Real-time super-resolution Sound Source Localization for robots

Nakamura, Keisuke; Nakadai, Kazuhiro; İnce, Gökhan

doi:10.1109/iros.2012.6385494

Cited by 57 publications

(25 citation statements)

References 15 publications

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“…As a solution, the GSVD-MUSIC (Generalized Singular Value Decomposition-MUSIC) is proposed in [69]. As indicated by its name, it mainly relies on a generalized singular value decomposition, which consists in determining the left and right singular vectors U l and U r respectively, together with Λ = diag(λ 1 , .…”

Section: Musicmentioning

confidence: 99%

“…Once this decomposition is performed, the algorithm remains identical, with the left singular vectors and their corresponding singular values being used for the separation between the signal and noise spaces [69]. At the end, GSVD is shown to be computed almost 3 times quicker than GEVD, which is a critical improvement for real-time applications.…”

Section: Musicmentioning

confidence: 99%

“…But computing the pseudo-spectrum at each candidate source position can result in a high computational costs. A hierarchical strategy with a coarse-to-fine approach is proposed in [69] to solve this issue. Another hidden point concerns the source number, which must be known before identifying the noise and signal spaces, and thus before determining the broadband pseudo-spectrum.…”

Section: Musicmentioning

confidence: 99%

See 2 more Smart Citations

A survey on sound source localization in robotics: From binaural to array processing methods

Argentieri

Danès

Souères

2015

Computer Speech & Language

133

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This paper attempts to provide a state-of-the-art of sound source localization in Robotics. Noticeably, this context raises original constraints-e.g. embeddability, real time, broadband environments, noise and reverberation-which are seldom simultaneously taken into account in Acoustics or Signal Processing. A comprehensive review is proposed of recent robotics achievements, be they binaural or rooted in Array Processing techniques. The connections are highlighted with the underlying theory as well as with elements of physiology and neurology of human hearing.

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Section: Musicmentioning

confidence: 99%

Section: Musicmentioning

confidence: 99%

Section: Musicmentioning

confidence: 99%

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A survey on sound source localization in robotics: From binaural to array processing methods

Argentieri

Danès

Souères

2015

Computer Speech & Language

133

View full text Add to dashboard Cite

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“…• The Audio-only dataset: in the laboratory, the speech recording from the TIMIT dataset [32] In both of these two datasets, the external noise is much lower than the fan noise, thence noise in the recorded signal is almost composed of the fan noise. The signal to noise ratios (SNR) are approximately 14 dB, 11 dB for Audio-only dataset with 1.1 m and 2.5 m robot-to-source distance, respectively, and 2 dB for audio-visual dataset 2 . As mentioned in Section III-C, the fan noise PSD φ vv (p, k) and ϕ wv (p, k) are precomputed.…”

Section: A the Datasetsmentioning

confidence: 99%

Reverberant sound localization with a robot head based on direct-path relative transfer function

Girin

Badeig

et al. 2016

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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This paper addresses the problem of sound-source localization (SSL) with a robot head, which remains a challenge in real-world environments. In particular we are interested in locating speech sources, as they are of high interest for humanrobot interaction. The microphone-pair response corresponding to the direct-path sound propagation is a function of the source direction. In practice, this response is contaminated by noise and reverberations. The direct-path relative transfer function (DP-RTF) is defined as the ratio between the directpath acoustic transfer function (ATF) of the two microphones, and it is an important feature for SSL. We propose a method to estimate the DP-RTF from noisy and reverberant signals in the short-time Fourier transform (STFT) domain. First, the convolutive transfer function (CTF) approximation is adopted to accurately represent the impulse response of the microphone array, and the first coefficient of the CTF is mainly composed of the direct-path ATF. At each frequency, the frame-wise speech auto-and cross-power spectral density (PSD) are obtained by spectral subtraction. Then a set of linear equations is constructed by the speech auto-and cross-PSD of multiple frames, in which the DP-RTF is an unknown variable, and is estimated by solving the equations. Finally, the estimated DP-RTFs are concatenated across frequencies and used as a feature vector for SSL. Experiments with a robot, placed in various reverberant environments, show that the proposed method outperforms two state-of-the-art methods.

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“…Most of these approaches have been implemented on robots [13], [14], [15] and used to estimate the source AoA in a similar way as with a static microphone array. Robots can actually provide more information by exploiting motion: this is known as active audition.…”

Section: Introductionmentioning

confidence: 99%

Localizing an intermittent and moving sound source using a mobile robot

Nguyen

Colas

Charpillet

2016

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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This paper addresses the problem of localizing and tracking one intermittent, moving sound source using a microphone array on a mobile robot. Robot motion provides a solution for estimating the distance to the source and avoiding front-back ambiguity. We propose a mixture Kalman filter (MKF) framework in order to fuse the robot motion information and the measurements taken at different poses of the robot. Experiments and statistical results demonstrate the ability of the proposed method to track one intermittent sound source in a reverberant environment where false measurements of the source angle of arrival (AoA) and the source activity often occur compared to a method that does not consider tracking source activity into account.

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Real-time super-resolution Sound Source Localization for robots

Cited by 57 publications

References 15 publications

A survey on sound source localization in robotics: From binaural to array processing methods

A survey on sound source localization in robotics: From binaural to array processing methods

Reverberant sound localization with a robot head based on direct-path relative transfer function

Localizing an intermittent and moving sound source using a mobile robot

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