1 |
Cyberbullying Classifiers are Sensitive to Model-Agnostic Perturbations ...
|
|
|
|
BASE
|
|
Show details
|
|
3 |
Mapping probability word problems to executable representations ...
|
|
|
|
BASE
|
|
Show details
|
|
4 |
Interlocutors’ Age Impacts Teenagers’ Online Writing Style: Accommodation in Intra- and Intergenerational Online Conversations
|
|
|
|
In: Front Artif Intell (2021)
|
|
BASE
|
|
Show details
|
|
6 |
The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe
|
|
|
|
In: Language Resources and Evaluation Conference ; https://hal.archives-ouvertes.fr/hal-02892154 ; Language Resources and Evaluation Conference, ELDA/ELRA, May 2020, Marseille, France ; https://lrec2020.lrec-conf.org/en/ (2020)
|
|
BASE
|
|
Show details
|
|
8 |
The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe ...
|
|
|
|
BASE
|
|
Show details
|
|
9 |
The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe ...
|
|
|
|
BASE
|
|
Show details
|
|
10 |
The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe ...
|
|
|
|
BASE
|
|
Show details
|
|
11 |
Neural Machine Translation of Artwork Titles Using Iconclass Codes ...
|
|
|
|
BASE
|
|
Show details
|
|
12 |
A deep generative approach to native language identification ...
|
|
|
|
BASE
|
|
Show details
|
|
13 |
Effective weakly supervised semantic frame induction using expression sharing in hierarchical hidden Markov models ...
|
|
|
|
BASE
|
|
Show details
|
|
14 |
What makes a distributional context useful? Lexical diversity is more important than frequency ...
|
|
|
|
BASE
|
|
Show details
|
|
15 |
Children Probably Store Short Rather Than Frequent or Predictable Chunks: Quantitative Evidence From a Corpus Study
|
|
|
|
Abstract:
One of the tasks faced by young children is the segmentation of a continuous stream of speech into discrete linguistic units. Early in development, syllables emerge as perceptual primitives, and the wholesale storage of syllable chunks is one possible strategy for bootstrapping the segmentation process. Here, we investigate what types of chunks children store. Our method involves selecting syllabified utterances from corpora of child-directed speech, which we vary according to (a) their length in syllables, (b) the mutual predictability of their syllables, and (c) their frequency. We then use the number of utterances within which words are contained to predict the time course of word learning, arguing that utterances which perform well at this task are also more likely to be stored, by young children, as undersegmented chunks. Our results show that short utterances are best-suited for predicting when children acquire the words contained within them, although the effect is rather small. Beyond this, we also find that short utterances are the most likely to correspond to words. Together, the two findings suggest that children may not store many complete utterances as undersegmented chunks, with most of the units that children store as hypothesized words corresponding to actual words. However, dovetailing with an item-based account of language-acquisition, when children do store undersegmented chunks, these are likely to be short sequences—not frequent or internally predictable multi-word chunks. We end by discussing implications for work on formulaic multi-word sequences.
|
|
Keyword:
Psychology
|
|
URL: https://doi.org/10.3389/fpsyg.2019.00080 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6363945/
|
|
BASE
|
|
Hide details
|
|
16 |
Overview of PAN 2019: Bots and Gender Profiling, Celebrity Profiling, Cross-domain Authorship Attribution and Style Change Detection
|
|
|
|
BASE
|
|
Show details
|
|
17 |
Multilingual Cross-domain Perspectives on Online Hate Speech ...
|
|
|
|
BASE
|
|
Show details
|
|
18 |
Patient representation learning and interpretable evaluation using clinical notes ...
|
|
|
|
BASE
|
|
Show details
|
|
19 |
Lexical category acquisition is facilitated by uncertainty in distributional co-occurrences
|
|
|
|
BASE
|
|
Show details
|
|
|
|