<i>Real-time Adaptive Concepts in Acoustics: Blind Signal Separation and Multichannel Echo Cancellation </i>

Schobben, Daniel W. E.; Sibul, Leon H.

doi:10.1121/1.1490591

Cited by 9 publications

(9 citation statements)

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“…Our notation implies that we are only considering finite impulse response (FIR) filters for separation. Conditions on invertibility of in the context of convolutive blind source separation are discussed in [11].…”

Section: A Separation Problemmentioning

confidence: 99%

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Geometric source separation: merging convolutive source separation with geometric beamforming

Parra¹,

Alvino

2002

IEEE Trans. Speech Audio Process.

242

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Convolutive blind source separation and adaptive beamforming have a similar goal-extracting a source of interest (or multiple sources) while reducing undesired interferences. A benefit of source separation is that it overcomes the conventional cross-talk or leakage problem of adaptive beamforming. Beamforming on the other hand exploits geometric information which is often readily available but not utilized in blind algorithms. In this work we propose to join these benefits by combining cross-power minimization of second-order source separation with geometric linear constraints used in adaptive beamforming. We find that the geometric constraints resolve some of the ambiguities inherent in the independence criterion such as frequency permutations and degrees of freedom provided by additional sensors. We demonstrate the new method in performance comparisons for actual room recordings of two and three simultaneous acoustic sources.

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Section: A Separation Problemmentioning

confidence: 99%

“…The results are sorted by their relative angle along the vertical axis [12 , 18 , 19 , 25 , 33 , 37 , 38 , 41 , 50 which correspond, in Fig. 3 (top), to locations pairs (1,2), (3,4), (1,5), (1,6), (1,7), (1,8), (1,9), (1,10), and (11,12), respectively. ]…”

Section: E Performance Comparisonmentioning

confidence: 99%

Geometric source separation: merging convolutive source separation with geometric beamforming

Parra¹,

Alvino

2002

IEEE Trans. Speech Audio Process.

242

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“…If cannot be written as , the terms will appear in (32) for an arbitrary , whose FFT has not been computed previously. Since the summation in (29) is now carried out in (31) in the frequency domain, only one inverse fast Fourier transform (IFFT) is required to obtain the output vector of the actual block , by using (13). This is similar as without filter partitioning.…”

Section: A Partitioned Frequency-domain Filteringmentioning

confidence: 99%

“…With , the filters are transformed into the frequency domain. The filtering and summation in (62) and (63) are then both carried out in the frequency domain (68) (69) This has the advantage that the output vector (10) can be obtained with (13) and (14) by using only one IFFT [see Fig. 5(b)].…”

Section: Filters In Parallelmentioning

confidence: 99%

Connecting partitioned frequency-domain filters in parallel or in cascade

Joho

Moschytz

2000

IEEE Trans. Circuits Syst. II

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Abstract-The efficient implementation of connected filters is an important issue in signal processing. A typical example is the cascade of two filters, e.g., an adaptive filter with a time-invariant prefilter. The filtering and adaptation is carried out very efficiently in the frequency domain whenever filters with many coefficients are required. This is implemented as a block algorithm by using overlap-save or overlap-add techniques. However, in many real-time applications also, a short latency time through the system is required, which leads to a degradation of the computational efficiency. Partitioned frequency-domain adaptive filters, also known as multidelay adaptive filters, provide an efficient way for the filtering and adaptation with long filters maintaining short processing delays. This paper shows a computationally efficient way of implementing two or more partitioned frequency-domain filters in cascade or in parallel when their filter lengths are large. The methods presented require only one fast Fourier transform (FFT) and one inverse fast Fourier transform per input and output port, respectively. The FFT size can be even smaller than the length of the filters. The filters can be either time invariant or adaptive.Index Terms-Cascade of filters, connecting filters, filters in parallel, frequency-domain adaptive filters, multidelay adaptive filters, partitioned frequency-domain adaptive filters.

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“…The teacher is advised against using a headset, but to use a wireless microphone together with fixed speakers. This requires the need for acoustic echo cancellation (AEC), either built in in the microphone or our software implementation [9]. Finally, the personal computer itself, needs to have a 3D accelerator graphics card in order to fluently visualise the 3D environment.…”

Section: Hardware Recommendationsmentioning

confidence: 99%

A 3D Virtual Learning Environment to Foster Communication for Long Term Ill Children

Fiore

Jorissen

Vansichem

et al. 2007

Technologies for E-Learning and Digital Entertainment

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Abstract. In this paper, we present a virtual learning environment which supports the learning process of long term sick children. By focusing on 3D Virtual Environments technology chronically ill students can still be 'telepresent' in their classroom. Analysis of existing ICT-based solutions reveal weaknesses including the absence of social involvement, the high cost of developing, and mobility issues. Our system, however, is based on concrete user needs, is educational sound and relevant, and offers a scalable and affordable solution. To this end we incorporate innovative hardware, software and connectivity features, set in a user friendly user interface based on 3D technologies. We believe our system (re)establishes high quality communication between the sick children and their regular school and classroom learning environment. Furthermore, even after school pupils are attracted to meet each other in the virtual learning environment in order to communicate and share information.

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Real-time Adaptive Concepts in Acoustics: Blind Signal Separation and Multichannel Echo Cancellation

Cited by 9 publications

References 0 publications

Geometric source separation: merging convolutive source separation with geometric beamforming

Geometric source separation: merging convolutive source separation with geometric beamforming

Connecting partitioned frequency-domain filters in parallel or in cascade

A 3D Virtual Learning Environment to Foster Communication for Long Term Ill Children

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