• International Journal of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.26-30
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• 2019

This paper proposes a new voice activity detection (VAD) method which is based on SNR and non-intrusive speech intelligibility estimation. In the conventional SNR-based VAD methods, voice activity probability is obtained by estimating frame-wise SNR at each spectral component. However these methods lack performance in various noisy environments. We devise a hybrid VAD method that uses non-intrusive speech intelligibility estimation as well as SNR estimation, where the speech intelligibility score is estimated based on deep neural network. In order to train model parameters of deep neural network, we use MFCC vector and the intrusive speech intelligibility score, STOI (Short-Time Objective Intelligent Measure), as input and output, respectively. We developed speech presence measure to classify each noisy frame as voice or non-voice by calculating the weighted average of the estimated STOI value and the conventional SNR-based VAD value at each frame. Experimental results show that the proposed method has better performance than the conventional VAD method in various noisy environments, especially when the SNR is very low.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.220-225
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• 2020

This paper investigates the non-intrusive speech intelligibility estimation method in noise environments when the bottleneck feature of autoencoder is used as an input to a neural network. The bottleneck feature-based method has the problem of severe performance degradation when the noise environment is changed. In order to overcome this problem, we propose a novel non-intrusive speech intelligibility estimation method that adds the noise environment information along with bottleneck feature to the input of long short-term memory (LSTM) neural network whose output is a short-time objective intelligence (STOI) score that is a standard tool for measuring intrusive speech intelligibility with reference speech signals. From the experiments in various noise environments, the proposed method showed improved performance when the noise environment is same. In particular, the performance was significant improved compared to that of the conventional methods in different environments. Therefore, we can conclude that the method proposed in this paper can be successfully used for estimating non-intrusive speech intelligibility in various noise environments.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.649-654
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• 2007

Eavesdropping prevention performance is evaluated on a commercial window shaker, which is used to prevent a glass window from eavesdropping. Speech transmission index (STI) is introduced in order to estimate quantitatively the speech intelligibility of the sound detected on the glass window. Objective test by IEC standard using modulation transfer function (MTF) is performed to determine STI. Using Maximum Length Sequency (MLS) signal as a sound source, MTF is measured by accelerometers and laser doppler vibrometer. STI under different level of disturbing wave are compared to confirm the disturbing effect on the speech intelligibility.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.127-134
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• 2009

In this study, possibility of the laser eavesdropping is investigated on the window glasses with various thicknesses, Glass windows are excited by maximum length sequency (MLS) signal and the vibration sound is detected by a laser doppler vibrometer. From the detected sound, speech intelligibility is objectively estimated. Speech transmission index (STI), which is based on the modulation transfer function (MTF). is calculated for the estimation. Finally, disturbing wave effect on the speech intelligibility is analysed by using an outside speaker and a window shaker attached on the glass window. The purpose of the study is to estimate the possibility of remote eavesdropping by the laser sensor and to evaluate the performance of the homemade window shaker to protect from the remote eavesdropping.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.551-556
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• 2008

Possibility of the remote eavesdropping through window glass is investigated using a laser sensor. Various thicknesses and types of glass windows are excited by maximum length sequency (MLS) signal and the vibration sound is detected by a laser doppler vibrometer. Intelligibility of the detected sound is evaluated using the speech transmission index (STI), which is based on the modulation transfer function (MTF). In order to identify the disturbing effect, different level of disturbing wave is generated by an outside speaker and a window shaker attached on the glass window. On the different thickness of glass windows, decrease effect of the speech intelligibility is analysed.

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.1061-1068
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• 2012

This paper deals with a noise reduction algorithm which uses the binary masking approach in the time-frequency domain to improve speech intelligibility. In the binary masking approach, the noise-corrupted speech is decomposed into time-frequency units. Noise-dominant time-frequency units are removed by setting the corresponding binary masks as "0"s and target-dominant units are retained untouched by assigning mask "1"s. We propose a binary mask estimation by comparing the local signal-to-noise ratio (SNR) to a threshold. The local SNR is estimated by a training-based approach. An optimal threshold is proposed, which is obtained from observing the distribution of the training database. The proposed method is evaluated by normal-hearing subjects and the intelligibility scores are computed by counting the number of words correctly recognized.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.175-182
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• 2010

In this paper, we propose a robust speech reinforcement technique to enhance the intelligibility of the degraded speech signal under the ambient noise environments based on soft decision scheme incorporating a speech absence probability (SAP) with speech reinforcement gains. Since the ambient noise significantly decreases the intelligibility of the speech signal, the speech reinforcement approach to amplify the estimated clean speech signal from the background noise environments for improving the intelligibility and clarity of the corrupted speech signal was proposed. In order to estimate the robust reinforcement gain rather than the conventional speech reinforcement method between speech active periods and nonspeech periods or transient intervals, we propose the speech reinforcement algorithm based on soft decision applying the SAP to the estimation of speech reinforcement gains. The performances of the proposed algorithm are evaluated by the Comparison Category Rating (CCR) of the measurement for subjective determination of transmission quality in ITU-T P.800 under various ambient noise environments and show better performances compared with the conventional method.

• 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.

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.311-318
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• 2013

This paper deals with a noise reduction algorithm which uses the binary masking in the time-frequency domain. To improve speech intelligibility in noise, noise-masked speech is decomposed into time-frequency units and mask "0" is assigned to masker-dominant region removing time-frequency units where noise is dominant compared to speech. In the previous research, Gaussian mixture models were used to classify the speech-dominant region and noise-dominant region which correspond to mask "1" and mask "0", respectively. In each frequency band, data were collected and trained to build the Gaussian mixture models and detection procedure is performed to the test data where each time-frequency unit belongs to speech-dominant region or noise-dominant region. In this paper, we consider the correlation of masks in the frequency domain and propose a post-processing method which exploits the Viterbi algorithm.

• Journal of Broadcast Engineering
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• v.18 no.6
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• pp.919-926
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• 2013

The acoustic signal from a distance sound source in an enclosed space often produces reverberant sound that varies depending on room impulse response. The estimation of the level of reverberation or the quality of the observed signal is important because it provides valuable information on the condition of system operating environment. It is also useful for designing a dereverberation system. This paper proposes a speech quality estimation method based on the harmonicity of received signal, a unique characteristic of voiced speech. At first, we show that the harmonic signal modeling to a reverberant signal is reasonable. Then, the ratio between the harmonically modeled signal and the estimated non-harmonic signal is used as a measure of standard room acoustical parameter, which is related to speech clarity. Experimental results show that the proposed method successfully estimates speech quality when the reverberation time varies from 0.2s to 1.0s. Finally, we confirm the superiority of the proposed method in both background noise and reverberant environments.