results show good separation enhancement performances on the real recordings of speech and music signals compared to the conventional BSS methods.

• Journal of Biomedical Engineering Research
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• v.28 no.6
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• pp.732-743
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• 2007

Background noise is one of the major complaints of not only hearing impaired persons but also normal listeners. This paper describes the results of two experiments in which speech recognition performance was determined for listeners with normal hearing and sensorineural hearing loss in noise environment. First, we compared speech enhancement algorithms by evaluation speech recognition ability in various speech-to-noise ratios and types of noise. Next, speech enhancement algorithms by reducing background noise were presented and evaluated to improve speech intelligibility for sensorineural hearing impairment listeners. We tested three noise reduction methods using single-microphone, such as spectrum subtraction and companding, Wiener filter method, and maximum likelihood envelop estimation. Their responses in background noise were investigated and compared with those by the speech enhancement algorithm that presented in this paper. The methods improved speech recognition test score for the sensorineural hearing impaired listeners, but not for normal listeners. The results suggest the speech enhancement algorithm with the loudness compression can improve speech intelligibility for listeners with sensorineural hearing loss.

• The Journal of the Acoustical Society of Korea
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• v.15 no.4
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• pp.83-92
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• 1996

This paper describes Lombard effect compensation and noise suppression so as to reduce speech recognition error in noisy environments. Lombard effect is represented by the variation of spectral envelope of energy normalized word and the variation of overall vocal intensity. The variation of spectral envelope can be compensated by linear transformation in cepstral domain. The variation of vocal intensity is canceled by spectral magnitude normalization. Spectral subtraction is use to suppress noise contamination, and band-pass filtering is used to emphasize dynamic features. To understand Lombard effect and verify the effectiveness of the proposed method, speech data are collected in simulated noisy environments. Recognition experiments were conducted with contamination by noise from automobile cabins, an exhibition hall, telephone booths in down town, crowded streets, and computer rooms. From the experiments, the effectiveness of the proposed method has been confirmed.

• Journal of radiological science and technology
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• v.40 no.3
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• pp.443-451
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• 2017

Mammography is commonly used for screening early breast cancer. However, mammographic images, which depend on the physical properties of breast components, are limited to provide information about whether a lesion is malignant or benign. Although a dual-energy subtraction technique decomposes a certain material from a mixture, it increases radiation dose and degrades the accuracy of material decomposition. In this study, we simulated a breast phantom using attenuation characteristics, and we proposed a technique to enable the accurate material decomposition by applying weighting factors for the dual-energy mammography based on a photon-counting detector using a Monte Carlo simulation tool. We also evaluated the contrast and noise of simulated breast images for validating the proposed technique. As a result, the contrast for a malignant tumor in the dual-energy weighted subtraction technique was 0.98 and 1.06 times similar than those in the general mammography and dual-energy subtraction techniques, respectively. However the contrast between malignant and benign tumors dramatically increased 13.54 times due to the low contrast of a benign tumor. Therefore, the proposed technique can increase the material decomposition accuracy for malignant tumor and improve the diagnostic accuracy of mammography.

• The Journal of the Acoustical Society of Korea
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• v.15 no.5
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• pp.38-43
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• 1996

This paper compares the recognition performances of feature vectors known to be robust to the environmental noise. And, the speech subtraction technique is combined with the noise robust feature to get more performance enhancement. The experiments using SMC(Short time Modified Coherence) analysis, root cepstral analysis, LDA(Linear Discriminant Analysis), PLP(Perceptual Linear Prediction), RASTA(RelAtive SpecTrAl) processing are carried out. An isolated word recognition system is composed using semi-continuous HMM. Noisy environment experiments usign two types of noises:exhibition hall, computer room are carried out at 0, 10, 20dB SNRs. The experimental result shows that SMC and root based mel cepstrum(root_mel cepstrum) show 9.86% and 12.68% recognition enhancement at 10dB in compare to the LPCC(Linear Prediction Cepstral Coefficient). And when combined with spectral subtraction, mel cepstrum and root_mel cepstrum show 16.7% and 8.4% enhanced recognition rate of 94.91% and 94.28% at 10dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.6
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• pp.994-1003
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• 1994

In this paper, a scheme of noise cancellation using spectral subreaction method with single input in an autombile noise environment is proposed. In order to remove the changing automonile noise components form the noisy speech signal, the noise of various states is analyzed and its characteristics are presented. For the decision of speech/nonspeech and the estimation of noise spectrum, a classification function is proposed on the basis of noise analysis. This function presents the precise decision of speech/nonspeech and the optimal estimation of noise spectrum with less computation. As the result of the estimation of noise spectrum by the proposed classification function, the clean speech signal is extracted from the noisy speech signal with high signal-to-ratio.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.147-156
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• 2022

In this paper, we propose Time-Division-Multiplexing Tertiary Offset Carrier (TDMTOC), a novel GNSS modulation based on Tertiary Offset Carrier (TOC) modulation. The TDMTOC modulation multiplexes two three-level signals (i.e., -1, 0, and 1) while crossing over time, and is a type of TOC modulation designed specifically for signal multiplexing. The proposed modulation generates TDMTOC subcarriers of two different phases by simply combining two Binary Offset Carrier (BOC) subcarriers by addition or subtraction. TDMTOC has better correlation and spectral properties than conventional BPSK, BOC, and MBOC modulation techniques, and has good power and spectral efficiency since it can multiplex signals without power loss similar to time division multiplexing. To prove this, we introduce the multiplexing process of TDMTOC, and compare TDMTOC with Binary Phase Shift Keying (BPSK), BOC, Composite BOC (CBOC), and Time Multiplexed BOC (TMBOC) that are currently serviced in GNSS by simulations of various aspects. Through the simulation results, we prove that TDMTOC has better correlation property than modulations currently used in GNSS, less intersystem interference due to its wide spectrum property, and robustness in multipath and noise channel environments.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.671-674
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• 2005

Atmospheric correction over the ocean part is more important than that over the land because the signal from the ocean is very small about one tenth of that reflected from land. In this study, the Spectral Shape Matching Method (SSMM) developed by Ahn and Shanmugam (2004) is evaluated using Landsat imagery acquired over the highly turbid Saemangeum Coastal Area. The result of SSMM is compared with COST model developed by Chavez (1991 and 1997). In principle, SSMM is simple and easy to implement on any satellite imagery, relying on both field and image properties. To assess the potential use of these methods, several field campaigns were conducted in the Saemangeum coastal area corresponding with Landsat-7 satellite's overpass on 29 May 2005. In-situ data collected from the coastal waters of Saemangeum using optical instruments (ASD field spectroradiometer) consists of ChI, Ap, SS, aooM, F(d). In order to perform SSMM, we use the in-situ water-leaving radiance spectra from clear oceanic waters to estimate the the path radiance from total signal recorded at the top of the atmosphere (TOA), due to the reason that the shape of clear water-leaving radiance spectra is nearly stable than turbid water-leaving radiance spectra. The retrieved water-leaving radiance after subtraction of path signal from TOA signal in this way is compared with that estimated by COST model. The result shows that SSMM enabled retrieval of water-leaving radiance spectra that are consistent with in-situ data obtained from Saemangeum coastal waters. The COST model yielded significantly high errors in these areas.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.580-582
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• 2004

스펙트럼 차감과정에서 발생하는 잔류 잡음을 제거하는 방법으로 파라메터를 이용하는 적응 스펙트럼 차감법이 있다. 이는 파라메터를 증가시켜 잔류 잡음을 감소시키는 방법이지만 파라메터를 과도하게 증가시킬 경우 음성 왜곡이 발생한다. 따라서, 적절한 파라메터를 추출하기 위하여 SNR이나, 마스킹 효과 등을 이용한 방법들이 제안되었으나 과도한 잡음의 제거로 인한 음성 왜곡 문제와 낮은 SNR에서 부정확한 파라메터의 추출 문제는 여전히 해결해야 할 과제로 남아있다. 본 논문은 기존의 SNR을 이용한 방법에 마스킹 효과를 적용한 수정된 적응 스펙트럼 차감법을 제안한다. 제안된 방법에서는 마스킹 임계치를 이용하여 잡음 추정값을 재 계산 항으로써 SNR을 향상시켰고, 이를 이용하여 파라메터를 추출함으로써 성능을 개선했다 성능평가 결과, 제안한 차감법을 적용한 음성신호를 고립단어 음성인식 시스템에 적용했을 때 기존의 방법 보다 인식률이 향상된 것을 확인할 수 있었다.