{"title":"Under-modelled blind system identification for time delay estimation in reverberant environments","authors":"Wei Xue, M. Brookes, P. Naylor","doi":"10.1109/IWAENC.2016.7602923","DOIUrl":"https://doi.org/10.1109/IWAENC.2016.7602923","url":null,"abstract":"In multichannel systems, acoustic time delay estimation (TDE) is a challenging problem in reverberant environments. Although blind system identification (BSI) based methods have been proposed which utilize a realistic signal model for the room impulse response (RIR), their TDE performance depends strongly on that of the BSI, which is often inaccurate in practice when the identified responses are under-modelled. In this paper, we propose a new under-modelled BSI based method for TDE in reverberant environments. An under-modelled BSI algorithm is derived, which is based on maximizing the cross-correlation of the cross-filtered signals rather than minimizing the cross-relation error, and also exploits the sparsity of the early part of the RIR. For TDE, this new criterion can be viewed as a generalization of conventional cross-correlation-based TDE methods by considering a more realistic model for the early RIR. Depending on the microphone spacing, only a short early part of each RIR is identified, and the time delays are estimated based on the peak locations in the identified early RIRs. Experiments in different reverberant environments with speech source signals demonstrate the effectiveness of the proposed method.","PeriodicalId":373697,"journal":{"name":"2016 IEEE International Workshop on Acoustic Signal Enhancement (IWAENC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122703295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Voice activity detection based on statistical likelihood ratio with adaptive thresholding","authors":"Xiaofei Li, R. Horaud, Laurent Girin, S. Gannot","doi":"10.1109/IWAENC.2016.7602911","DOIUrl":"https://doi.org/10.1109/IWAENC.2016.7602911","url":null,"abstract":"Statistical likelihood ratio test is a widely used voice activity detection (VAD) method, in which the likelihood ratio of the current temporal frame is compared with a threshold. A fixed threshold is always used, but this is not suitable for various types of noise. In this paper, an adaptive threshold is proposed as a function of the local statistics of the likelihood ratio. This threshold represents the upper bound of the likelihood ratio for the non-speech frames, whereas it remains generally lower than the likelihood ratio for the speech frames. As a result, a high non-speech hit rate can be achieved, while maintaining speech hit rate as large as possible.","PeriodicalId":373697,"journal":{"name":"2016 IEEE International Workshop on Acoustic Signal Enhancement (IWAENC)","volume":"1 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123796369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tomoko Kawase, K. Niwa, Kazunori Kobayashi, Yusuke Hioka
{"title":"Application of neural network to source PSD estimation for wiener filter based array sound source enhancement","authors":"Tomoko Kawase, K. Niwa, Kazunori Kobayashi, Yusuke Hioka","doi":"10.1109/IWAENC.2016.7602949","DOIUrl":"https://doi.org/10.1109/IWAENC.2016.7602949","url":null,"abstract":"The Wiener filter has been used as a post-filter applied to the output of beamforming, which boosts the overall performance of sound source enhancement. Since the power spectral density (PSD) of each sound source needs to be estimated to derive the Wiener filter, a previous study attempted to estimate source PSDs from the output signals of multiple beamformings using linear approximation realized by the least squares method. In this study, we propose an alternative approach to this estimation process that uses a neural network to implement the approximation by using a non-linear function. Experimental results reveal that the proposed method estimated the Wiener filter more accurately, resulting in higher source enhancement performance while reducing the distortion in the desired sound signal.","PeriodicalId":373697,"journal":{"name":"2016 IEEE International Workshop on Acoustic Signal Enhancement (IWAENC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125107999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Extraction of exterior field from a mixed sound field for 2D height-invariant sound propagation","authors":"Abdullah Fahim, P. Samarasinghe, T. Abhayapala","doi":"10.1109/IWAENC.2016.7602967","DOIUrl":"https://doi.org/10.1109/IWAENC.2016.7602967","url":null,"abstract":"Any sound field caused by one or more sound sources takes the form of an interior, exterior or a mixed sound field based on the source locations. The recording and reproduction of interior or exterior sound fields in terms of harmonic decomposition has been extensively studied in the literature, however the challenging task of separating them in a mixed field remains largely unexplored. But in nature, the interior and exterior sound fields often co-exist, hence their isolation can be very useful in many acoustic processes. In this paper, we discuss a method to extract the exterior field from a mixed sound field for 2D height-invariant sound propagation. Such an extraction method can be employed to record a sound field in a noisy or interfered room or to perform dereverberation in a reverberant room where the sound fields due to the source signal and its reflections superimpose each other. We demonstrate two practical uses of the proposed method in the forms of (i) an exterior sound field recording in a mixed wave field and (ii) speech dereverberation in a simulated reverberant room.","PeriodicalId":373697,"journal":{"name":"2016 IEEE International Workshop on Acoustic Signal Enhancement (IWAENC)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121214553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Improved nonnegative adaptive filtering algorithms","authors":"K. Zhao, J. Ni, Xiaoping Chen","doi":"10.1109/IWAENC.2016.7602966","DOIUrl":"https://doi.org/10.1109/IWAENC.2016.7602966","url":null,"abstract":"The nonnegative least mean square (NNLMS) algorithm has the advantages of simplicity and ease of implementation, but it has a slow convergence rate in sparse nonnegative system identification and its robustness is not strong in an impulsive interference environment. To solve these problems, an lo-norm NNLMS (lo-NNLMS) algorithm is presented by using an lo-norm optimization. Then, an lo-norm nonnegative least logarithmic absolute difference (lo-NNLLAD) algorithm is proposed by combining the lo-norm of the weight vector and a logarithmic function as cost function. Simulation results show the lo-NNLMS algorithm can increase the convergence rate in sparse nonnegative system identification, and that the lo-NNLLAD algorithm is more robust than the lo-NNLMS algorithm.","PeriodicalId":373697,"journal":{"name":"2016 IEEE International Workshop on Acoustic Signal Enhancement (IWAENC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123694545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ofer Schwartz, Yuval Dorfan, Emanuël Habets, S. Gannot
{"title":"Multi-speaker DOA estimation in reverberation conditions using expectation-maximization","authors":"Ofer Schwartz, Yuval Dorfan, Emanuël Habets, S. Gannot","doi":"10.1109/IWAENC.2016.7602897","DOIUrl":"https://doi.org/10.1109/IWAENC.2016.7602897","url":null,"abstract":"A novel direction of arrival (DOA) estimator for concurrent speakers in reverberant environment is presented. Reverberation, if not properly addressed, is known to degrade the performance of DOA estimators. In our contribution, the DOA estimation task is formulated as a maximum likelihood (ML) problem, which is solved using the expectation-maximization (EM) procedure. The received microphone signals are modelled as a sum of anechoic and reverberant components. The reverberant components are modelled by a timeinvariant coherence matrix multiplied by time-varying reverberation power spectral density (PSD). The PSDs of the anechoic speech and reverberant components are estimated as part of the EM procedure. It is shown that the DOA estimates, obtained by the proposed algorithm, are less affected by reverberation than competing algorithms that ignore the reverberation. Experimental study demonstrates the benefit of the presented algorithm in reverberant environment using measured room impulse responses (RIRs).","PeriodicalId":373697,"journal":{"name":"2016 IEEE International Workshop on Acoustic Signal Enhancement (IWAENC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117263791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Approximate MVDR and MMSE beamformers exploiting scale-invariant reconstruction of signals on microphones","authors":"Zbyněk Koldovský, F. Nesta","doi":"10.1109/IWAENC.2016.7602928","DOIUrl":"https://doi.org/10.1109/IWAENC.2016.7602928","url":null,"abstract":"Minimum Variance Distortionless Response (MVDR) and Minimum Mean-Squared Error (MMSE) beamformers are popular array processors for enhancing multichannel recordings of a directional source. We propose their approximate variants having the generalized sidelobe canceler structure whose performances depend purely on the blocking matrix part. No auxiliary methods such as adaptive interference canceler or voice activity detector to estimate the source/noise covariance are needed. Instead, scale-invariant least square estimators are used, which enable to estimate the noise also during speech activity and to recover original spectra of the target source on the microphones. In experiments, we compare signal-to-noise ratio improvements of several variants of the beamformers achieved on six-channel recordings of speech in nonstationary noisy conditions.","PeriodicalId":373697,"journal":{"name":"2016 IEEE International Workshop on Acoustic Signal Enhancement (IWAENC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129873990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A modified a priori SER for acoustic echo suppression using wiener filter","authors":"Ying Tong, Yaping Gu","doi":"10.1109/IWAENC.2016.7602950","DOIUrl":"https://doi.org/10.1109/IWAENC.2016.7602950","url":null,"abstract":"In this paper, we address the problem of single-channel acoustic echo suppression using wiener filter method. A time-frequency varying self-adaptive averaging factor in the minimum-mean square estimation (MMSE) sense to estimate the a priori signal-to-echo ratio (SER) is proposed. The modified a priori SER can track the sudden change of the near-end signal more quickly. Performance of the novel method is accessed by using the Weiner filter based acoustic echo suppression algorithm in which the smoothing parameter is a constant value. By using the proposed algorithm, improved results are obtained at different signal-to-noise ratio (SNR) levels.","PeriodicalId":373697,"journal":{"name":"2016 IEEE International Workshop on Acoustic Signal Enhancement (IWAENC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128437972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Affine projection algorithm for acoustic feedback cancellation using prediction error method in hearing aids","authors":"L. Tran, H. H. Dam, S. Nordholm","doi":"10.1109/IWAENC.2016.7602885","DOIUrl":"https://doi.org/10.1109/IWAENC.2016.7602885","url":null,"abstract":"Prediction error method (PEM) is popularly applied to acoustic feedback cancellation (AFC) in hearing aids. Commonly, this method uses normalized least mean square (NLMS) adaptive filter to estimate the coefficients of the real feedback path. A disadvantage of NLMS algorithm is to provide a slow convergence rate when coloured incoming signals are used. To address this problem, we propose a simple but effective way to apply an affine projection algorithm (APA) to acoustic feedback cancellation using PEM. Performance of the proposed method is evaluated for speech incoming signal in both cases of using/not using a probe noise. Simulation results show that the proposed method outperforms the PEM using NLMS in both terms of misalignment and added stable gain.","PeriodicalId":373697,"journal":{"name":"2016 IEEE International Workshop on Acoustic Signal Enhancement (IWAENC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126707779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An iterative method for equalization of multichannel acoustic systems robust to system identification errors","authors":"Wancheng Zhang, P. Naylor","doi":"10.1109/IWAENC.2016.7602899","DOIUrl":"https://doi.org/10.1109/IWAENC.2016.7602899","url":null,"abstract":"The use of an iterative method for equalization of acoustic systems, the channel estimates of which are obtained from supervised system identification (SSI), is investigated. An optimally-stopped weighted conjugate gradient (OS-WCG) algorithm is presented. In the presence of system identification errors (SIEs), a peak of weighted direct-to-reverberant ratio (WDRR) in the iterative process is shown. Then a method to estimate the iteration index of the peak is provided. Finally, a stopping condition for the iteration is proposed. Evaluation results show that using OS-WCG, an improvement up to 20 dB in C50 and 0.141 s in T30 can be achieved.","PeriodicalId":373697,"journal":{"name":"2016 IEEE International Workshop on Acoustic Signal Enhancement (IWAENC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114801267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}