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1
The contextual logic
In: https://hal.archives-ouvertes.fr/hal-03195162 ; 2022 (2022)
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2
Learning and controlling the source-filter representation of speech with a variational autoencoder
In: https://hal.archives-ouvertes.fr/hal-03650569 ; 2022 (2022)
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3
Assessing the impact of OCR noise on multilingual event detection over digitised documents
In: ISSN: 1432-5012 ; EISSN: 1432-1300 ; International Journal on Digital Libraries ; https://hal.archives-ouvertes.fr/hal-03635985 ; International Journal on Digital Libraries, Springer Verlag, 2022, ⟨10.1007/s00799-022-00325-2⟩ (2022)
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Introducing the HIPE 2022 Shared Task: Named Entity Recognition and Linking in Multilingual Historical Documents
In: Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II ; https://hal.archives-ouvertes.fr/hal-03635971 ; Matthias Hagen; Suzan Verberne; Craig Macdonald; Christin Seifert; Krisztian Balog; Kjetil Nørvåg; Vinay Setty. Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II, 13186, Springer International Publishing, pp.347-354, 2022, Lecture Notes in Computer Science, 978-3-030-99738-0. ⟨10.1007/978-3-030-99739-7_44⟩ (2022)
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5
Can Character-based Language Models Improve Downstream Task Performance in Low-Resource and Noisy Language Scenarios?
In: Seventh Workshop on Noisy User-generated Text (W-NUT 2021, colocated with EMNLP 2021) ; https://hal.inria.fr/hal-03527328 ; Seventh Workshop on Noisy User-generated Text (W-NUT 2021, colocated with EMNLP 2021), Jan 2022, punta cana, Dominican Republic ; https://aclanthology.org/2021.wnut-1.47/ (2022)
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6
Annotation of Morphological Errors in L2 Russian Corpus Analysis
In: 21st Annual Second Language Acquisition and Teaching Interdisciplinary Roundtable ; https://hal.archives-ouvertes.fr/hal-03620469 ; 21st Annual Second Language Acquisition and Teaching Interdisciplinary Roundtable, University of Arizona, Feb 2022, Tucson, United States (2022)
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7
Cross-Situational Learning Towards Robot Grounding
In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
Abstract: 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, where part of the problem is understanding how language models can perform grounded language acquisition through noisy supervision and discussing how they can account for brain learning dynamics. Most prior works have tracked the co-occurrence between single words and referents to model how infants learn wordreferent mappings. This paper studies cross-situational learning (CSL) with full sentences: we want to understand brain mechanisms that enable children to learn mappings between words and their meanings from full sentences in early language learning. We investigate the CSL task on a few training examples with two sequence-based models: (i) Echo State Networks (ESN) and (ii) Long-Short Term Memory Networks (LSTM). Most importantly, we explore several word representations including One-Hot, GloVe, pretrained BERT, and fine-tuned BERT representations (last layer token representations) to perform the CSL task. We apply our approach to three diverse datasets (two grounded language datasets and a robotic dataset) and observe that (1) One-Hot, GloVe, and pretrained BERT representations are less efficient when compared to representations obtained from fine-tuned BERT. (2) ESN online with final learning (FL) yields superior performance over ESN online continual learning (CL), offline learning, and LSTMs, indicating the more biological plausibility of ESNs and the cognitive process of sentence reading. (2) LSTM with fewer hidden units showcases higher performance for small datasets, but LSTM with more hidden units is Cross-Situational Learning needed to perform reasonably well on larger corpora. (4) ESNs demonstrate better generalization than LSTM models for increasingly large vocabularies. Overall, these models are able to learn from scratch to link complex relations between words and their corresponding meaning concepts, handling polysemous and synonymous words. Moreover, we argue that such models can extend to help current human-robot interaction studies on language grounding and better understand children's developmental language acquisition. We make the code publicly available * .
Keyword: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]; [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]; [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]; BERT; cross-situational learning; echo state networks; grounded language; LSTM
URL: https://hal.archives-ouvertes.fr/hal-03628290
https://hal.archives-ouvertes.fr/hal-03628290v2/file/Journal_of_Social_and_Robotics.pdf
https://hal.archives-ouvertes.fr/hal-03628290v2/document
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8
Cross-Situational Learning Towards Robot Grounding
In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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9
A Methodology for the Comparison of Human Judgments With Metrics for Coreference Resolution
In: HumEval at ACL ; https://hal.archives-ouvertes.fr/hal-03650294 ; HumEval at ACL, May 2022, Dublin, Ireland ; https://humeval.github.io/ (2022)
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10
Can machines learn to see without visual databases?
In: https://hal.archives-ouvertes.fr/hal-03526569 ; 2022 (2022)
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11
A comparative study of several parameterizations for speaker recognition ...
Faundez-Zanuy, Marcos. - : arXiv, 2022
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12
A Neural Pairwise Ranking Model for Readability Assessment ...
Lee, Justin; Vajjala, Sowmya. - : arXiv, 2022
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13
Compiler-Driven Simulation of Reconfigurable Hardware Accelerators ...
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14
Subspace-based Representation and Learning for Phonotactic Spoken Language Recognition ...
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15
ClassSPLOM -- A Scatterplot Matrix to Visualize Separation of Multiclass Multidimensional Data ...
Aupetit, Michael; Ali, Ahmed. - : arXiv, 2022
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16
A Deep CNN Architecture with Novel Pooling Layer Applied to Two Sudanese Arabic Sentiment Datasets ...
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17
Mono vs Multilingual BERT: A Case Study in Hindi and Marathi Named Entity Recognition ...
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18
Informative Causality Extraction from Medical Literature via Dependency-tree based Patterns ...
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19
Learning and controlling the source-filter representation of speech with a variational autoencoder ...
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20
Correcting Misproducted Speech using Spectrogram Inpainting ...
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