• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.51-55
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• 2019

This paper proposes a speech enhancement method utilizing the feature compensation gain for robust speech recognition performances in noisy environments. In this paper we propose a speech enhancement method utilizing the feature compensation gain which is obtained from the PCGMM (Parallel Combined Gaussian Mixture Model)-based feature compensation method employing variational model composition. The experimental results show that the proposed method significantly outperforms the conventional front-end algorithms and our previous research over various background noise types and SNR (Signal to Noise Ratio) conditions in mismatched ASR (Automatic Speech Recognition) system condition. The computation complexity is significantly reduced by employing the noise model selection technique with maintaining the speech recognition performance at a similar level.

• The Journal of the Acoustical Society of Korea
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• v.28 no.7
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• pp.668-673
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• 2009

In this paper, we propose the minima controlled speech presence uncertainty tracking method to improve a speech enhancement. In the conventional tracking speech presence uncertainty, we propose a method for estimating distinct values of the a priori speech absence probability for different frames and channels. This estimation is inherently based on a posteriori SNR and used in estimating the speech absence probability (SAP). In this paper, we propose a novel estimation of distinct values of the a priori speech absence probability, which is based on minima controlled speech presence uncertainty tracking method, for different frames and channels. Subsequently, estimation is applied to the calculation of speech absence probability for speech enhancement. Performance of the proposed enhancement algorithm is evaluated by ITU-T P. 862 perceptual evaluation of speech quality (PESQ) under various noise environments. We show that the proposed algorithm yields better results compared to the conventional tracking speech presence uncertainty.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1127-1136
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• 2016

Speech enhancement algorithm plays an important role in numerous speech signal processing applications. Over the last few decades, many algorithms have been studied for speech enhancement. The algorithms are based on spectral subtraction, Wiener filter, and subspace method etc. They have good performance of speech enhancement, but the performance can be deteriorated in specific noises or low SNR environment. In this paper, a new speech enhancement algorithms are proposed based on adaptive noise canceller. And the proposed algorithm improved performance of adaptive noise cancelling using 2-D binary mask. From objective experimental index, it is confirmed that the proposed algorithm is useful and has better performance than recently proposed speech enhancement algorithms.

• Journal of the Korean Society of Radiology
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• v.10 no.6
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• pp.451-456
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• 2016

Radiation dose to patient is unavoidable when diagnosis is carried out using X-ray. Radiation diagnosis using dual energy X-ray was examined to verify the possibility of medical applications by SNR and image scoring. The dual energy X-ray was realized by combining together two image plates and filter of 0.5 mm thick Cu or Al. Under one X-ray exposure, contrast enhanced image was obtained using two images of image plates. The enhanced image showed higher SNR and image score compared to the first image which was the image recorded with the first image plate. The dual energy X-ray technique would be a very useful method for obtaining higher SNR image and for realizing very low dose, and could be applied to medical applications.

• The Journal of the Acoustical Society of Korea
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• v.28 no.1
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• pp.77-83
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• 2009

This paper proposes a new noise-biased compensation of minimum statistics(MS) method using a nonlinear function and a priori speech absence probability(SAP) for speech enhancement in non-stationary noisy environments. The minimum statistics(MS) method is well known technique for noise power estimation in non-stationary noisy environments. It tends to bias the noise estimate below that of true noise level. The proposed method is combined with an adaptive parameter based on a sigmoid function and a priori speech absence probability (SAP) for biased compensation. Specifically. we apply the adaptive parameter according to the a posteriori SNR. In addition, when the a priori SAP equals unity, the adaptive biased compensation factor separately increases ${\delta}_{max}$ each frequency bin, and vice versa. We evaluate the estimation of noise power capability in highly non-stationary and various noise environments, the improvement in the segmental signal-to-noise ratio (SNR), and the Itakura-Saito Distortion Measure (ISDM) integrated into a spectral subtraction (SS). The results shows that our proposed method is superior to the conventional MS approach.

• The Journal of the Acoustical Society of Korea
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• v.17 no.2E
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• pp.38-46
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• 1998

In this paper, we propose a remote speech input device, a new method of user-friendly speech input in spontaneous speech recognition system. We focus the user friendliness on hands-free and microphone independence in speech recognition applications. Our method adopts two algorithms, the automatic speech detection and the microphone array delay-and-sum beamforming (DSBF)-based speech enhancement. The automatic speech detection algorithm is composed of two stages; the detection of speech and nonspeech using the pitch information for the detected speech portion candidate. The DSBF algorithm adopts the time domain cross-correlation method as its time delay estimation. In the performance evaluation, the speech detection algorithm shows within-200 ms start point accuracy of 93%, 99% under 15dB, 20dB, and 25dB signal-to-noise ratio (SNR) environments, respectively and those for the end point are 72%, 89%, and 93% for the corresponding environments, respectively. The classification of speech and nonspeech for the start point detected region of input signal is performed by the pitch information-base method. The percentages of correct classification for speech and nonspeech input are 99% and 90%, respectively. The eight microphone array-based speech enhancement using the DSBF algorithm shows the maximum SNR gaing of 6dB over a single microphone and the error reductin of more than 15% in the spontaneous speech recognition domain.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.87-94
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• 2009

Noise estimation and suppression are a crucial factor of many speech communication and recognition systems. In this paper, proposed algorithm is based on the ratio of variance normalized of noisy power spectrum in time-frequency domain. Our proposed algorithm tracks the threshold and controls the trade-off between residual noise and distortion. This algorithm is evaluated by the ITU-T P.835 signal distortion (SIG) and segment signal to noise ratio (SNR), and is superior to the conventional methods.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.5
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• pp.205-215
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• 2006

In this paper an optical power meter using Hadamard transform, which can be used in multiple channel optical elements alignment system, is proposed. A traditional optical power meter in multiple channel optical elements alignment system is able to judge how well the elements are aligned each other by measuring optical power of the first and the last two channels with at least two detectors. It has critical drawback that the alignment accuracy per channel is dependent on the number of detectors. The proposed optical power meter can get noise reduction by the Hadamard transform based multiplexing technique. The Hadamard transform based multiplexing technique using spatial light modulators is distinguished by the best enhancement of signal-to-noise ratio (SNR) for the reconstructed signals. Moreover, the noise reduction increases with increasing the order of multiplexing, namely the number of optical element channels. The proposed system is implemented by PDLC (Polymer Dispersed Liquid Crystal) mask which is operated by electric filed and generates optimal multiplexing patterns based on the Hadamard transform and single detector. It means that we obtain not only the each channel's optical power of multiple channel elements at once but also the best enhancement of SNR with single detector. Experimental results show that the proposed optical power meter is suitable for an active optical alignment system for multiple channel optical elements.

• The Journal of the Acoustical Society of Korea
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• v.21 no.4
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• pp.374-379
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• 2002

In this paper, a nobel method to reduce noise using voice/unvoice classification is proposed. Voice and unvoice are an important feature of speech and the proposed method processes noisy speech differently for each voice/unvoice part. Speech is classified into voice/unvoice using zero-crossing rate and energy, and a modified speech/noise dominant-decision is proposed based on voice/unvoice classification. The proposed method was tested on conditions of white noise and airplane noise, and on the basis of comparing segmental SNR with the existing method and listening to the enhanced speech, a performance of the proposed method was superior to that of the existing method.

• Journal of the Korean Society for Nondestructive Testing
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• v.16 no.1
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• pp.1-9
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• 1996

Many signal-processing techniques have been found to be useful in ultrasonic and nondestructive evaluation. Among the most popular techniques are signal averaging, spatial compounding, matched filters and homomorphic processing. One of the significant new process is split-spectrum processing(SSP), which can be equally useful in signal-to-noise ratio(SNR) improvement and grain characterization in several specimens. The purpose of this paper is to explore the utility of SSP in ultrasonic NDE. A wide variety of engineering problems are reviewed, and suggestions for implementation of the technique are provided. SSP uses the frequency-dependent response of the interfering coherent noise produced by unresolvable scatters in the resolution range cell of a transducer. It is implemented by splitting the frequency spectrum of the received signal by using gaussian bandpass filter. The theoretical basis for the potential of SSP for grain characterization in SUS 304 material is discussed, and some experimental evidence for the feasibility of the approach is presented. Results of SNR enhancement in signals obtained from real four samples of SUS 304. The influence of various processing parameters on the performance of the processing technique is also discussed. The minimization algorithm, which provides an excellent SNR enhancement when used either in conjunction with other SSP algorithms like polarity-check or by itself, is also presented.