• Title/Summary/Keyword: Noise Robust

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A Study on Noisy Speech Recognition Using a Bayesian Adaptation Method (Bayesian 적응 방식을 이용한 잡음음성 인식에 관한 연구)

  • 정용주
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.2
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    • pp.21-26
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    • 2001
  • An expectation-maximization (EM) based Bayesian adaptation method for the mean of noise is proposed for noise-robust speech recognition. In the algorithm, the on-line testing utterances are used for the unsupervised Bayesian adaptation and the prior distribution of the noise mean is estimated using the off-line training data. For the noisy speech modeling, the parallel model combination (PMC) method is employed. The proposed method has shown to be effective compared with the conventional PMC method for the speech recognition experiments in a car-noise condition.

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Design Sensitivity Studies for Statistical Energy Analysis Modeling of Construction Vehicles (통계적 에너지 해석 모델을 이용한 건설 장비 설계에 관한 연구)

  • ;Manning, Jerome E.;Tracey, Brian H.
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 1997.10a
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    • pp.385-390
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    • 1997
  • In recent years there has been an increasing emphasis on shortening design cycles for bringing products to market. This requires the development of computer aided engineering tools which allow analysts to quickly evaluate the effect of design changes on noise, vibration, and harshness. Statistical Energy Analysis (SEA) modeling is a valuable tool for predicting noise and vibration as SEA models are inherently simpler and more robust than deterministic models. SEA modeling can be combined with design sensitivity analysis (DSA) to identify design changes which give the largest performance benefit. This paper describes SEA modeling of an equipment cab. SEA predictions are compared to test data, showing good agreement. The use of design sensitivity analysis in improving cab design is then demonstrated.

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Ultralow Intensity Noise Pulse Train from an All-fiber Nonlinear Amplifying Loop Mirror-based Femtosecond Laser

  • Dohyeon Kwon;Dohyun Kim
    • Current Optics and Photonics
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    • v.7 no.6
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    • pp.708-713
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    • 2023
  • A robust all-fiber nonlinear amplifying loop-mirror-based mode-locked femtosecond laser is demonstrated. Power-dependent nonlinear phase shift in a Sagnac loop enables stable and power-efficient mode-locking working as an artificial saturable absorber. The pump power is adjusted to achieve the lowest intensity noise for stable long-term operation. The minimum pump power for mode-locking is 180 mW, and the optimal pump power is 300 mW. The lowest integrated root-mean-square relative intensity noise of a free-running mode-locked laser is 0.009% [integration bandwidth: 1 Hz-10 MHz]. The long-term repetition-rate instability of a free-running mode-locked laser is 10-7 over 1,000 s averaging time. The repetition-rate phase noise scaled at 10-GHz carrier is -122 dBc/Hz at 10 kHz Fourier frequency. The demonstrated method can be applied as a seed source in high-precision real-time mid-infrared molecular spectroscopy.

Noise-Robust Porcine Respiratory Diseases Classification Using Texture Analysis and CNN (질감 분석과 CNN을 이용한 잡음에 강인한 돼지 호흡기 질병 식별)

  • Choi, Yongju;Lee, Jonguk;Park, Daihee;Chung, Yongwha
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.3
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    • pp.91-98
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    • 2018
  • Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. In particular, porcine respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this paper, we propose a noise-robust system for the early detection and recognition of pig wasting diseases using sound data. In this method, first we convert one-dimensional sound signals to two-dimensional gray-level images by normalization, and extract texture images by means of dominant neighborhood structure technique. Lastly, the texture features are then used as inputs of convolutional neural networks as an early anomaly detector and a respiratory disease classifier. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (low-cost sound sensor) and accurately (over 96% accuracy) even under noise-environmental conditions, either as a standalone solution or to complement known methods to obtain a more accurate solution.

Motion Adaptive Temporal-Spatial Noise Reduction Scheme with Separated Pre- and Post-Spatial Filter (분리된 전처리 및 후처리 광간영역 필터를 가진 움직임 적응적 시공간영역 잡음 제거 기법)

  • Kim, Sung-Deuk;Lim, Kyoung-Won
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.5
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    • pp.40-47
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    • 2009
  • A motion adaptive video noise reduction scheme is proposed by cascading a temporal filter and a spatial filter. After a noise-robust motion detection is performed with a pre-spatial filter, the strength of the motion adaptive temporal filter is controlled by the amount of temporal movement. In order to fully utilize the temporal correlation of video signal, noisy input image is processed first by the temporal filter, therefore, image details of temporally stationary region are quite well preserved while undesired noises are suppressed. In contrast to the pre-spatial filter used for the robust motion detection, the cascaded post-spatial filter removes the remained noises by considering the strength of the temporal filter and the spatial self-similarity search results obtained from the pre-spatial filter.

Robust Speech Enhancement Using HMM and $H_\infty$ Filter (HMM과 $H_\infty$필터를 이용한 강인한 음성 향상)

  • 이기용;김준일
    • The Journal of the Acoustical Society of Korea
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    • v.23 no.7
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    • pp.540-547
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    • 2004
  • Since speech enhancement algorithms based on Kalman/Wiener filter require a priori knowledge of the noise and have focused on the minimization of the variance of the estimation error between clean and estimated speech signal, small estimation error on the noise statistics may lead to large estimation error. However, H/sub ∞/ filter does not require any assumptions and a priori knowledge of the noise statistics, but searches the best estimated signal among the entire estimated signal by applying least upper bound, consequently it is more robust to the variation of noise statistics than Kalman/Wiener filter. In this paper, we Propose a speech enhancement method using HMM and multi H/sub ∞/ filters. First, HMM parameters are estimated with the training data. Secondly, speech is filtered with multiple number of H/sub ∞/ filters. Finally, the estimation of clean speech is obtained from the sum of the weighted filtered outputs. Experimental results shows about 1dB∼2dB SNR improvement with a slight increment of computation compared with the Kalman filter method.

An Evaluation and Combination of Noise Reduction Filtering and Edge Detection Filtering for the Feature Element Selection in Stereo Matching (스테레오 정합 특징 요소 선택을 위한 잡음 감소 필터링과 에지 검출 필터링의 성능 평가와 결합)

  • Moon, Chang-Gi;Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.23 no.4
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    • pp.273-285
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    • 2007
  • Most stereo matching methods use intensity values in small image patches to measure the correspondence between two points. If the noisy pixels are used in computing the corresponding point, the matching performance becomes low. For this reason, the noise plays a critical role in determining the matching performance. In this paper, we propose a method for combining intensity and edge filters robust to the noise in order to improve the performance of stereo matching using high resolution satellite imagery. We used intensity filters such as Mean, Median, Midpoint and Gaussian filter and edge filters such as Gradient, Roberts, Prewitt, Sobel and Laplacian filter. To evaluate the performance of intensity and edge filters, experiments were carried out on both synthetic images and satellite images with uniform or gaussian noise. Then each filter was ranked based on its performance. Among the intensity and edge filters, Median and Sobel filter showed best performance while Midpoint and Laplacian filter showed worst result. We used Ikonos satellite stereo imagery in the experiments and the matching method using Median and Sobel filter showed better matching results than other filter combinations.

Reference Channel Input-Based Speech Enhancement for Noise-Robust Recognition in Intelligent TV Applications (지능형 TV의 음성인식을 위한 참조 잡음 기반 음성개선)

  • Jeong, Sangbae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.2
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    • pp.280-286
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    • 2013
  • In this paper, a noise reduction system is proposed for the speech interface in intelligent TV applications. To reduce TV speaker sound which are very serious noises degrading recognition performance, a noise reduction algorithm utilizing the direct TV sound as the reference noise input is implemented. In the proposed algorithm, transfer functions are estimated to compensate for the difference between the direct TV sound and that recorded with the microphone installed on the TV frame. Then, the noise power spectrum in the received signal is calculated to perform Wiener filter-based noise cancellation. Additionally, a postprocessing step is applied to reduce remaining noises. Experimental results show that the proposed algorithm shows 88% recognition rate for isolated Korean words at 5 dB input SNR.

Creation and Assessment of Korean Speech and Noise DB in Car Environments (자동차 환경에서의 노이즈 DB 및 한국어 음성 DB 구축)

  • Lee Kwang-Hyun;Kim Bong-Wan;Lee Yong-Ju
    • MALSORI
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    • no.48
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    • pp.141-153
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    • 2003
  • Researches into robust recognition in noise environments, especially in car environments, are being carried out actively in speech community. In this paper we will report on three types of corpora that SiTEC (Speech Information TEchnology & industry promotion Center) has created for research into speech recognition in car noise environments. The first is the recordings of 900 Korean native speakers, distributed according to gender, age, and region, who uttered application words in car environments. The second is the collections of mixed noise in 3 car types by model while setting up various noise patterns which can be obtained with the car engine on or off, at different driving speed, and in different road conditions with windows open or closed. The third is the recordings of simulated speech by HATS (Head and Torso Simulator) in car environments with the internal and external noise factors added. These three types of recordings were all made through synchronized 8 channel microphones that are fixed in a car. The creation and applications of these corpora will be reported on in detail.

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Efficient Compensation of Spectral Tilt for Speech Recognition in Noisy Environment (잡음 환경에서 음성인식을 위한 스펙트럼 기울기의 효과적인 보상 방법)

  • Cho, Jungho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.1
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    • pp.199-206
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    • 2017
  • Environmental noise can degrade the performance of speech recognition system. This paper presents a procedure for performing cepstrum based feature compensation to make recognition system robust to noise. The approach is based on direct compensation of spectral tilt to remove effects of additive noise. The noise compensation scheme operates in the cepstral domain by means of calculating spectral tilt of the log power spectrum. Spectral compensation is applied in combination with SNR-dependent cepstral mean compensation. Experimental results, in the presence of white Gaussian noise, subway noise and car noise, show that the proposed compensation method achieves substantial improvements in recognition accuracy at various SNR's.