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2015 23rd European Signal Processing Conference (EUSIPCO)最新文献

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Permutation-free clustering of relative transfer function features for blind source separation 盲源分离中相对传递函数特征的无置换聚类
2015 23rd European Signal Processing Conference (EUSIPCO) Pub Date : 2015-12-28 DOI: 10.1109/EUSIPCO.2015.7362415
N. Ito, S. Araki, T. Nakatani
{"title":"Permutation-free clustering of relative transfer function features for blind source separation","authors":"N. Ito, S. Araki, T. Nakatani","doi":"10.1109/EUSIPCO.2015.7362415","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362415","url":null,"abstract":"This paper describes an application of relative transfer functions (RTFs) to underdetermined blind source separation (BSS). A clustering-based BSS approach has the advantage that it can even deal with the underdetermined case, where the sources outnumber the microphones. Among others, clustering of a normalized observation vector (NOV) has proven effective for BSS even under reverberation. We here point out that the NOV gives information about RTFs of the dominant source, and hence call it the RTF features. Most of the previous BSS methods are limited in that they undergo significant performance degradation when the number of sources is not known precisely. This paper introduces our recently developed method for joint BSS and source counting based on permutation-free clustering of the RTF features. We demonstrate the effectiveness of the method in experiments with reverberant mixtures of an unknown number of sources with a reverberation time of up to 440 ms.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133940170","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}
引用次数: 13
Combining NDHMM and phonetic feature detection for speech recognition 结合NDHMM和语音特征检测进行语音识别
2015 23rd European Signal Processing Conference (EUSIPCO) Pub Date : 2015-12-28 DOI: 10.1109/EUSIPCO.2015.7362667
T. Svendsen, Jarle Bauck Hamar
{"title":"Combining NDHMM and phonetic feature detection for speech recognition","authors":"T. Svendsen, Jarle Bauck Hamar","doi":"10.1109/EUSIPCO.2015.7362667","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362667","url":null,"abstract":"Non-negative HMM (N-HMM) [1] is a model that is well suited for modeling a mixture of e.g. audio signals, but does not have the ability to generalize to model unseen data. Non-negative durational HMM (NdHMM) has recently been proposed [2] as a modification to N-HMM that can allow for generalization, and thus make the approach suitable for automatic speech recognition. A detector-based approach to speech recognition has been studied by several researchers as an alternative to the traditional HMM approach. A bank of phonetic feature detectors will produce phonetic feature posteriors, which fit well with the non-negativity constraint of NdHMM. We review the NdHMM approach proposed in [2] and propose to extend this approach by combining NdHMM with a phonetic feature detection front-end in a tandem-like system. Experimental results of the proposed approach are presented.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133996381","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}
引用次数: 1
Efficient algorithms for ‘universally’ constrained matrix and tensor factorization 通用约束矩阵和张量分解的有效算法
2015 23rd European Signal Processing Conference (EUSIPCO) Pub Date : 2015-12-28 DOI: 10.1109/eusipco.2015.7362839
Kejun Huang, N. Sidiropoulos, A. Liavas
{"title":"Efficient algorithms for ‘universally’ constrained matrix and tensor factorization","authors":"Kejun Huang, N. Sidiropoulos, A. Liavas","doi":"10.1109/eusipco.2015.7362839","DOIUrl":"https://doi.org/10.1109/eusipco.2015.7362839","url":null,"abstract":"We propose a general algorithmic framework for constrained matrix and tensor factorization, which is widely used in unsupervised learning. The new framework is a hybrid between alternating optimization (AO) and the alternating direction method of multipliers (ADMM): each matrix factor is updated in turn, using ADMM. This combination can naturally accommodate a great variety of constraints on the factor matrices, hence the term `universal'. Computation caching and warm start strategies are used to ensure that each update is evaluated efficiently, while the outer AO framework guarantees that the algorithm converges monotonically. Simulations on synthetic data show significantly improved performance relative to state-of-the-art algorithms.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"17 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134172416","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}
引用次数: 6
A methodology for estimating the radiation pattern of a violin during the performance 估计小提琴演奏时辐射模式的一种方法
2015 23rd European Signal Processing Conference (EUSIPCO) Pub Date : 2015-12-28 DOI: 10.1109/EUSIPCO.2015.7362643
A. Canclini, Luca Mucci, F. Antonacci, A. Sarti, S. Tubaro
{"title":"A methodology for estimating the radiation pattern of a violin during the performance","authors":"A. Canclini, Luca Mucci, F. Antonacci, A. Sarti, S. Tubaro","doi":"10.1109/EUSIPCO.2015.7362643","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362643","url":null,"abstract":"We propose a method for the estimation of the three-dimensional radiation pattern of violins, during the performance of a musician. A microphone array captures the energy radiated by the violin in different directions using beamforming based on sub-arrays. The 3D radiation pattern is estimated allowing the musician to freely move. In particular, a tracking system estimates the position and orientation of the violin. The adopted system can be also used in a mildly reverberant environment, thus allowing the musician to play in a natural fashion. The experimental results prove the accuracy and the effectiveness of the method.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"79 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134196675","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}
引用次数: 5
Periodic ARMA models: Application to particulate matter concentrations 周期性ARMA模型:应用于颗粒物质浓度
2015 23rd European Signal Processing Conference (EUSIPCO) Pub Date : 2015-12-28 DOI: 10.1109/EUSIPCO.2015.7362771
A. J. Sarnaglia, V. Reisen, P. Bondon
{"title":"Periodic ARMA models: Application to particulate matter concentrations","authors":"A. J. Sarnaglia, V. Reisen, P. Bondon","doi":"10.1109/EUSIPCO.2015.7362771","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362771","url":null,"abstract":"We propose the use of multivariate version of Whittle's methodology to estimate periodic autoregressive moving average models. In the literature, this estimator has been widely used to deal with large data sets, since, in this context, its performance is similar to the Gaussian maximum likelihood estimator and the estimates are obtained much faster. Here, the usefulness of Whittle estimator is illustrated by a Monte Carlo simulation and by fitting the periodic autoregressive moving average model to daily mean concentrations of particulate matter observed in Cariacica, Brazil. The results confirm the potentiality of Whittle estimator when applied to periodic time series.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133048253","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}
引用次数: 7
Speaker localization and separation using incremental distributed expectation-maximization 使用增量分布期望最大化的说话人定位和分离
2015 23rd European Signal Processing Conference (EUSIPCO) Pub Date : 2015-12-28 DOI: 10.1109/EUSIPCO.2015.7362585
Yuval Dorfan, Dani Cherkassky, S. Gannot
{"title":"Speaker localization and separation using incremental distributed expectation-maximization","authors":"Yuval Dorfan, Dani Cherkassky, S. Gannot","doi":"10.1109/EUSIPCO.2015.7362585","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362585","url":null,"abstract":"A network of microphone pairs is utilized for the joint task of localizing and separating multiple concurrent speakers. The recently presented incremental distributed expectation-maximization (IDEM) is addressing the first task, namely detection and localization. Here we extend this algorithm to address the second task, namely blindly separating the speech sources. We show that the proposed algorithm, denoted distributed algorithm for localization and separation (DALAS), is capable of separating speakers in reverberant enclosure without a priori information on their number and locations. In the first stage of the proposed algorithm, the IDEM algorithm is applied for blindly detecting the active sources and to estimate their locations. In the second stage, the location estimates are utilized for selecting the most useful node of microphones for the subsequent separation stage. Separation is finally obtained by utilizing the hidden variables of the IDEM algorithm to construct masks for each source in the relevant node.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133869307","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}
引用次数: 10
An extended reverberation decay tail metric as a measure of perceived late reverberation 一种扩展混响衰减尾度量，用于测量可感知的晚混响
2015 23rd European Signal Processing Conference (EUSIPCO) Pub Date : 2015-12-28 DOI: 10.1109/EUSIPCO.2015.7362546
Hamza A. Javed, P. Naylor
{"title":"An extended reverberation decay tail metric as a measure of perceived late reverberation","authors":"Hamza A. Javed, P. Naylor","doi":"10.1109/EUSIPCO.2015.7362546","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362546","url":null,"abstract":"In this paper the development and evaluation of an extended Reverberation Decay Tail (RDT) metric is described. The signal-based metric predicts the perceived impact of reverberation on speech, by identifying and characterising energy decay characteristics in the signal Bark spectrum. In comparison with a previous metric, the new metric is extended to operate on wideband speech and incorporates an improved perceptual model and decay curve detection scheme. Furthermore, contributions of this work include experimental testing and validation of the metric on reverberant speech. The tests conducted show positive correlation with objective measures such as C50 as well as with subjective listening test scores. Potential applications of the measure include use as an evaluation tool for dereverberation research.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115601038","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}
引用次数: 3
The ensemble Kalman filter and its relations to other nonlinear filters 集合卡尔曼滤波器及其与其它非线性滤波器的关系
2015 23rd European Signal Processing Conference (EUSIPCO) Pub Date : 2015-12-28 DOI: 10.1109/EUSIPCO.2015.7362581
Michael Roth, C. Fritsche, Gustaf Hendeby, F. Gustafsson
{"title":"The ensemble Kalman filter and its relations to other nonlinear filters","authors":"Michael Roth, C. Fritsche, Gustaf Hendeby, F. Gustafsson","doi":"10.1109/EUSIPCO.2015.7362581","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362581","url":null,"abstract":"The Ensemble Kalman filter (EnKF) is a standard algorithm in oceanography and meteorology, where it has got thousands of citations. It is in these communities appreciated since it scales much better with state dimension n than the standard Kalman filter (KF). In short, the EnKF propagates ensembles with N state realizations instead of mean values and covariance matrices and thereby avoids the computational and storage burden of working on n × n matrices. Perhaps surprising, very little attention has been devoted to the EnKF in the signal processing community. In an attempt to change this, we present the EnKF in a Kalman filtering context. Furthermore, its application to nonlinear problems is compared to sigma point Kalman ilters and the particle ilter, so as to reveal new insights and improvements for high-dimensional filtering algorithms in general. A simulation example shows the EnKF performance in a space debris tracking application.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114158019","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}
引用次数: 20
Pipelined design of an instantaneous frequency estimation-based time-frequency optimal filter 基于瞬时频率估计的时频最优滤波器的流水线设计
2015 23rd European Signal Processing Conference (EUSIPCO) Pub Date : 2015-12-28 DOI: 10.1109/eusipco.2015.7362556
Veselin N. Ivanović, Srdjan Jovanovski, Nevena Radović
{"title":"Pipelined design of an instantaneous frequency estimation-based time-frequency optimal filter","authors":"Veselin N. Ivanović, Srdjan Jovanovski, Nevena Radović","doi":"10.1109/eusipco.2015.7362556","DOIUrl":"https://doi.org/10.1109/eusipco.2015.7362556","url":null,"abstract":"Pipelined signal adaptive hardware design of an optimal time-frequency (TF) filter has been presented. It is based on the real-time results of TF analysis and on the TF analysis-based instantaneous frequency (IF) estimation. The implemented pipelining technique allows the filter to overlap in execution unconditional steps performing in neighboring TF instants and, therefore, to significantly enhance time performance. The improvement in execution time corresponding to the one clock cycle by a TF point (i.e. even 50% in some TF points) is achieved. The design is tested on multicomponent signals and compared with the other possible IF estimation-based TF filter's designs.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114729562","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}
引用次数: 0
Acoustic direction finding in highly reverberant environment with single acoustic vector sensor 单声矢量传感器在高混响环境下的声测向
2015 23rd European Signal Processing Conference (EUSIPCO) Pub Date : 2015-12-28 DOI: 10.1109/EUSIPCO.2015.7362795
M. Aktas, Toygar Akgün, Huseyin Ozkan
{"title":"Acoustic direction finding in highly reverberant environment with single acoustic vector sensor","authors":"M. Aktas, Toygar Akgün, Huseyin Ozkan","doi":"10.1109/EUSIPCO.2015.7362795","DOIUrl":"https://doi.org/10.1109/EUSIPCO.2015.7362795","url":null,"abstract":"We propose a novel wideband acoustic direction finding method for highly reverberant environments using measurements from a single Acoustic Vector Sensor (AVS). Since an AVS is small in size and can be effectively used within the full acoustic frequency bands, the proposed solution is suitable for wideband acoustic source localization. In particular, we introduce a novel approach to extract the signal portions that are not distorted with multipath signals and noise. We do not make any stochastic and sparseness assumptions regarding the underlying signal source. Hence, our approach can be applied to a wide range of wideband acoustic signals. We present experiments with acoustic signals that are specially exposed to long reverberations, where the Signal-to-Noise Ratio is as low as 0 dB. In these experiments, the proposed method reliably estimates the source direction with less than 5 degrees of error even under the introduced significantly high reverberation conditions.","PeriodicalId":401040,"journal":{"name":"2015 23rd European Signal Processing Conference (EUSIPCO)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116052187","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}
引用次数: 4
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