Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Sound source localization: Conventional methods and intensity vector direction exploitation
Date
2011-01-01
Author
Günel Kılıç, Banu
Hacıhabiboğlu, Hüseyin
Metadata
Show full item record
Item Usage Stats
159
views
0
downloads
Cite This
Automatic sound source localization has recently gained interest due to its various applications that range from surveillance to hearing aids, and teleconferencing to human computer interaction. Automatic sound source localization may refer to the process of determining only the direction of a sound source, which is known as the direction-of-arrival estimation, or also its distance in order to obtain its coordinates. Various methods have previously been proposed for this purpose. Many of these methods use the time and level differences between the signals captured by each element of a microphone array. An overview of these conventional array processing methods is given and the factors that affect their performance are discussed. The limitations of these methods affecting real-time implementation are highlighted. An emerging source localization method based on acoustic intensity is explained. A theoretical evaluation of different microphone array geometries is given. Two well-known problems, localization of multiple sources and localization of acoustic reflections, are addressed.
URI
https://hdl.handle.net/11511/82478
Relation
Machine Audition Principles Algorithms and Systems
Collections
Graduate School of Informatics, Book / Book chapter
Suggestions
OpenMETU
Core
Instrument based wavelet packet decomposition for audio feature extraction
Hacıhabiboğlu, Hüseyin (null; 2001-09-10)
Feature extraction from audio data is a major concern in computer assisted music applications and content based audio retrieval. For general non-stationary signals, wavelet packet decomposition is used with entropy functions for best basis search. Musical instruments have well defined frequency ranges. Thus when audio data containing a solo instrument is concerned, wavelet packet decomposition may be adapted to that instrument's individual characteristics. The method discussed in this paper uses a number of...
Energy efficient wireless unicast routing alternatives for machine-to-machine networks
Tekbiyik, Neyre; Uysal, Elif (Elsevier BV, 2011-09-01)
Machine-to-machine (M2M) communications is a new and rapidly developing technology for large-scale networking of devices without dependence on human interaction. Energy efficiency is one of the important design objectives for machine-to-machine network architectures that often contain multihop wireless subnetworks. Constructing energy-efficient routes for sending data through such networks is important not only for the longevity of the nodes which typically depend on battery energy, but also for achieving a...
Speaker and posture classification using instantaneous acoustic features of breath signals
İlerialkan, Atı; Hacıhabiboğlui Hüseyin.; Department of Multimedia Informatics (2019)
Acoustic features extracted from speech are widely used for problems such as biometric speaker identification or first-person activity detection. However, use of speech data raises concerns about privacy due to the explicit availability of the speech content. In this thesis, we propose a method for speech and posture classification using intra-speech breathing sounds. The acoustical instantaneous side information was extracted from breath instances using the Hilbert-Huang transform. Instantaneous frequency,...
ACOUSTIC SOURCE SEPARATION USING RIGID SPHERICAL MICROPHONE ARRAYS VIA SPATIALLY WEIGHTED ORTHOGONAL MATCHING PURSUIT
Coteli, Mert Burkay; Hacıhabiboğlu, Hüseyin (2018-09-20)
Acoustic source separation refers to the extraction of individual source signals from microphone array recordings of multiple sources made in multipath environments such as rooms. The most straightforward approach to acoustic source separation involves spatial filtering via beamforming. While beamforming works well for a few sources and under low reverberation, its performance diminishes for a high number of sources and/or high reverberation. An informed acoustic source separation method based on the applic...
Information Freshness in Random Access Channels for IoT Systems
Munari, Andrea; Uysal, Elif (2021-09-20)
This paper introduces and discusses some recent advances in the field of information freshness for Internet of things (IoT) applications. Focusing on a setup in which a large number of transmitters share a common wireless channel to deliver updates to a common receiver, we tackle in particular the role played by random access policies based on variations of the basic ALOHA protocol, employed in most practical IoT systems. The fundamental trade-offs that emerge are discussed together with the enhancement ach...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
B. Günel Kılıç and H. Hacıhabiboğlu,
Sound source localization: Conventional methods and intensity vector direction exploitation
. 2011, p. 161.