Multi-Stream Long Short-Term Memory Neural Network Language Model
dc.authorid | Ebru Arısoy / 0000-0002-8311-3611 | |
dc.contributor.author | Saraçlar, Murat | |
dc.contributor.author | Arısoy, Ebru | |
dc.date.accessioned | 2019-02-28T13:04:26Z | |
dc.date.accessioned | 2019-02-28T11:08:17Z | |
dc.date.available | 2019-02-28T13:04:26Z | |
dc.date.available | 2019-02-28T11:08:17Z | |
dc.date.issued | 2015 | |
dc.department | Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümü | en_US |
dc.description | Ebru Arısoy (MEF Author) | en_US |
dc.description.WoSDocumentType | Proceedings Paper | |
dc.description.WoSIndexDate | 2015 | en_US |
dc.description.WoSPublishedMonth | Eylül | en_US |
dc.description.WoSYOKperiod | YÖK - 2015-16 | en_US |
dc.description.abstract | Long Short-Term Memory (LSTM) neural networks are recurrent neural networks that contain memory units that can store contextual information from past inputs for arbitrary amounts of time. A typical LSTM neural network language model is trained by feeding an input sequence. i.e., a stream of words, to the input layer of the network and the output layer predicts the probability of the next word given the past inputs in the sequence. In this paper we introduce a multi-stream LSTM neural network language model where multiple asynchronous input sequences are fed to the network as parallel streams while predicting the output word sequence. For our experiments, we use a sub-word sequence in addition to a word sequence as the input streams, which allows joint training of the LSTM neural network language model using both information sources. | en_US |
dc.description.woscitationindex | Conference Proceedings Citation Index - Science | en_US |
dc.identifier.citation | Arisoy, E., Saraclar, M., (2015). Multi-stream long short-term memory neural network language model. Conference: 16th Annual Conference of the International-Speech-Communication-Association (INTERSPEECH 2015) Location: Dresden, GERMANY, vol: 1-5. p. 1413-1417. | en_US |
dc.identifier.endpage | 1417 | en_US |
dc.identifier.scopus | 2-s2.0-84959116680 | |
dc.identifier.scopusquality | N/A | |
dc.identifier.startpage | 1413 | en_US |
dc.identifier.uri | https://hdl.handle.net/20.500.11779/665 | |
dc.identifier.volume | 1_5 | en_US |
dc.identifier.wos | WOS:000380581600296 | |
dc.identifier.wosquality | N/A | |
dc.institutionauthor | Arısoy, Ebru | |
dc.language.iso | en | en_US |
dc.relation.ispartof | Conference: 16th Annual Conference of the International-Speech-Communication-Association (INTERSPEECH 2015) Location: Dresden, GERMANY Date: SEP 06-10, 2015 | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Long short-term memory | en_US |
dc.subject | Sub-word-based language modeling | en_US |
dc.subject | Language modeling | en_US |
dc.title | Multi-Stream Long Short-Term Memory Neural Network Language Model | en_US |
dc.type | Conference Object | en_US |
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