Results 1 - 10
of
41
Oracle estimators for the benchmarking of source separation algorithms
- Queen Mary, University of London
, 2006
"... ..."
(Show Context)
A SURVEY OF CONVOLUTIVE BLIND SOURCE SEPARATION METHODS
- SPRINGER HANDBOOK ON SPEECH PROCESSING AND SPEECH COMMUNICATION
"... In this chapter, we provide an overview of existing algorithms for blind source separation of convolutive audio mixtures. We provide a taxonomy, wherein many of the existing algorithms can be organized, and we present published results from those algorithms that have been applied to real-world audio ..."
Abstract
-
Cited by 39 (0 self)
- Add to MetaCart
In this chapter, we provide an overview of existing algorithms for blind source separation of convolutive audio mixtures. We provide a taxonomy, wherein many of the existing algorithms can be organized, and we present published results from those algorithms that have been applied to real-world audio separation tasks.
Undercomplete blind subspace deconvolution
- JMLR
, 2007
"... We introduce the blind subspace deconvolution (BSSD) problem, which is the extension of both the blind source deconvolution (BSD) and the independent subspace analysis (ISA) tasks. We examine the case of the undercomplete BSSD (uBSSD). Applying temporal concatenation we reduce this problem to ISA. T ..."
Abstract
-
Cited by 26 (18 self)
- Add to MetaCart
(Show Context)
We introduce the blind subspace deconvolution (BSSD) problem, which is the extension of both the blind source deconvolution (BSD) and the independent subspace analysis (ISA) tasks. We examine the case of the undercomplete BSSD (uBSSD). Applying temporal concatenation we reduce this problem to ISA. The associated ‘high dimensional ’ ISA problem can be handled by a recent technique called joint f-decorrelation (JFD). Similar decorrelation methods have been used previously for kernel independent component analysis (kernel-ICA). More precisely, the kernel canonical correlation (KCCA) technique is a member of this family, and, as is shown in this paper, the kernel generalized variance (KGV) method can also be seen as a decorrelation method in the feature space. These kernel based algorithms will be adapted to the ISA task. In the numerical examples, we (i) examine how efficiently the emerging higher dimensional ISA tasks can be tackled, and (ii) explore the working and advantages of the derived kernel-ISA methods.
Probabilistic modeling paradigms for audio source separation
- In Machine Audition: Principles, Algorithms and Systems. IGI Global
, 2010
"... Most sound scenes result from the superposition of several sources, which can be separately perceived and analyzed by human listeners. Source separation aims to provide machine listeners with similar skills by extracting the sounds of individual sources from a given scene. Existing separation system ..."
Abstract
-
Cited by 25 (14 self)
- Add to MetaCart
(Show Context)
Most sound scenes result from the superposition of several sources, which can be separately perceived and analyzed by human listeners. Source separation aims to provide machine listeners with similar skills by extracting the sounds of individual sources from a given scene. Existing separation systems operate either by emulating the human auditory system or by inferring the parameters of probabilistic sound models. In this chapter, we focus on the latter approach and provide a joint overview of established and recent models, including independent component analysis, local time-frequency models and spectral template-based models. We show that most models are instances of one of the following two general paradigms: linear modeling or variance modeling. We compare the merits of either paradigm and report objective performance figures. We conclude by discussing promising combinations of probabilistic priors and inference algorithms that could form the basis of future state-of-the-art systems.
Blind source separation based on time-domain optimization of a frequency-domain independence criterion
- IEEE TRANS. AUDIO, SPEECH, LANGUAGE PROCESS
, 2006
"... A new technique for the blind separation of convolutive mixtures is proposed in this paper. Inspired by the works of Amari, Sabala, and Rahbar, we firstly start from the application of Kullback–Leibler divergence in frequency domain, and then we integrate Kullback–Leibler divergence over the whole ..."
Abstract
-
Cited by 9 (5 self)
- Add to MetaCart
A new technique for the blind separation of convolutive mixtures is proposed in this paper. Inspired by the works of Amari, Sabala, and Rahbar, we firstly start from the application of Kullback–Leibler divergence in frequency domain, and then we integrate Kullback–Leibler divergence over the whole frequency range of interest to yield a new objective function which turns out to be time-domain variable dependent. In other words, the objective function is derived in frequency domain which can be optimized with respect to time domain variables. The proposed technique has the advantages of frequency domain approaches and is suitable for very long mixing channels, but does not suffer from the local permutation problem as the separation is achieved in time-domain.
Batch and adaptive PARAFAC-based blind separation of convolutive speech mixtures
- IEEE Audio, Speech, Language Process
, 2010
"... ..."
(Show Context)
Audio Source Separation: Solutions and Problems
, 2002
"... this paper, the authors review the methods based around Independent Component Analysis (ICA), discussing the various choices available in algorithm design. We then explore the issue of sensitivity to speaker movement which appears to impose fundamental limitations on BSS performance ..."
Abstract
-
Cited by 8 (0 self)
- Add to MetaCart
this paper, the authors review the methods based around Independent Component Analysis (ICA), discussing the various choices available in algorithm design. We then explore the issue of sensitivity to speaker movement which appears to impose fundamental limitations on BSS performance
Robust cross-correlation-based methods for sound-source localization and separation using a large-aperture microphone array
, 2011
"... Microphone arrays have been used in many applications, such as: teleconferencing, speech recognition, talker characterization, speech enhancement, source localization and separation, etc. Despite the fast-paced development in microphone-array hardware, software and algorithms, there still exist nume ..."
Abstract
-
Cited by 5 (0 self)
- Add to MetaCart
Microphone arrays have been used in many applications, such as: teleconferencing, speech recognition, talker characterization, speech enhancement, source localization and separation, etc. Despite the fast-paced development in microphone-array hardware, software and algorithms, there still exist numerous challenges for microphonearray processing. A few of these are: Real-time issues, efficient and effective algorithms to deal with a variety of environments and noisy conditions. This thesis is concerned with effective and efficient algorithms for the tasks of sound-source localization and separation, using a large-aperture microphone array in an adverse environment. The phase transform (PHAT) has been shown experimentally to cope effectively with the reverberation noise, which is the main challenge in most environments. In this thesis, first, an analytic solution of the steered response power using the phase transform (SRP-PHAT) is derived to explain the robustness of the PHAT against reverberation.
Controlled Complete ARMA Independent Process Analysis
"... Abstract—In this paper we address the controlled complete ..."
Abstract
-
Cited by 3 (2 self)
- Add to MetaCart
(Show Context)
Abstract—In this paper we address the controlled complete
Determined source separation for microphone recordings using IIR filters
- in 129th Convention of the Audio Engineering Society
, 2010
"... The papers at this Convention have been selected on the basis of a submitted abstract and extended precis that have been peer reviewed by at least two qualified anonymous reviewers. This convention paper has been reproduced from the author’s advance manuscript, without editing, corrections, or consi ..."
Abstract
-
Cited by 3 (3 self)
- Add to MetaCart
(Show Context)
The papers at this Convention have been selected on the basis of a submitted abstract and extended precis that have been peer reviewed by at least two qualified anonymous reviewers. This convention paper has been reproduced from the author’s advance manuscript, without editing, corrections, or consideration by the Review Board. The AES takes no responsibility for the contents. Additional papers may be obtained by sending request and remittance to Audio
