Search Results for author:
Found 22 papers, 4 papers with code
Depth-Bounded Statistical PCFG Induction as a Model of Human Grammar Acquisition
Abstract This article describes a simple PCFG induction model with a fixed category domain that predicts a large majority of attested constituent boundaries, and predicts labels consistent with nearly half of attested constituent labels on a standard evaluation data set of child-directed speech.
Primum Non Nocere: Before working with Indigenous data, the ACL must confront ongoing colonialism
In this paper, we challenge the ACL community to reckon with historical and ongoing colonialism by adopting a set of ethical obligations and best practices drawn from the Indigenous studies literature.
How to encode arbitrarily complex morphology in word embeddings, no corpus needed
In this paper, we present a straightforward technique for constructing interpretable word embeddings from morphologically analyzed examples (such as interlinear glosses) for all of the world’s languages.
Illinois Japanese \leftrightarrow English News Translation for WMT 2021
This system paper describes an end-to-end NMT pipeline for the Japanese \leftrightarrow English news translation task as submitted to WMT 2021, where we explore the efficacy of techniques such as tokenizing with language-independent and language-dependent tokenizers, normalizing by orthographic conversion, creating a politeness-and-formality-aware model by implementing a tagger, back-translation, model ensembling, and n-best reranking.
Expanding Universal Dependencies for Polysynthetic Languages: A Case of St. Lawrence Island Yupik
This paper describes the development of the first Universal Dependencies (UD) treebank for St. Lawrence Island Yupik, an endangered language spoken in the Bering Strait region.
A Digital Corpus of St. Lawrence Island Yupik
St. Lawrence Island Yupik (ISO 639-3: ess) is an endangered polysynthetic language in the Inuit-Yupik language family indigenous to Alaska and Chukotka.
Morphology Matters: A Multilingual Language Modeling Analysis
We fill in missing typological data for several languages and consider corpus-based measures of morphological complexity in addition to expert-produced typological features.
Neural Polysynthetic Language Modelling
In the literature, languages like Finnish or Turkish are held up as extreme examples of complexity that challenge common modelling assumptions.
Improved Finite-State Morphological Analysis for St. Lawrence Island Yupik Using Paradigm Function Morphology
In this work, we present a re-implementation of the Chen {\&} Schwartz (2018) finite-state morphological analyzer for St. Lawrence Island Yupik that incorporates new linguistic insights; in particular, in this implementation we make use of the Paradigm Function Morphology (PFM) theory of morphology.
Unsupervised Learning of PCFGs with Normalizing Flow
This paper describes a neural PCFG inducer which employs context embeddings (Peters et al., 2018) in a normalizing flow model (Dinh et al., 2015) to extend PCFG induction to use semantic and morphological information.
Community lexical access for an endangered polysynthetic language: An electronic dictionary for St. Lawrence Island Yupik
If a user searches for an inflected Yupik word form, we perform a morphological analysis and return entries for the root word and for any derivational suffixes present in the word.
Depth-bounding is effective: Improvements and evaluation of unsupervised PCFG induction
There have been several recent attempts to improve the accuracy of grammar induction systems by bounding the recursive complexity of the induction model (Ponvert et al., 2011; Noji and Johnson, 2016; Shain et al., 2016; Jin et al., 2018).
Unsupervised Grammar Induction with Depth-bounded PCFG
There has been recent interest in applying cognitively or empirically motivated bounds on recursion depth to limit the search space of grammar induction models (Ponvert et al., 2011; Noji and Johnson, 2016; Shain et al., 2016).
DLVM: A modern compiler infrastructure for deep learning systems
Deep learning software demands reliability and performance.
Memory-Bounded Left-Corner Unsupervised Grammar Induction on Child-Directed Input
This paper presents a new memory-bounded left-corner parsing model for unsupervised raw-text syntax induction, using unsupervised hierarchical hidden Markov models (UHHMM).
Fast, Scalable Phrase-Based SMT Decoding
The utilization of statistical machine translation (SMT) has grown enormously over the last decade, many using open-source software developed by the NLP community.
