• 제목/요약/키워드: auditory model

검색결과 158건 처리시간 0.025초

적응 필터를 이용한 청각 자극에 의한 뇌자도 신호에서 노이즈 제거 (Adaptive Noise Subtraction in Auditory Evoked Field)

  • 이동훈;안창범
    • 대한전기학회논문지:시스템및제어부문D
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    • 제52권10호
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    • pp.606-610
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    • 2003
  • Noise subtraction using reference channel data has been used to improve signal-to-noise ratio in magnetoencephalography. In this paper, an adaptive noise subtraction model is proposed and parameters for the model are optimized. A criterion to determine an optimal update period for the filter coefficients is proposed based on the ratio of peak amplitude of evoked field (N100m) divided by the output standard deviation. Experiments are carried out using a 40 channel MEG system. From the experiments, the proposed noise subtraction method shows superior performances over existing non-adaptive methods. Two-dimensional topographic map is shown for a diagnosis with a cubic spline interpolation.

청각모델과 회귀회로망을 이용한 음성인식에 관한 연구 (A Study on Speech Recognition Using Auditory Model and Recurrent Network)

  • 김동준;이재혁
    • 대한의용생체공학회:의공학회지
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    • 제11권1호
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    • pp.157-162
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    • 1990
  • In this study, a peripheral auditory model is used as a frequency feature extractor and a recurrent network which has recurrent links on input nodes is constructed in order to show the reliability of the recurrent network as a recognizer by executing recognition tests for 4 Korean place names and syllables. In the case of using the general learning rule, it is found that the weights are diverged for a long sequence because of the characteristics of the node function in the hidden and output layers. So, a refined weight compensation method is proposed and, using this method, it is possible to improve the system operation and to use long data. The recognition results are considerably good, even if time worping and endpoint detection are omitted and learning patterns and test patterns are made of average length of data. The recurrent network used in this study reflects well time information of temporal speech signal.

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잡음에 강한 음성 인식을 위한 성문 가중 켑스트럼에 관한 연구 (Glottal Weighted Cepstrum for Robust Speech Recognition)

  • 전선도;강철호
    • 한국음향학회지
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    • 제18권5호
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    • pp.78-82
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    • 1999
  • 본 연구는 잡음에 강한 음성 파라미터로써 널리 사용하는 가중 켑스트럼에 관한 연구이다. 특히 청각 모델인 PLP(Perceptual Linear Predictive)에서 켑스트럼을 추출 후 비대칭형 성문 펄스 파형 형태를 가중치 함수로 사용하는 방법을 제안한다. 또한 이러한 가중 켑스트럼을 성도 모델에서의 성도파형과 켑스트럼과 연관하여 분석하였다. 그리고 청각 모델인 PLP의 켑스트럼에 가중시켜 청각 모델과 성도 모델을 모두 적용한 음성 파라미터를 얻었다. 이러한 방법의 성능 평가를 위해 차량내 잡음과 길거리에서의 잡음 환경에서의 고립 단어 인식 실험을 하였다. 그리고 기존의 LP(Linear Prediction)에 의한 가중된 윈도우 켑스트럼 및 PLP에 의한 가중된 Liftering 켑스트럼 등과 비교하였다. 모의 실험 결과는 기존의 가중된 cepstrum 보다 제안하는 성문 가중 켑스트럼이 보다 높은 인식율을 보여준다.

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Prediction of the Exposure to 1763MHz Radiofrequency Radiation Based on Gene Expression Patterns

  • Lee, Min-Su;Huang, Tai-Qin;Seo, Jeong-Sun;Park, Woong-Yang
    • Genomics & Informatics
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    • 제5권3호
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    • pp.102-106
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    • 2007
  • Radiofrequency (RF) radiation at the frequency of mobile phones has been not reported to induce cellular responses in in vitro and in vivo models. We exposed HEI-OC1, conditionally-immortalized mouse auditory cells, to RF radiation to characterize cellular responses to 1763 MHz RF radiation. While we could not detect any differences upon RF exposure, whole-genome expression profiling might provide the most sensitive method to find the molecular responses to RF radiation. HEI-OC1 cells were exposed to 1763 MHz RF radiation at an average specific absorption rate (SAR) of 20 W/kg for 24 hr and harvested after 5 hr of recovery (R5), alongside sham-exposed samples (S5). From the whole-genome profiles of mouse neurons, we selected 9 differentially-expressed genes between the S5 and R5 groups using information gain-based recursive feature elimination procedure. Based on support vector machine (SVM), we designed a prediction model using the 9 genes to discriminate the two groups. Our prediction model could predict the target class without any error. From these results, we developed a prediction model using biomarkers to determine the RF radiation exposure in mouse auditory cells with perfect accuracy, which may need validation in in vivo RF-exposure models.

인공와우 어음처리방식을 위한 적응효과 알고리즘의 음성개시점 검출 특성 비교 (Comparison of Speech Onset Detection Characteristics of Adaptation Algorithms for Cochlear Implant Speech Processor)

  • 최성진;김진호;김경환
    • 대한의용생체공학회:의공학회지
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    • 제29권1호
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    • pp.25-31
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    • 2008
  • It is well known that temporal information, i.e speech onset, about input speech can be represented to the response nerve signal of auditory nerve better depending on the adaptation effect occurred in the auditory nerve synapse. In addition, the performance of a speech processor of cochlear implant can be improved by the adaptation effect. In this paper, we observed the emphasis characteristic of speech onset in the recently proposed adaptation algorithm, analyzed the characteristic of performance change according to the variation of parameters and compared with transient emphasis spectral maxima (TESM) is the previous typical strategy. When observing false peaks which are generated everywhere except speech onset, in the case of the proposed model, the false peak were generated much less than in the case of the TESM and it is more distinguishable under noise.

Emotion recognition from speech using Gammatone auditory filterbank

  • 레바부이;이영구;이승룡
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(A)
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    • pp.255-258
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    • 2011
  • An application of Gammatone auditory filterbank for emotion recognition from speech is described in this paper. Gammatone filterbank is a bank of Gammatone filters which are used as a preprocessing stage before applying feature extraction methods to get the most relevant features for emotion recognition from speech. In the feature extraction step, the energy value of output signal of each filter is computed and combined with other of all filters to produce a feature vector for the learning step. A feature vector is estimated in a short time period of input speech signal to take the advantage of dependence on time domain. Finally, in the learning step, Hidden Markov Model (HMM) is used to create a model for each emotion class and recognize a particular input emotional speech. In the experiment, feature extraction based on Gammatone filterbank (GTF) shows the better outcomes in comparison with features based on Mel-Frequency Cepstral Coefficient (MFCC) which is a well-known feature extraction for speech recognition as well as emotion recognition from speech.

인지로봇 청각시스템을 위한 의사최적 이동음원 도래각 추적 필터 (Quasi-Optimal Linear Recursive DOA Tracking of Moving Acoustic Source for Cognitive Robot Auditory System)

  • 한슬기;나원상;황익호;박진배
    • 제어로봇시스템학회논문지
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    • 제17권3호
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    • pp.211-217
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    • 2011
  • This paper proposes a quasi-optimal linear DOA (Direction-of-Arrival) estimator which is necessary for the development of a real-time robot auditory system tracking moving acoustic source. It is well known that the use of conventional nonlinear filtering schemes may result in the severe performance degradation of DOA estimation and not be preferable for real-time implementation. These are mainly due to the inherent nonlinearity of the acoustic signal model used for DOA estimation. This motivates us to consider a new uncertain linear acoustic signal model based on the linear prediction relation of a noisy sinusoid. Using the suggested measurement model, it is shown that the resultant DOA estimation problem is cast into the NCRKF (Non-Conservative Robust Kalman Filtering) problem [12]. NCRKF-based DOA estimator provides reliable DOA estimates of a fast moving acoustic source in spite of using the noise-corrupted measurement matrix in the filter recursion and, as well, it is suitable for real-time implementation because of its linear recursive filter structure. The computational efficiency and DOA estimation performance of the proposed method are evaluated through the computer simulations.

음악신호와 뇌파 특징의 회귀 모델 기반 감정 인식을 통한 음악 분류 시스템 (Music classification system through emotion recognition based on regression model of music signal and electroencephalogram features)

  • 이주환;김진영;정동기;김형국
    • 한국음향학회지
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    • 제41권2호
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    • pp.115-121
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    • 2022
  • 본 논문에서는 음악 청취 시에 나타나는 뇌파 특징을 이용하여 사용자 감정에 따른 음악 분류 시스템을 제안한다. 제안된 시스템에서는 뇌파 신호로부터 추출한 감정별 뇌파 특징과 음악신호에서 추출한 청각적 특징 간의 관계를 회귀 심층신경망을 통해 학습한다. 실제 적용 시에는 이러한 회귀모델을 기반으로 제안된 시스템은 입력되는 음악의 청각 특성에 매핑된 뇌파 신호 특징을 자동으로 생성하고, 이 특징을 주의집중 기반의 심층신경망에 적용함으로써 음악을 자동으로 분류한다. 실험결과는 제안된 자동 음악분류 프레임 워크의 음악 분류 정확도를 제시한다.

Near-Infrared Laser Stimulation of the Auditory Nerve in Guinea Pigs

  • Guan, Tian;Wang, Jian;Yang, Muqun;Zhu, Kai;Wang, Yong;Nie, Guohui
    • Journal of the Optical Society of Korea
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    • 제20권2호
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    • pp.269-275
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    • 2016
  • This study has investigated the feasibility of 980-nm low-energy pulsed near-infrared laser stimulation to evoke auditory responses, as well as the effects of radiant exposure and pulse duration on auditory responses. In the experiments, a hole was drilled in the basal turn of the cochlea in guinea pigs. An optical fiber with a 980-nm pulsed infrared laser was inserted into the hole, orientating the spiral ganglion cells in the cochlea. To model deafness, the tympanic membrane was mechanically damaged. Acoustically evoked compound action potentials (ACAPs) were recorded before and after deafness, and optically evoked compound action potentials (OCAPs) were recorded after deafness. Similar spatial selectivity between optical and acoustical stimulation was found. In addition, OCAP amplitudes increased with radiant exposure, indicating a photothermal mechanism induced by optical stimulation. Furthermore, at a fixed radiant exposure, OCAP amplitudes decreased as pulse duration increased, suggesting that optical stimulation might be governed by the time duration over which the energy is delivered. Thus, the current experiments have demonstrated that a 980-nm pulsed near-infrared laser with low energy can evoke auditory neural responses similar to those evoked by acoustical stimulation. This approach could be used to develop optical cochlear implants.

조현병 환자의 언어성 환청과 정신병리의 PANSS 요인들 간의다차원적 관계 (Multidimensional Relationship between Auditory Verbal Hallucinations and PANSS Factors of Psychopathology in the Patients with Schizophrenia)

  • 신샘이;김세현;이남영;윤탁;김용식;정인원
    • 생물정신의학
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    • 제22권4호
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    • pp.163-172
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    • 2015
  • Objectives This study was aimed to examine the multidimensional relationship between auditory verbal hallucinations (AVHs) and Positive and Negative Syndrome Scale (PANSS) factors of psychopathology in the patients with schizophrenia. And we explored the differences between assessments to hallucination by the clinicians and patients. Methods 82 patients with schizophrenia who were assessed by the Hamilton Program for Schizophrenia Voices Questionnaire (HPSVQ), Psychotic Symptom Rating Scale-Auditory Hallucination (PSYRATS-AHS), and the PANSS were recruited. Hwang's five-factor model of PANSS, items and total scores of hallucination scales, Kim's and Haddock's factor models of hallucination were applied to examine the correlations between psychopathology and AVHs. AVH-positive patients was 50 in PANSS-HPSVQ group and 24 in PANSS-PSYRATS-AHS. These two groups were separately analyzed. Results Among the five factors of the PANSS, negative and depression/anxiety factors were correlated with the total scores of HPSVQ and PSYRATS-AHS, and positive and autistic preoccupation factors were correlated only with the total score of PSYRATS-AHS. The activation factor was correlated with none of the total scores of HPSVQ/PSYRATS-AHS. These correlation patterns of a total score of HPSVQ/PSYRATS-AHS were same in the emotional factor of HPSVQ and physical factor of PSYRATS-AHS respectively. In the items which showed significant correlations, correlation coefficients of PANSS-PSYRATS-AHS group ranged between 0.406-0.755 and those of PANSS-HPSVQ ranged between 0.283-0.420. Conclusions This study suggested that the psychopathological domains of schizophrenia were differentially correlated with AVHs and the assessment of AVHs by clinicians and patients showed substantial differences which should be integrated into the therapeutic interventions.