| Presentation | 2019-06-18 Detection of Syntactic Anomalies in Spoken Sentences from Single-trial EEG Signals with Neural Networks Shunnosuke Motomura, Hiroki Tanaka, Satoshi Nakamura, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this paper we propose a method with neural networks for detecting syntactic anomalies in sentences using electroencephalogram (EEG) signals. To the best of our knowledge, there have been few studies for detecting syntactic anomalies from single-trial EEG signals. Eighteen participants listened to sentences, some of which included syntactically anomalous words, and answered the correctness of the sentences by pressing a button. During this procedure, we recorded EEG signals of the participants. We evaluated Stacked autoencoders (SAE) and Long-short term memory (LSTM) and a baseline model, Support vector machine (SVM), for classifying EEG signals with respect to syntactic anomalies. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Electroencephalogram (EEG) / event-related potentials (ERPs) / P600 / Stacked Autoencoders / Long-Short Term Memory |
| Paper # | NC2019-15,IBISML2019-13 |
| Date of Issue | 2019-06-10 (NC, IBISML) |
| Conference Information | |
| Committee | NC / IBISML / IPSJ-MPS / IPSJ-BIO |
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| Conference Date | 2019/6/17(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Okinawa Institute of Science and Technology |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Neurocomputing, Machine Learning Approach to Biodata Mining, and General |
| Chair | Hayaru Shouno(UEC) / Hisashi Kashima(Kyoto Univ.) / Masakazu Sekijima(Tokyo Tech) / Hiroyuki Kurata(Kyutech) |
| Vice Chair | Kazuyuki Samejima(Tamagawa Univ) / Masashi Sugiyama(Univ. of Tokyo) / Koji Tsuda(Univ. of Tokyo) |
| Secretary | Kazuyuki Samejima(NAIST) / Masashi Sugiyama(NTT) / Koji Tsuda(Nagoya Inst. of Tech.) / (AIST) / (Nagoya Univ.) |
| Assistant | Takashi Shinozaki(NICT) / Ken Takiyama(TUAT) / Tomoharu Iwata(NTT) / Shigeyuki Oba(Kyoto Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Neurocomputing / Technical Committee on Infomation-Based Induction Sciences and Machine Learning / IPSJ Special Interest Group on Mathematical Modeling and Problem Solving / IPSJ Special Interest Group on Bioinformatics and Genomics |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Detection of Syntactic Anomalies in Spoken Sentences from Single-trial EEG Signals with Neural Networks |
| Sub Title (in English) | |
| Keyword(1) | Electroencephalogram (EEG) |
| Keyword(2) | event-related potentials (ERPs) |
| Keyword(3) | P600 |
| Keyword(4) | Stacked Autoencoders |
| Keyword(5) | Long-Short Term Memory |
| 1st Author's Name | Shunnosuke Motomura |
| 1st Author's Affiliation | Nara Institute of Science and Technology(NAIST) |
| 2nd Author's Name | Hiroki Tanaka |
| 2nd Author's Affiliation | Nara Institute of Science and Technology(NAIST) |
| 3rd Author's Name | Satoshi Nakamura |
| 3rd Author's Affiliation | Nara Institute of Science and Technology(NAIST) |
| Date | 2019-06-18 |
| Paper # | NC2019-15,IBISML2019-13 |
| Volume (vol) | vol.119 |
| Number (no) | NC-88,IBISML-89 |
| Page | pp.pp.63-68(NC), pp.85-90(IBISML), |
| #Pages | 6 |
| Date of Issue | 2019-06-10 (NC, IBISML) |