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

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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages167-175
Number of pages9
Volume6791 LNCS
EditionPART 1
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event21st International Conference on Artificial Neural Networks, ICANN 2011 - Espoo
Duration: 2011 Jun 142011 Jun 17

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6791 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other21st International Conference on Artificial Neural Networks, ICANN 2011
CityEspoo
Period11/6/1411/6/17

Fingerprint

Recurrent neural networks
Recurrent Neural Networks
Self-organization
Acoustic waves
Unknown
Restriction
Dynamical Model
Search Space
Robot
Classify
Hardware
Robots
Sound
Prediction
Experiment
Experiments
Class
Learning

Keywords

  • Classification
  • Environmental Sounds
  • Neuro-dynamical Model
  • Prediction

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 6791 LNCS, 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; Okuno, Hiroshi G.; Ogata, Tetsuya.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6791 LNCS 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 proceedingConference 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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 edn, vol. 6791 LNCS, 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, 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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 ed. Vol. 6791 LNCS. 2011. p. 167-175. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-642-21735-7_21
Zhang, Yang ; Nishide, Shun ; Takahashi, Toru ; Okuno, Hiroshi G. ; Ogata, Tetsuya. / Cluster self-organization of known and unknown environmental sounds using recurrent neural network. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6791 LNCS 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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