Cluster self-organization of known and unknown environmental sounds using recurrent neural network

Yang Zhang; Shun Nishide; Toru Takahashi; Hiroshi G. Okuno; Tetsuya Ogata

doi:10.1007/978-3-642-21735-7_21

Cluster self-organization of known and unknown environmental sounds using recurrent neural network

Yang Zhang^*, Shun Nishide, Toru Takahashi, Hiroshi G. Okuno, Tetsuya Ogata

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Our goal is to develop a system that is able to learn and classify environmental sounds for robots working in the real world. In the real world, two main restrictions pertain in learning. First, the system has to learn using only a small amount of data in a limited time because of hardware restrictions. Second, it has to adapt to unknown data since it is virtually impossible to collect samples of all environmental sounds. We used a neuro-dynamical model to build a prediction and classification system which can self-organize sound classes into parameters by learning samples. The proposed system searches space of parameters for classifying. In the experiment, we evaluated the accuracy of classification for known and unknown sound classes.

Original language	English
Title of host publication	Artificial Neural Networks and Machine Learning, ICANN 2011 - 21st International Conference on Artificial Neural Networks, Proceedings
Pages	167-175
Number of pages	9
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-21735-7_21
Publication status	Published - 2011
Externally published	Yes
Event	21st International Conference on Artificial Neural Networks, ICANN 2011 - Espoo, Finland Duration: 2011 Jun 14 → 2011 Jun 17

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	6791 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	21st International Conference on Artificial Neural Networks, ICANN 2011
Country/Territory	Finland
City	Espoo
Period	11/6/14 → 11/6/17

Keywords

Classification
Environmental Sounds
Neuro-dynamical Model
Prediction

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-21735-7_21

Cite this

Zhang, Y., Nishide, S., Takahashi, T., Okuno, H. G., & Ogata, T. (2011). Cluster self-organization of known and unknown environmental sounds using recurrent neural network. In Artificial Neural Networks and Machine Learning, ICANN 2011 - 21st International Conference on Artificial Neural Networks, Proceedings (PART 1 ed., pp. 167-175). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6791 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-21735-7_21

Cluster self-organization of known and unknown environmental sounds using recurrent neural network. / Zhang, Yang; Nishide, Shun; Takahashi, Toru et al.
Artificial Neural Networks and Machine Learning, ICANN 2011 - 21st International Conference on Artificial Neural Networks, Proceedings. PART 1. ed. 2011. p. 167-175 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6791 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zhang, Y, Nishide, S, Takahashi, T, Okuno, HG & Ogata, T 2011, Cluster self-organization of known and unknown environmental sounds using recurrent neural network. in Artificial Neural Networks and Machine Learning, ICANN 2011 - 21st International Conference on Artificial Neural Networks, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 6791 LNCS, pp. 167-175, 21st International Conference on Artificial Neural Networks, ICANN 2011, Espoo, Finland, 11/6/14. https://doi.org/10.1007/978-3-642-21735-7_21

Zhang Y, Nishide S, Takahashi T, Okuno HG, Ogata T. Cluster self-organization of known and unknown environmental sounds using recurrent neural network. In Artificial Neural Networks and Machine Learning, ICANN 2011 - 21st International Conference on Artificial Neural Networks, Proceedings. PART 1 ed. 2011. p. 167-175. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-21735-7_21

Zhang, Yang ; Nishide, Shun ; Takahashi, Toru et al. / Cluster self-organization of known and unknown environmental sounds using recurrent neural network. Artificial Neural Networks and Machine Learning, ICANN 2011 - 21st International Conference on Artificial Neural Networks, Proceedings. PART 1. ed. 2011. pp. 167-175 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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Cluster self-organization of known and unknown environmental sounds using recurrent neural network

Abstract

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Keywords

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