Language Acquisition
69 papers with code • 1 benchmarks • 6 datasets
Language acquisition refers to tasks related to the learning of a second language.
Benchmarks
These leaderboards are used to track progress in Language Acquisition
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Libraries
Use these libraries to find Language Acquisition models and implementationsDatasets
BLiMP
Duolingo SLAM Shared Task
Duolingo Spaced Repetition Data
New Brown Corpus
BabySLM
Latest papers with no code
Evaluating Neural Language Models as Cognitive Models of Language Acquisition
The success of neural language models (LMs) on many technological tasks has brought about their potential relevance as scientific theories of language despite some clear differences between LM training and child language acquisition.
A Human-Robot Mutual Learning System with Affect-Grounded Language Acquisition and Differential Outcomes Training
This paper presents a novel human-robot interaction setup for robot and human learning of symbolic language for identifying robot homeostatic needs.
Audio-Visual Neural Syntax Acquisition
We study phrase structure induction from visually-grounded speech.
Robustness of the Random Language Model
The Random Language Model (De Giuli 2019) is an ensemble of stochastic context-free grammars, quantifying the syntax of human and computer languages.
Spanish Resource Grammar version 2023
We present the latest version of the Spanish Resource Grammar (SRG), a grammar of Spanish implemented in the HPSG formalism.
Rethinking the Evaluating Framework for Natural Language Understanding in AI Systems: Language Acquisition as a Core for Future Metrics
In the burgeoning field of artificial intelligence (AI), the unprecedented progress of large language models (LLMs) in natural language processing (NLP) offers an opportunity to revisit the entire approach of traditional metrics of machine intelligence, both in form and content.
Grounded Language Acquisition From Object and Action Imagery
Deep learning approaches to natural language processing have made great strides in recent years.
Automatically measuring speech fluency in people with aphasia: first achievements using read-speech data
The four predictors were finally combined into multivariate regression models (a multiplelinear regression - MLR, and two non-linear models) to predict the average SLP ratings of speech fluency, using a leave-one speaker-out validation scheme.
Bootstrapping Developmental AIs: From Simple Competences to Intelligent Human-Compatible AIs
The mainstream AIs approaches are the generative and deep learning approaches with large language models (LLMs) and the manually constructed symbolic approach.
On the Computational Modeling of Meaning: Embodied Cognition Intertwined with Emotion
This document chronicles this author's attempt to explore how words come to mean what they do, with a particular focus on child language acquisition and what that means for models of language understanding.\footnote{I say \emph{historical} because I synthesize the ideas based on when I discovered them and how those ideas influenced my later thinking.}
