How to Choose Successful Losers in Error-Driven Phonotactic Learning

The Error-driven Ranking Model of the Acquisition of Phonotactics: How to Keep the Faithfulness Constraints at Bay

Simple induction of (deterministic) probabilistic finite-state automata for phonotactics by stochastic gradient descent

We introduce a simple and highly general phonotactic learner which induces a probabilistic finite-state automaton from word-form data. We describe the learner and show how to parameterize it to induce unrestricted regula…

Automated Quality Control for Language Documentation: Detecting Phonotactic Inconsistencies in a Kokborok Wordlist

Lexical data collection in language documentation often contains transcription errors and undocumented borrowings that can mislead linguistic analysis. We present unsupervised anomaly detection methods to identify phonot…

How Phonotactics Affect Multilingual and Zero-shot ASR Performance

The idea of combining multiple languages' recordings to train a single automatic speech recognition (ASR) model brings the promise of the emergence of universal speech representation. Recently, a Transformer encoder-deco…

Modeling U.S. State-Level Policies by Extracting Winners and Losers from Legislative Texts

Decisions on state-level policies have a deep effect on many aspects of our everyday life, such as health-care and education access. However, there is little understanding of how these policies and decisions are being fo…