Localizing Bird Songs Using an Open Source Robot Audition System with a Microphone Array

Author(s):  
Reiji Suzuki ◽  
Shiho Matsubayashi ◽  
Kazuhiro Nakadai ◽  
Hiroshi G. Okuno
2017 ◽  
Vol 29 (1) ◽  
pp. 213-223 ◽  
Author(s):  
Reiji Suzuki ◽  
◽  
Shiho Matsubayashi ◽  
Richard W. Hedley ◽  
Kazuhiro Nakadai ◽  
...  

[abstFig src='/00290001/20.jpg' width='300' text='Bird songs recorded and localized by HARKBird' ] Understanding auditory scenes is important when deploying intelligent robots and systems in real-world environments. We believe that robot audition can better recognize acoustic events in the field as compared to conventional methods such as human observation or recording using single-channel microphone array. We are particularly interested in acoustic interactions among songbirds. Birds do not always vocalize at random, for example, but may instead divide a soundscape so that they avoid overlapping their songs with those of other birds. To understand such complex interaction processes, we must collect much spatiotemporal data in which multiple individuals and species are singing simultaneously. However, it is costly and difficult to annotate many or long recorded tracks manually to detect their interactions. In order to solve this problem, we are developing HARKBird, an easily-available and portable system consisting of a laptop PC with open-source software for robot audition HARK (Honda Research Institute Japan Audition for Robots with Kyoto University) together with a low-cost and commercially available microphone array. HARKBird enables us to extract the songs of multiple individuals from recordings automatically. In this paper, we introduce the current status of our project and report preliminary results of recording experiments in two different types of forests – one in the USA and the other in Japan – using this system to automatically estimate the direction of arrival of the songs of multiple birds, and separate them from the recordings. We also discuss asymmetries among species in terms of their tendency to partition temporal resources.


2018 ◽  
Vol 2 (2) ◽  
pp. 1-1 ◽  
Author(s):  
Reiji Suzuki ◽  
Shinji Sumitani ◽  
Naren Naren ◽  
Shiho Matsubayashi ◽  
Takaya Arita ◽  
...  

We report on a simple and practical application of HARK, an easily available and portable system for bird song localization using an open-source software for robot audition HARK, to a deeper understanding of ecoacoustic dynamics of bird songs, focusing on a fine-scaled temporal analysis of song movement — song type dynamics in playback experiments. We extended HARKBird and constructed a system that enables us to conduct automatic playback and interactive experiments with different conditions, with a real-time recording and localization of sound sources. We investigate how playback of conspecific songs and playback patterns can affect vocalization of two types of songs and spatial movement of an individual of Japanese bush-warbler, showing quantitatively that there exist strong relationships between song type and spatial movement. We also simulated the ecoacoustic dynamics of the singing behavior of the focal individual using a software, termed Bird song explorer, which provides users a virtual experience of acoustic dynamics of bird songs using a 3D game platform Unity. Based on experimental results, we discuss how our approach can contribute to ecoacoustics in terms of two different roles of sounds: sounds as tools and subjects.


2013 ◽  
Vol 347-350 ◽  
pp. 922-926
Author(s):  
Ming Wang ◽  
Jian Hui Chen ◽  
Guang Long Wang ◽  
Feng Qi Gao ◽  
Ji Chen Li ◽  
...  

Acoustic source orientation is an important feature in robot audition. This paper applied a spatial cone six-element (SCSE) microphone array and combined with the time difference of arrival (TDOA) between pairs of spatial separated microphones to estimate acoustic source orientation. Simulate three stages of the acoustic orientation process in a real indoor environment, and results show that the algorithm is simple and effective, reducing the amount of calculation, having anti-noise and reverberation ability to meet the requirements of orientation accuracy.


2015 ◽  
Vol 137 (4) ◽  
pp. 2193-2193
Author(s):  
John Granzow ◽  
Tim O'Brien ◽  
Darrell Ford ◽  
Yoo H. Yeh ◽  
Yoomi Hur ◽  
...  

2017 ◽  
Vol 48 (3-4) ◽  
pp. 44-51 ◽  
Author(s):  
Gert Herold ◽  
Ennes Sarradj

The open-source Python library Acoular is aimed at the processing of microphone array data. It features a number of algorithms for acoustic source characterization in time domain and frequency domain. The modular, object-oriented architecture allows for flexible programming and a multitude of applications. This includes the processing of measured array data, the mapping of sources, the filtering of subcomponent noise, and the generation of synthetic data for test purposes. Several examples illustrating its versatility are given, as well as one example for implementing a new algorithm into the package.


2017 ◽  
Vol 29 (1) ◽  
pp. 15-15 ◽  
Author(s):  
Hiroshi G. Okuno ◽  
◽  
Kazuhiro Nakadai

Robot audition, the ability of a robot to listen to several things at once with its own “ears,” is crucial to the improvement of interactions and symbiosis between humans and robots. Since robot audition was originally proposed and has been pioneered by Japanese research groups, this special issue on robot audition technologies of the Journal of Robotics and Mechatronics covers a wide collection of advanced topics studied mainly in Japan. Specifically, two consecutive JSPS Grants-in-Aid for Scientific Research (S) on robot audition (PI: Hiroshi G. Okuno) from 2007 to 2017, JST Japan-France Research Cooperative Program on binaural listening for humanoids (PI: Hiroshi G. Okuno and Patrick Danès) from 2009 to 2013, and the ImPACT Tough Robotics Challenge (PM: Prof. Satoshi Tadokoro) on extreme audition for search and rescue robots since 2015 have contributed to the promotion of robot audition research, and most of the papers in this issue are the outcome of these projects. Robot audition was surveyed in the special issue on robot audition in the Journal of Robotic Society of Japan, Vol.28, No.1 (2011) and in our IEEE ICASSP-2015 paper. This issue covers the most recent topics in robot audition, except for human-robot interactions, which was covered by many papers appearing in Advanced Robotics as well as other journals and international conferences, including IEEE IROS.   This issue consists of twenty-three papers accepted through peer reviews. They are classified into four categories: signal processing, music and pet robots, search and rescue robots, and monitoring animal acoustics in natural habitats.   In signal processing for robot audition, Nakadai, Okuno, et al. report on HARK open source software for robot audition, Takeda, et al. develop noise-robust MUSIC-sound source localization (SSL), and Yalta, et al. use deep learning for SSL. Odo, et al. develop active SSL by moving artificial pinnae, and Youssef, et al. propose binaural SSL for an immobile or mobile talker. Suzuki, Otsuka, et al. evaluate the influence of six impulse-response-measuring signals on MUSIC-based SSL, Sekiguchi, et al. give an optimal allocation of distributed microphone arrays for sound source separation, and Tanabe, et al. develop 3D SSL by using a microphone array and LiDAR. Nakadai and Koiwa present audio-visual automatic speech recognition, and Nakadai, Tezuka, et al. suppress ego-noise, that is, noise generated by the robot itself.   In music and pet robots, Ohkita, et al. propose audio-visual beat tracking for a robot to dance with a human dancer, and Tomo, et al. develop a robot that operates a wayang puppet, an Indonesian world cultural heritage, by recognizing emotion in Gamelan music. Suzuki, Takahashi, et al. develop a pet robot that approaches a sound source. In search and rescue robots, Hoshiba, et al. implement real-time SSL with a microphone array installed on a multicopter UAV, and Ishiki, et al. design a microphone array for multicopters. Ohata, et al. detect a sound source with a multicopter microphone array, and Sugiyama, et al. identify detected acoustic events through a combination of signal processing and deep learning. Bando, et al. enhance the human-voice online and offline for a hose-shaped rescue robot with a microphone array.   In monitoring animal acoustics in natural habitats, Suzuki, Matsubayashi, et al. design and implement HARKBird, Matsubayashi, et al. report on the experience of monitoring birds with HARKBird, and Kojima, et al. use a spatial-cue-based probabilistic model to analyze the songs of birds singing in their natural habitat. Aihara, et al. analyze a chorus of frogs with dozens of sound-to-light conversion device Firefly, the design and analysis of which is reported on by Mizumoto, et al.   The editors and authors hope that this special issue will promote the further evolution of robot audition technologies in a diversity of applications.


2008 ◽  
Vol 2008 (0) ◽  
pp. _1P1-G13_1-_1P1-G13_4
Author(s):  
Kazuhiro Nakadai ◽  
Shunichi Yamamoto ◽  
Hiroshi G. Okuno ◽  
Hirofumi Nakajima ◽  
Yuji Hasegawa ◽  
...  

2010 ◽  
Vol 24 (5-6) ◽  
pp. 739-761 ◽  
Author(s):  
Kazuhiro Nakadai ◽  
Toru Takahashi ◽  
Hiroshi G. Okuno ◽  
Hirofumi Nakajima ◽  
Yuji Hasegawa ◽  
...  

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