Adaptive Time Delay Estimation Using Filter Length Constraints for Source Localization in Reverberant Acoustic Environments

Salvati, Daniele; Canazza, Sergio

doi:10.1109/lsp.2013.2253319

Cited by 25 publications

(14 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…-de-noise (and de-crack, de-hiss, de-click) tools, allowing the users to improve the SNR of audio signals. The algorithms described in [13,16,33] will be considered (if the audio documents are recorded in a live scenario, using microphone arrays, see [42,43]); -machine learning techniques to automatically find the correct equalization curve.…”

Section: Discussionmentioning

confidence: 99%

Tape music archives: from preservation to access

et al. 2017

Self Cite

View full text Add to dashboard Cite

This article presents a methodology for the active preservation of, and the access to, magnetic tapes of audio archives. The methodology has been defined and implemented by a multidisciplinary team involving engineers as well as musicians, composers and archivists. The strong point of the methodology is the philological awareness that influenced the development of digital tools, which consider the critical questions in the historian and musicologist’s approach: the secondary information and the history of transmission of an audio document

show abstract

Section: Discussionmentioning

confidence: 99%

Tape music archives: from preservation to access

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…Due to the advantages of lower complexity, GCC is often used in real-time system. In this paper, the M-CPSP algorithm is used to estimate time delay, which has advantages of higher accuracy of time delay estimation in noisy and reverberant environments and low complexity, then calculates the sound source localization based on time delay and the cross array model with four microphones [3].…”

Section: @Qqcommentioning

confidence: 99%

Research and implementation on a real-time microphone array sound source localization system

Peng¹,

Wu²,

Luo³

et al. 2013

Proceedings of 3rd International Conference on Multimedia Technology(ICMT-13)

View full text Add to dashboard Cite

To carry out a real-time sound source localization system with a small amount of microphones, a specific implementation method is presented in this paper. This method comprises two steps: time delay estimation and position calculation. Firstly, the modified cross power spectrum phase algorithm (M-CPSP) is applied to time delay estimation, which has higher precision of time delay estimation in real-time environments. Moreover, the cross array model with four microphones is applied to this system and sound source position is calculated by the geometrical relationship between the spatial coordinates of four microphones and time delay. Experimental results show that the M-CPSP algorithm has a high accuracy of time delay estimation in strong noisy and reverberant environments and the error of distance positioning is less than ±25cm, the error of angle positioning is less than ±5 o , which meets the needs of practical application.

show abstract

“…Since the classic article on TDOA written by Knapp and Carter was published in 1976, this problem has perpetually been a research focus in the field of international signal processing (Knapp et al, 1976). The common method of TDOA includes the generalized cross correlation method (Knapp et al, 1976;Souden et al, 2010;Jin et al, 2013), the phase spectrum estimation method (Youn et al, 1982;Qiu et al, 2012), the generalized bi-spectral estimation method (Hinich et al, 1992;Hou et al, 2013), the adaptive estimation method (Gedalyahu et al, 2010;Salvati and Canazza, 2013), the energy method based on HilbertHuang transform and so on. These methods have been widely used in many fields.…”

Section: Introductionmentioning

confidence: 99%

Time difference of arrival estimation of microseismic signals based on alpha-stable distribution

Jia

Gong

Peng

et al. 2018

Nonlin. Processes Geophys.

View full text Add to dashboard Cite

Abstract. Microseismic signals are generally considered to follow the Gauss distribution. A comparison of the dynamic characteristics of sample variance and the symmetry of microseismic signals with the signals which follow α-stable distribution reveals that the microseismic signals have obvious pulse characteristics and that the probability density curve of the microseismic signal is approximately symmetric. Thus, the hypothesis that microseismic signals follow the symmetric α-stable distribution is proposed. On the premise of this hypothesis, the characteristic exponent α of the microseismic signals is obtained by utilizing the fractional low-order statistics, and then a new method of time difference of arrival (TDOA) estimation of microseismic signals based on fractional low-order covariance (FLOC) is proposed. Upon applying this method to the TDOA estimation of Ricker wavelet simulation signals and real microseismic signals, experimental results show that the FLOC method, which is based on the assumption of the symmetric α-stable distribution, leads to enhanced spatial resolution of the TDOA estimation relative to the generalized cross correlation (GCC) method, which is based on the assumption of the Gaussian distribution.

show abstract

Adaptive Time Delay Estimation Using Filter Length Constraints for Source Localization in Reverberant Acoustic Environments

Cited by 25 publications

References 6 publications

Tape music archives: from preservation to access

Tape music archives: from preservation to access

Research and implementation on a real-time microphone array sound source localization system

Time difference of arrival estimation of microseismic signals based on alpha-stable distribution

Contact Info

Product

Resources

About