Measurement Combination for Acoustic Source Localization in a Room Environment

Pertilä, Pasi; Korhonen, Teemu; Visa, Ari

doi:10.1155/2008/278185

Cited by 25 publications

(22 citation statements)

References 23 publications

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“…A good example of this decision is presented in [37] where, assuming there are only two sound sources in a meeting room, the beamforming technique 'decides' which sound source is assigned to which sound source class. These decisions are carried out at specific intervals, with which several methodologies can be employed for tracking purposes, such as Kalman filters [18] or particle filtering [38]. Another technique that is somewhat related to this type of approach, discussed and refined in [39], is known as the position-pitch (PoPi) plane, where, instead of mapping energy values onto the directional plane, a pitch spectrum is estimated per direction, providing possibilities to jointly estimate the DOA and pitch of sound sources, which, in turn, provides additional information to locate more than one source in the same direction.…”

Section: Amount Of Microphones Employed Vs Number Of Sources Estimatedmentioning

confidence: 99%

Lightweight multi-DOA tracking of mobile speech sources

Rascón

Fuentes

Meza

2015

J AUDIO SPEECH MUSIC PROC.

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Estimating the directions of arrival (DOAs) of multiple simultaneous mobile sound sources is an important step for various audio signal processing applications. In this contribution, we present an approach that improves upon our previous work that is now able to estimate the DOAs of multiple mobile speech sources, while being light in resources, both hardware-wise (only using three microphones) and software-wise. This approach takes advantage of the fact that simultaneous speech sources do not completely overlap each other. To evaluate the performance of this approach, a multi-DOA estimation evaluation system was developed based on a corpus collected from different acoustic scenarios named Acoustic Interactions for Robot Audition (AIRA).

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Section: Amount Of Microphones Employed Vs Number Of Sources Estimatedmentioning

confidence: 99%

Lightweight multi-DOA tracking of mobile speech sources

Rascón

Fuentes

Meza

2015

J AUDIO SPEECH MUSIC PROC.

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“…GCC, GCC-PHAT, Moddemeijer information theoretic delay criterion (MODD), and cochlear filtering (COCH), were compared in [15]. Other existing TDE algorithms include the use of linear interpolation and multichannel cross correlation coefficient (MCCC) [17], maximum-likelihood approach [24], crosspower spectrum phase analysis [25], creation of a new spatial likelihood function by combining operation [26], and weighting of GCC for weakening the effects of noise [8]. The performance of TDE is significantly affected by room reverberation and noise.…”

Section: A Review On Acoustic Source Localizationmentioning

confidence: 99%

Speaker tracking module for indoor robot navigation

Teachasrisaksakul

Iemcha-od

Thiemjarus

et al. 2012

2012 9th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technolog

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The goal of this study is to equip a mobile service robot with an ability to navigate to the human who commands the robot by speech. This paper proposes a Bayesian approach to sound source localization for speaker tracking module. Based on time delay of arrival (TDOA) features, sound source direction is classified using a naïve Bayesian network. The method requires low computational complexity and is feasible for real-time robot navigation. Based on an experiment with various parameter settings in an indoor environment, different factors that affect the classification accuracy have been analyzed. Further validation on a human speaker with random sound volumes and positions illustrates that the proposed method can work efficiently in real-world environments.

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“…Particle filtering methods dominate the audio source tracking literature (Lehmann & Johansson, 2007;Li & Ser, 2010;Pertilä et al, 2008;Talantzis et al, 2009). The seminal work of Ward et.…”

Section: Related Workmentioning

confidence: 99%

Camera Pointing with Coordinate-Free Localization and Tracking

Ettinger¹,

Freund²

2011

Advances in Sound Localization

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where c is the speed of sound in the medium. ∆ ij is often called the time delay of arrival (TDOA) between microphone i and j. It is worth noting that if f is the sampling rate being used, then the largest the TDOA can be in terms of audio samples is M = m i − m j 2 f /c. In other words, ∆ ij is always in the range [−M, M] and in practice can only be estimated to the nearest sample. This observation directly reveals the fact that close together microphones cannot have as wide a range of TDOAs as microphones that are spaced further apart. Placing microphones further 318 Advances in Sound Localization

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Measurement Combination for Acoustic Source Localization in a Room Environment

Cited by 25 publications

References 23 publications

Lightweight multi-DOA tracking of mobile speech sources

Lightweight multi-DOA tracking of mobile speech sources

Speaker tracking module for indoor robot navigation

Camera Pointing with Coordinate-Free Localization and Tracking

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