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13
Simultaneous localization of multiple sound sources using blind adaptive MIMO filtering
- In IEEE Int. Conf. Acoustics, Speech, Signal Processing (ICASSP
, 2005
"... Abstract — The TDOA-based acoustic source localization approach is a powerful and widely-used method which can be applied for one source in several dimensions or several sources in one dimension. However the localization turns out to be more challenging when multiple sound sources should be localize ..."
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Cited by 36 (17 self)
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Abstract — The TDOA-based acoustic source localization approach is a powerful and widely-used method which can be applied for one source in several dimensions or several sources in one dimension. However the localization turns out to be more challenging when multiple sound sources should be localized in multiple dimensions, due to a spatial ambiguity phenomenon which requires to perform an intermediate step after the TDOA estimation and before the calculation of the geometrical source positions. In order to obtain the required set of TDOA estimates for the multidimensional localization of multiple sound sources, we apply a recently presented TDOA estimation method based on blind adaptive multiple-input-multiple-output (MIMO) system identification. We demonstrate that this localization method also provides valuable side information which allows us to resolve the spatial ambiguity without any prior knowledge about the source positions. Furthermore we show that the blind adaptive MIMO system identification allows a high spatial resolution. Experimental results for the localization of two sources in a two-dimensional plane show the effectiveness of the proposed scheme. I.
A real-time blind source separation scheme and its application to reverberant and noisy acoustic environments
, 2006
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SEPARATING CONVOLUTIVE MIXTURES WITH TRINICON
"... Blind source separation (BSS) algorithms are often categorized as either narrowband or broadband algorithms depending on whether their respective cost functions aim at individual DFT bins or the entire broadband signal. In this contribution, we present comparable general natural gradient-based formu ..."
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Cited by 3 (0 self)
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Blind source separation (BSS) algorithms are often categorized as either narrowband or broadband algorithms depending on whether their respective cost functions aim at individual DFT bins or the entire broadband signal. In this contribution, we present comparable general natural gradient-based formulations of both concepts based on the TRINICON framework. As a distinctive feature, narrowband algorithms imply an internal permutation and scaling problem. We show that the common DOA estimation-based methods for aligning the permutations effectively rely on geometric a-priori knowledge, and we explain why they need to be complemented by additional repair mechanisms for robust BSS. The latter can already be viewed as approximations of the generic TRINICON broadband algorithm. As a conclusion, we propose to always use a generic broadband algorithm as a starting point for the design of new BSS algorithms. 1.
Acoustic Echo Cancellation for Multiple Reproduction Channels: From First Principles to Real-Time Solutions
"... Multichannel acoustic echo cancellation (MCAEC) is a key technology whenever hands-free and full-duplex communication in modern systems with multichannel sound reproduction is desired. Although the basic principle of echo cancellation has been well known for several decades, the multichannel case po ..."
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Cited by 2 (1 self)
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Multichannel acoustic echo cancellation (MCAEC) is a key technology whenever hands-free and full-duplex communication in modern systems with multichannel sound reproduction is desired. Although the basic principle of echo cancellation has been well known for several decades, the multichannel case poses some additional and fundamentally different challenges. Moreover, there are even some notable differences between the two-channel case and the general multichannel case which has been addressed bit by bit only in recent years. The aim of this paper is twofold. On the one hand, after a brief review of the problem of multichannel acoustic echo cancellation, this paper gives an outline of how the problem may be tackled based on some fundamental principles. In this sense, the presentation in this paper brings together for the first time ideas from system theory, information theory, psychoacoustics, and also wave physics. Based on this framework, and as the other main contribution, we present in this paper some recent advances in the field of MCAEC. Thereby, important issues in the case of more than two channels are emphasized. Finally, as an outlook, we touch on our ongoing work towards MCAEC for massive multichannel sound reproduction, such as wave field synthesis. 1
‘Shadow BSS ’ for Blind Source Separation in Rapidly Time-Varying Acoustic Scenes
"... Abstract. This paper addresses the tracking capability of blind source separation algorithms for rapidly time-varying sensor or source positions. Based on a known algorithm for blind source separation, which also allows for simultaneous localization of multiple active sources in reverberant environm ..."
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Cited by 1 (1 self)
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Abstract. This paper addresses the tracking capability of blind source separation algorithms for rapidly time-varying sensor or source positions. Based on a known algorithm for blind source separation, which also allows for simultaneous localization of multiple active sources in reverberant environments, the source separation performance will be investigated for abrupt microphone array rotations representing the worst case. After illustrating the deficiencies in source-tracking with the given efficient implementation of the BSS algorithm, a method to ensure robust source separation even with abrupt microphone array rotations is proposed. Experimental results illustrate the efficiency of the proposed concept. 1
State-of-the-art overview Localization and Tracking of Multiple Interlocutors with Multiple Sensors
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POST-PROCESSING FOR BSS ALGORITHMS TO RECOVER SPATIAL CUES
"... This paper addresses the problem of recovering spatial cues after microphone array processing by blind source separation. Based on the known demixing system determined by the blind source separation, we derive two spatialization algorithms. One algorithm exploits the inverse of the demixing system, ..."
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This paper addresses the problem of recovering spatial cues after microphone array processing by blind source separation. Based on the known demixing system determined by the blind source separation, we derive two spatialization algorithms. One algorithm exploits the inverse of the demixing system, while the other algorithm exploits the adjoint of the demixing system. Both algorithms are evaluated by objective and subjective measures. We therefore consider the recovered time difference of arrival and the subjective perception of the spatialized signals. 1.
