نتایج جستجو برای: sequence learning

تعداد نتایج: 990992  

2017
Tatyana Ruzsics Tanja Samardzic

Learning internal word structure has recently been recognized as an important step in various multilingual processing tasks and in theoretical language comparison. In this paper, we present a neural encoder-decoder model for learning canonical morphological segmentation. Our model combines character-level sequence-to-sequence transformation with a language model over canonical segments. We obta...

2016
Sarah Nadine Meissner Ariane Keitel Martin Südmeyer Bettina Pollok

Although implicit motor sequence learning is rather well understood in young adults, effects of aging on this kind of learning are controversial. There is first evidence that working memory (WM) might play a role in implicit motor sequence learning in young adults as well as in adults above the age of 65. However, the knowledge about the development of these processes across the adult life span...

2014
Katherine R. Gamble Thomas J. Cummings Jr. Steven E. Lo Pritha T. Ghosh James H. Howard Jr. Darlene V. Howard

Implicit sequence learning involves learning about dependencies in sequences of events without intent to learn or awareness of what has been learned. Sequence learning is related to striatal dopamine levels, striatal activation, and integrity of white matter connections. People with Parkinson's disease (PD) have degeneration of dopamine-producing neurons, leading to dopamine deficiency and ther...

Journal: :Journal of experimental psychology. General 2009
Eric H Schumacher Hillary Schwarb

Some studies suggest that dual-task processing impairs sequence learning; others suggest it does not. The reason for this discrepancy remains obscure. It may have to do with the dual-task procedure often used. Many dual-task sequence learning studies pair the serial reaction time (SRT) task with a tone-counting secondary task. The tone-counting task, however, is not ideal for studying the cogni...

2011
Youngbin Kwak Rachael D. Seidler Thad A. Polk Wayne Aldridge Nicolaas I. Bohnen Rachael Seidler Nico Bohnen Martijn Müller Praveen Dayalu Scott Peltier Darcy Huismann Nika George Halley Feldman Sarah Shin Alyssa Erickson Melissa Tan Mona Ramlawi Melanie Sottile Peter Hitchcock Joaquin Anguera Ashley Bangert Jin Bo Jeanne Langan Jessica Bernard Bryan Benson Nate Boyden Brett Fling Nathan Miller

Parkinson’s disease (PD) is a neurodegenerative disorder affecting the dopamine neurotransmitter system which is crucial for motor control and cognitive function. Dopaminergic medications alleviate Parkisonian motor symptoms however evidence shows that they also interfere with normal functioning in other domains. The current dissertation aimed to determine the effect of dopaminergic medication ...

Journal: :NeuroImage 2011
Eric W. Gobel Todd B. Parrish Paul J. Reber

Learning of complex motor skills requires learning of component movements as well as the sequential structure of their order and timing. Using a Serial Interception Sequence Learning (SISL) task, participants learned a sequence of precisely timed interception responses through training with a repeating sequence. Following initial implicit learning of the repeating sequence, functional MRI data ...

2017
Shahin Amiriparian Michael Freitag Nicholas Cummins Björn Schuller

This paper describes our contribution to the Acoustic Scene Classification task of the IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and Events (DCASE 2017). We propose a system for this task using a recurrent sequence to sequence autoencoder for unsupervised representation learning from raw audio files. First, we extract mel-spectrograms from the raw audio files. Secon...

Journal: :CoRR 2016
Jiatao Gu Zhengdong Lu Hang Li Victor O. K. Li

We address an important problem in sequence-to-sequence (Seq2Seq) learning referred to as copying, in which certain segments in the input sequence are selectively replicated in the output sequence. A similar phenomenon is observable in human language communication. For example, humans tend to repeat entity names or even long phrases in conversation. The challenge with regard to copying in Seq2S...

2017
Jindrich Libovický Jindrich Helcl

Modeling attention in neural multi-source sequence-to-sequence learning remains a relatively unexplored area, despite its usefulness in tasks that incorporate multiple source languages or modalities. We propose two novel approaches to combine the outputs of attention mechanisms over each source sequence, flat and hierarchical. We compare the proposed methods with existing techniques and present...

2016
Sam Wiseman Alexander M. Rush

Sequence-to-Sequence (seq2seq) modeling has rapidly become an important generalpurpose NLP tool that has proven effective for many text-generation and sequence-labeling tasks. Seq2seq builds on deep neural language modeling and inherits its remarkable accuracy in estimating local, next-word distributions. In this work, we introduce a model and beamsearch training scheme, based on the work of Da...

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