Echo state vs. lstm networks for word sense disambiguation
Inspired by bidirectional long short-term memory (LSTM) recurrent neural network (RNN)
architectures, commonly applied in natural language processing (NLP) tasks, we have …
architectures, commonly applied in natural language processing (NLP) tasks, we have …
Hierarchical-task reservoir for anytime POS tagging from continuous speech
L Pedrelli, X Hinaut - 2020 International Joint Conference on …, 2020 - ieeexplore.ieee.org
We propose a novel architecture called Hierarchical-Task Reservoir (HTR) suitable for real-
time sentence parsing from continuous speech. Accordingly, we introduce a novel task that …
time sentence parsing from continuous speech. Accordingly, we introduce a novel task that …
Cross-Situational Learning Towards Robot Grounding
How do children acquire language through unsupervised or noisy supervision? How do
their brain process language? We take this perspective to machine learning and robotics …
their brain process language? We take this perspective to machine learning and robotics …
Echo state network for word sense disambiguation
The current developments in the area report on numerous applications of recurrent neural
networks for Word Sense Disambiguation that allowed the increase of prediction accuracy …
networks for Word Sense Disambiguation that allowed the increase of prediction accuracy …
Word embeddings improvement via echo state networks
K Simov, P Koprinkova-Hristova… - … on INnovations in …, 2019 - ieeexplore.ieee.org
The paper continues investigations on the application of bidirectional echo state networks
(BiESN) to the task of word sense disambiguation (WSD). Motivated by observations that the …
(BiESN) to the task of word sense disambiguation (WSD). Motivated by observations that the …
A reservoir computing approach to word sense disambiguation
Reservoir computing (RC) has emerged as an alternative approach for the development of
fast trainable recurrent neural networks (RNNs). It is considered to be biologically plausible …
fast trainable recurrent neural networks (RNNs). It is considered to be biologically plausible …
Robust bidirectional processing for speech-controlled robotic scenarios
J Twiefel - 2020 - ediss.sub.uni-hamburg.de
Automatic Speech Recognition (ASR) is often employed for applications like dictation, where
the aim is to cover a broad range of vocabularies. Also, ASR is a central interface for …
the aim is to cover a broad range of vocabularies. Also, ASR is a central interface for …
[PDF][PDF] An analysis of subtask-dependency in robot command interpretation with dilated CNNs.
In this paper, we tackle sequence-to-tree transduction for language processing with neural
networks implementing several subtasks, namely tokenization, semantic annotation, and …
networks implementing several subtasks, namely tokenization, semantic annotation, and …
and Petya Osenova () Institute of Information and Communication Technology, Bulgarian Academy of Sciences, Akad. G. Bonchev. 25A, 1113 Sofia, Bulgaria …
P Koprinkova-Hristova - Artificial Intelligence: Methodology …, 2018 - books.google.com
The current developments in the area report on numerous applications of recurrent neural
networks for Word Sense Disambiguation that allowed the increase of prediction accuracy …
networks for Word Sense Disambiguation that allowed the increase of prediction accuracy …