DSP Implementation of Extended Infomax ICA Algorithm for Blind Source Separation

Moreno, Luz Noé Oliva; Moreno-Cadenas, J.A.; Flores-Nava, L.M.; Gómez-Castañeda, F.

doi:10.1109/iceee.2006.251932

Cited by 6 publications

(1 citation statement)

References 6 publications

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“…Previously an online (thus real-time) version for natural gradient IVA (NG-IVA) was formulated in [10] and mentioned in [11], along with various implementations of realtime (online) ICA [12,13,14] (which all have to address the permutation problem by means of various post-processing techniques). Furthermore, a batch version of Auxiliary IVA is implemented on an embedded system in the form of a smartphone application [15].…”

Section: Introductionmentioning

confidence: 99%

Real-time independent vector analysis with Student's t source prior for convolutive speech mixtures

Harris

Rivet

Naqvi

et al. 2015

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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A common approach to blind source separation is to use independent component analysis. However when dealing with realistic convolutive audio and speech mixtures, processing in the frequency domain at each frequency bin is required. As a result this introduces the permutation problem, inherent in independent component analysis, across the frequency bins. Independent vector analysis directly addresses this issue by modeling the dependencies between frequency bins, namely making use of a source prior. An alternative source prior for real-time (online) natural gradient independent vector analysis is proposed. A Student's t probability density function is known to be more suited for speech sources, due to its heavier tails, and is incorporated into a real-time version of natural gradient independent vector analysis. In addition, the importance of the degrees of freedom parameter within the Student's t distribution is highlighted. The final algorithm is realized as a real-time embedded application on a floating point Texas Instruments digital signal processor platform, where simulated recordings from a reverberant room are used for testing. Results are shown to be better than with the original (super-Gaussian) source prior.

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Section: Introductionmentioning

confidence: 99%

Real-time independent vector analysis with Student's t source prior for convolutive speech mixtures

Harris

Rivet

Naqvi

et al. 2015

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Real-time blind audio source separation: performance assessment on an advanced digital signal processor

Pani

Raffo

2014

J Supercomput

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Many on-line blind audio source separation (BASS) algorithms have been presented so far to the scientific community, but only a few of them have been evaluated in terms of their real-time performance. In this paper we consider a well-established BASS method (oriented to voices separation) evaluating its performance in terms of separation quality allowed by a real-time embedded computing implementation, also considering novel and state-of-the-art improvements to the it. To this aim, the algorithm has been implemented and ported for real-time execution onto an advanced low-power digital signal processor targeted for complex-domain applications. The optimized embedded implementation is able to perform up to five iterations of the gradient for any input frame of data, achieving good separation levels (up to 11.8 dB of signal to interference ratio on custom recording in real environments). The proposed solution doubles the performance of a C-optimized version running on a traditional PC processor, achieving a better separation result with lower power requirement

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FPGA implementation of blind source separation using a novel ICA algorithm

vinita

Somani

Manikandan

2017

2017 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia)

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DSP Implementation of Extended Infomax ICA Algorithm for Blind Source Separation

Cited by 6 publications

References 6 publications

Real-time independent vector analysis with Student's t source prior for convolutive speech mixtures

Real-time independent vector analysis with Student's t source prior for convolutive speech mixtures

Real-time blind audio source separation: performance assessment on an advanced digital signal processor

FPGA implementation of blind source separation using a novel ICA algorithm

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