55 papers with code • 1 benchmarks • 6 datasets
Language acquisition refers to tasks related to the learning of a second language.
These leaderboards are used to track progress in Language Acquisition
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Most implemented papers
Semantic speech retrieval with a visually grounded model of untranscribed speech
We introduce a newly collected data set of human semantic relevance judgements and an associated task, semantic speech retrieval, where the goal is to search for spoken utterances that are semantically relevant to a given text query.
Predicting and Explaining Human Semantic Search in a Cognitive Model
Recent work has attempted to characterize the structure of semantic memory and the search algorithms which, together, best approximate human patterns of search revealed in a semantic fluency task.
Interactive Grounded Language Acquisition and Generalization in a 2D World
We build a virtual agent for learning language in a 2D maze-like world.
Neural Network Acceptability Judgments
This paper investigates the ability of artificial neural networks to judge the grammatical acceptability of a sentence, with the goal of testing their linguistic competence.
Context Based Approach for Second Language Acquisition
Our system uses a logistic regression model to predict the likelihood of a student making a mistake while answering an exercise on Duolingo in all three language tracks - English/Spanish (en/es), Spanish/English (es/en) and French/English (fr/en).
Language as a Cognitive Tool to Imagine Goals in Curiosity-Driven Exploration
We argue that the ability to imagine out-of-distribution goals is key to enable creative discoveries and open-ended learning.
Learning Music Helps You Read: Using Transfer to Study Linguistic Structure in Language Models
We propose transfer learning as a method for analyzing the encoding of grammatical structure in neural language models.
Visually Grounded Continual Learning of Compositional Phrases
To study this human-like language acquisition ability, we present VisCOLL, a visually grounded language learning task, which simulates the continual acquisition of compositional phrases from streaming visual scenes.
An Efficient, Probabilistically Sound Algorithm for Segmentation and Word Discovery
The model yields a language-independent, prior probability distribution on all possible sequences of all possible words over a given alphabet, based on the assumption that the input was generated by concatenating words from a fixed but unknown lexicon.
Learning Semantic Correspondences with Less Supervision
A central problem in grounded language acquisition is learning the correspondences between a rich world state and a stream of text which references that world state.