Title
A novel biologically inspired neural network solution for robotic 3D sound source sensing
Abstract
This paper presents a novel real-time robotic binaural sound localization method based on hierarchical fuzzy artificial neural networks and a generic set of head related transfer functions. The robot is a humanoid equipped with the KEMAR artificial head and torso. Inside the ear canals two small microphones play the role of the eardrums in collecting the impinging sound waves. The neural networks are trained using synthesized sound sources placed every 5° from 0° to 255° in azimuth, and every 5° from ¿ 45° to 80° in elevation. To improve generalization, the training data was corrupted with noise. Thanks to fuzzy logic, the method is able to interpolate at its output, locating with high accuracy sound sources at positions which were not used for training, even in presence of strong distortion. In order to achieve high localization accuracy, two different binaural cues are combined, namely the interaural intensity differences and interaural time differences. As opposed to microphone-array methods, the presented technique, uses only two microphones to localize sound sources in a real-time 3D environment.
Year
DOI
Venue
2008
10.1007/s00500-007-0249-9
Soft Comput.
Keywords
Field
DocType
hierarchical fuzzy artificial neural,sound localization method,back-propagation,impinging sound wave,localization accuracy,uses only two microphones to loca- lize sound sources in a real-time 3d environment. keywords binaural hearing · robotic sound localization · fuzzy neural networks · back-propagation · hrtf,hrtf,different binaural cue,namelytheinterauralintensitydifferencesandinteraural time differences. as opposed to microphone-array methods,high localization accuracy,the presented technique,neural network solution,fuzzy logic,fuzzy neural networks,novel biologically,binaural hearing,sound source,kemar artificial head,robotic sound localization,two different binaural cues are combi- ned,synthesized sound source,high accuracy sound source,fuzzy neural network,real time,sound localization,interaural time difference,head related transfer function,artificial neural network,back propagation,neural network
Head-related transfer function,Computer science,Azimuth,Artificial intelligence,Artificial neural network,Distortion,Computer vision,Fuzzy logic,Speech recognition,Sound localization,Backpropagation,Binaural recording,Machine learning
Journal
Volume
Issue
ISSN
12
7
1433-7479
Citations 
PageRank 
References 
1
0.36
8
Authors
2
Name
Order
Citations
PageRank
Fakheredine Keyrouz1507.19
Klaus Diepold243756.47