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Francis Tyers

6 accepted papers

2025

Ihquin tlahtouah in Tetelahtzincocah: An annotated, multi-purpose audio and text corpus of Western Sierra Puebla Nahuatl

NAACL 2025long

The development of digital linguistic resources is essential for enhancing the inclusion of indigenous and marginalized languages in the digital domain. Indigenous languages of Mexico, despite representing vast typological diversity and millions of speakers, have largely been overlooked in NLP until…

2024

Developing a Benchmark for Pronunciation Feedback: Creation of a Phonemically Annotated Speech Corpus of isiZulu Language Learner Speech

COLING 2024main

Pronunciation of the phonemic inventory of a new language often presents difficulties to second language (L2) learners. These challenges can be alleviated by the development of pronunciation feedback tools that take speech input from learners and return information about errors in the utterance. Thi…

Cited by 0SourcePDFScholar
2024

Producing a Parallel Universal Dependencies Treebank of Ancient Hebrew and Ancient Greek via Cross-Lingual Projection

COLING 2024main

In this paper we present the initial construction of a treebank of Ancient Greek containing portions of the Septuagint, a translation of the Hebrew Scriptures (1576 sentences, 39K tokens, roughly 7% of the total corpus). We construct the treebank by word-aligning and projecting from the parallel tex…

Cited by 0SourcePDFScholar
2021

A Large-Scale Study of Machine Translation in Turkic Languages

EMNLP 2021main

Recent advances in neural machine translation (NMT) have pushed the quality of machine translation systems to the point where they are becoming widely adopted to build competitive systems. However, there is still a large number of languages that are yet to reap the benefits of NMT. In this paper, we…

2021

Do RNN States Encode Abstract Phonological Alternations?

NAACL 2021long

Sequence-to-sequence models have delivered impressive results in word formation tasks such as morphological inflection, often learning to model subtle morphophonological details with limited training data. Despite the performance, the opacity of neural models makes it difficult to determine whether…