Towards real-time source counting by estimation of coherent-to-diffuse ratios from ad-hoc microphone array recordings

Pasha, Shahab; Donley, Jacob; Ritz, Christian; Zou, Yue

doi:10.1109/hscma.2017.7895582

Cited by 5 publications

(4 citation statements)

References 17 publications

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“…Moonen and Bertrand [86] suggested a multi-speaker voice activity detection method that tracks the power of multiple simultaneous speakers. Coherent-to-diffuse ratio (CDR) values (32) calculated or estimated at dual microphone node locations are also applied for source counting [56].…”

Section: Source Counting and Crosstalk Detectionmentioning

confidence: 99%

See 1 more Smart Citation

Distributed Microphone Arrays, Emerging Speech and Audio Signal Processing Platforms: A Review

Pasha¹,

Lundgren²,

Ritz³

et al. 2020

Adv. sci. technol. eng. syst. j.

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Given ubiquitous digital devices with recording capability, distributed microphone arrays are emerging recording tools for hands-free communications and spontaneous tele-conferencings. However, the analysis of signals recorded with diverse sampling rates, time delays, and qualities by distributed microphone arrays is not straightforward and entails important considerations. The crucial challenges include the unknown/changeable geometry of distributed arrays, asynchronous recording, sampling rate mismatch, and gain inconsistency. Researchers have recently proposed solutions to these problems for applications such as source localization and dereverberation, though there is less literature on real-time practical issues. This article reviews recent research on distributed signal processing techniques and applications. New applications benefitting from the wide coverage of distributed microphones are reviewed and their limitations are discussed. This survey does not cover partially or fully connected wireless acoustic sensor networks.

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Section: Source Counting and Crosstalk Detectionmentioning

confidence: 99%

“…The main limitation of the method proposed by Pasha et al [56] is that all the nodes must be of the same structure, which limits the method's applicability. The MSC is found using the cross-power spectral density (CPSD) as presented by Pasha et al [87] (Figure 4):…”

Section: Source Counting and Crosstalk Detectionmentioning

confidence: 99%

Distributed Microphone Arrays, Emerging Speech and Audio Signal Processing Platforms: A Review

Pasha¹,

Lundgren²,

Ritz³

et al. 2020

Adv. sci. technol. eng. syst. j.

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“…In this research statistical cues, Kurtosis and Skewness [17], derived from the single channel LP residual signals are applied as the distance estimates. Compared with acoustic features such as Magnitude Squared Coherence (MSC) which requires dual-channel microphones of the same structure [18,19], the applied statistical features are applicable to any microphone type.…”

Section: Distance Cues For Ad-hoc Microphonesmentioning

confidence: 99%

“…Also a spatially modified beamformer is proposed and applied for the AR modelling and compression of the source signal through the joint analysis of reverberant multi-channel ad-hoc recordings. The applied statistical distance [16] and reverberation level cues [17] proposed in this work are applicable to microphones with inconsistent gains and do not require identical dual-channel microphones [18,19]. The target application of this research is the speech compression for the immersive meeting scenarios [20] where the microphones do not form a fully connected Wireless Acoustic Sensor Network (WASN) and the participants have their independent recording device and microphone.…”

Section: Introductionmentioning

confidence: 99%

Multi-Channel Compression and Coding of Reverberant Ad-Hoc Recordings Through Spatial Autoregressive Modelling

Pasha

Lundgren

2019

2019 30th Irish Signals and Systems Conference (ISSC)

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Autoregressive modelling techniques such as multi-channel linear prediction are widely used for applications such as coding, dereverberation and compression of the speech signals. State of the art multi-channel linear prediction methods do not take into account the spatial locations of the microphones and assume single distance compact microphone arrays. In this paper a spatially modified multichannel autoregressive compression and coding method is proposed and successfully tested in order to adapt the standard multi-channel method to the virtual reality and immersive video conferencing applications where the microphones can be meters away from each other. The proposed method estimates the spatial distances between each microphone and the source to optimise the joint compression of the microphones covering a wide area. The results suggest that the proposed method outperforms the standard multi-channel compression and coding method when applied to the ad-hoc scenarios.

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Blind speaker counting in highly reverberant environments by clustering coherence features

Pasha

Donley

Ritz

2017

2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)

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Towards real-time source counting by estimation of coherent-to-diffuse ratios from ad-hoc microphone array recordings

Cited by 5 publications

References 17 publications

Distributed Microphone Arrays, Emerging Speech and Audio Signal Processing Platforms: A Review

Distributed Microphone Arrays, Emerging Speech and Audio Signal Processing Platforms: A Review

Multi-Channel Compression and Coding of Reverberant Ad-Hoc Recordings Through Spatial Autoregressive Modelling

Blind speaker counting in highly reverberant environments by clustering coherence features

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