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Cross-Linguistic Syntactic Evaluation of Word Prediction Models
[article]
2020
arXiv
pre-print
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To investigate how these models' ability to learn syntax varies by language, we introduce CLAMS (Cross-Linguistic Assessment of Models on Syntax), a syntactic evaluation suite for monolingual and multilingual ...
A range of studies have concluded that neural word prediction models can distinguish grammatical from ungrammatical sentences with high accuracy. ...
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation or the other supporting ...
arXiv:2005.00187v2
fatcat:zhlwi3wcwnb2lg5n3xcnmwb5de
Cross-Linguistic Syntactic Evaluation of Word Prediction Models
2020
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
unpublished
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To investigate how these models' ability to learn syntax varies by language, we introduce CLAMS (Cross-Linguistic Assessment of Models on Syntax), a syntactic evaluation suite for monolingual and multilingual ...
A range of studies have concluded that neural word prediction models can distinguish grammatical from ungrammatical sentences with high accuracy. ...
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation or the other supporting ...
doi:10.18653/v1/2020.acl-main.490
fatcat:fplayozt4re7tcs56ml6666nam
Does BERT agree? Evaluating knowledge of structure dependence through agreement relations
[article]
2019
arXiv
pre-print
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Learning representations that accurately model semantics is an important goal of natural language processing research. Many semantic phenomena depend on syntactic structure. ...
We evaluate BERT's sensitivity to four types of structure-dependent agreement relations in a new semi-automatically curated dataset across 26 languages. ...
Thus, evaluating a model's ability to capture agreement relations is also an evaluation of its ability to capture syntactic structure. ...
arXiv:1908.09892v1
fatcat:3542t77ua5c5xkuk3wb3gyg35m
Finding Universal Grammatical Relations in Multilingual BERT
[article]
2020
arXiv
pre-print
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Recent work has found evidence that Multilingual BERT (mBERT), a transformer-based multilingual masked language model, is capable of zero-shot cross-lingual transfer, suggesting that some aspects of its ...
This evidence suggests that even without explicit supervision, multilingual masked language models learn certain linguistic universals. ...
By evaluating Spearman correlation between all pairs of words, one directly evaluates the extent to which the ordering of words j by distance to each word i is correctly predicted, a key notion of the ...
arXiv:2005.04511v2
fatcat:acjbx7rdcjan5nhfa7zah6uwii
AzterTest: Open source linguistic and stylistic analysis tool
2020
Revista de Procesamiento de Lenguaje Natural (SEPLN)
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In this Section we present an extrinsic evaluation of AzterTest in a readability assessment scenario for English texts. ...
In this evaluation, we have tested various classifiers to detect three reading levels (elementary, intermediate, advanced) based on Coh-Metrix and AzterTest's output on an open licensed corpora. ...
For example, the raw number of words is usually a predictive feature, but it depends on text length and not on its linguistic characteristics. ...
dblp:journals/pdln/BengoetxeaGM20
fatcat:xcm32pj64vdhbbvsuaryhx2bwa
Understanding Cross-Lingual Syntactic Transfer in Multilingual Recurrent Neural Networks
[article]
2021
arXiv
pre-print
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In this paper we dissect different forms of cross-lingual transfer and look for its most determining factors, using a variety of models and probing tasks. ...
But what kind of knowledge is really shared among languages within these models? ...
In contrast to the current mainstream focus on BERT-like models (Rogers et al., 2020) , we evaluate more classical LSTM-based models trained for next word prediction or translation over a moderate number ...
arXiv:2003.14056v3
fatcat:bvuocwt3xrbzdmoiezj5iqkxxa
Robust Training under Linguistic Adversity
2017
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
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We consider several flavours of linguistically plausible corruption, include lexical semantic and syntactic methods. ...
Empirically, we evaluate our method with a convolutional neural model across a range of sentiment analysis datasets. ...
We focus on the generation of two classes of text noise: (1) syntactic noise; and (2) semantic noise. 2 Syntactic Noise The first class of linguistic noise is syntactic, focusing on the syntactic struc-ture ...
doi:10.18653/v1/e17-2004
dblp:conf/eacl/BaldwinCL17
fatcat:osdzobqrcbdfxnv6dzip7b36wi
Predicting Foreign Language Usage from English-Only Social Media Posts
2018
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)
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We contrast the predictive power of the state-of-theart machine learning models trained on lexical, syntactic, and stylistic signals with neural network models learned from word, character and byte representations ...
Finally, by analyzing cross-lingual transferthe influence of non-English languages on various levels of linguistic performance in English, we present novel findings on stylistic and syntactic variations ...
For that we first develop linguistic models to test our hypothesis, and then evaluate syntactic and stylistic similarities across speakers of non-English languages using the English portion of their multilingual ...
doi:10.18653/v1/n18-2096
dblp:conf/naacl/VolkovaRP18
fatcat:jyrften5ezdv7hpvosb6ot7xhy
Bridging between Cognitive Processing Signals and Linguistic Features via a Unified Attentional Network
[article]
2022
arXiv
pre-print
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2021 pre-print arXiv:2112.08831v1 fatcat:igwp3jboznhuhpqdx6rykgnifa
Specifically, we present a unified attentional framework that is composed of embedding, attention, encoding and predicting layers to selectively map cognitive processing signals to linguistic features. ...
We define the mapping procedure as a bridging task and develop 12 bridging tasks for lexical, syntactic and semantic features. ...
Acknowledgments The present research was partially supported by the Natural Science Foundation of Tianjin (Grant No. 19JCZDJC31400). ...
arXiv:2112.08831v2
fatcat:5e5j56qw35fbdkrbrcvx6emocm
Machine Learning Approach to Evaluate MultiLingual Summaries
2017
Proceedings of the MultiLing 2017 Workshop on Summarization and Summary Evaluation Across Source Types and Genres
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This method relies on machine learning approach which operates by combining multiple features to build models that predict the human score (overall responsiveness) of a new summary. ...
We have experimented our method in summary level evaluation where we evaluate the quality of each text summary separately. ...
The main steps we plan to take in our future works, are the construction of predictive models for more languages and the addition of other types of features such as entities based features, part-ofspeech ...
doi:10.18653/v1/w17-1007
dblp:conf/acl-multiling/EllouzeJB17
fatcat:v4lisky3ibh47acxi5jc7sfjcu
LIMIT-BERT : Linguistic Informed Multi-Task BERT
[article]
2020
arXiv
pre-print
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2019 pre-print arXiv:1910.14296v1 fatcat:6ptbcupjmrhyzd4flfkqlfal5e
Besides, LIMIT-BERT adopts linguistics mask strategy: Syntactic and Semantic Phrase Masking which mask all of the tokens corresponding to a syntactic/semantic phrase. ...
LIMIT-BERT includes five key linguistic syntax and semantics tasks: Part-Of-Speech (POS) tags, constituent and dependency syntactic parsing, span and dependency semantic role labeling (SRL). ...
BERT obtains new state-of-the-art or competitive results on four parsing tasks of Propbank benchmarks and Penn Treebank. ...
arXiv:1910.14296v2
fatcat:aubzncxtsnaq3oqo5yqbby2b24
Parsing Arabic using deep learning technology
2021
Tunisian-Algerian Joint Conference on Applied Computing
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Syntactic Parsing present a fundamental step in the process of automatic analysis of the language since it is the crucial task of determining the syntactic structures sentences. ...
We present our methodology and expose evaluation results using several deep learning architectures. ...
The skip-gram aims to predict the words of the context given an input word [15] . ...
dblp:conf/tacc/MaalejKA21
fatcat:utma3sawgfgzzkjgjaj3xioe3m
Analyzing the Mono- and Cross-Lingual Pretraining Dynamics of Multilingual Language Models
[article]
2022
arXiv
pre-print
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We investigate when these models acquire their in-language and cross-lingual abilities by probing checkpoints taken from throughout XLM-R pretraining, using a suite of linguistic tasks. ...
In contrast, when the model learns to transfer cross-lingually depends on the language pair. ...
Dependency Structure We evaluate syntactic dependency structure knowledge with two pairwise probing tasks: arc prediction, in which the probe is trained to discriminate between pairs of words that are ...
arXiv:2205.11758v1
fatcat:pc3bf2e64rff7ciogwez7tcu2u
Page 2670 of Linguistics and Language Behavior Abstracts: LLBA Vol. 28, Issue 5
[page]
1994
Linguistics and Language Behavior Abstracts: LLBA
Preserved Fulltext
The Internet Archive has digitized a microfilm copy of this work. It may be possible to borrow a copy for reading.
Burling’s Maru (Tibeto Burman) analysis, Land Dayak (Austronesian) data support, coronal feature exten- sion/vowels; 9410474 language-specific meanings, grammatical category encodings, cross- linguistic ...
order correlation, cross- linguistic analysis; 9411208
time/meaning/language interactions, chronosemantics development; 9410794
Tone
Chinese homophone judgment, tone role; experiments; Cantonese/ Mandarin ...
Distributional Information: A Powerful Cue for Acquiring Syntactic Categories
1998
Cognitive Science
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More than half of the distance between self-prediction and chance for all corpora. free word order, prodrop Japanese (Miyata, 1992(Miyata, , 1995 free word order, rich morphology Crotian (Kovacevic, 2003 ...
Finding: A small sample of adult data increases prediction accuracy for the child's utterances 34% over chance. ...
Word order prediction can be a way to evaluate syntactic constraints cross-linguistically. Connectionist models of syntax acquisition do word order prediction (Elman, 1990; Chang, 2002) . ...
doi:10.1207/s15516709cog2204_2
fatcat:bxedlcdfkjdkvbkvetieuejmtu
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