← Search

Rolando Coto-Solano

7 accepted papers

2024

Development of Community-Oriented Text-to-Speech Models for Māori ‘Avaiki Nui (Cook Islands Māori)

COLING 2024main

In this paper we describe the development of a text-to-speech system for Māori ‘Avaiki Nui (Cook Islands Māori). We provide details about the process of community-collaboration that was followed throughout the project, a continued engagement where we are trying to develop speech and language technol…

Cited by 0Source ↗PDF ↗Scholar ↗
2024

Multilingual Models for ASR in Chibchan Languages

NAACL 2024long

We present experiments on Automatic Speech Recognition (ASR) for Bribri and Cabécar, two languages from the Chibchan family. We fine-tune four ASR algorithms (Wav2Vec2, Whisper, MMS & WavLM) to create monolingual models, with the Wav2Vec2 model demonstrating the best performance. We then proceed to…

Cited by 0Source ↗PDF ↗Scholar ↗
2024

Parsing for Mauritian Creole Using Universal Dependencies

COLING 2024main

This paper presents a first attempt to apply Universal Dependencies (De Marneffe et al., 2021) to train a parser for Mauritian Creole (MC), a French-based Creole language spoken on the island of Mauritius. This paper demonstrates the construction of a 161-sentence (1007-token) treebank for MC and ev…

2023

Improving Syntactic Probing Correctness and Robustness with Control Tasks

ACL 2023short

Syntactic probing methods have been used to examine whether and how pre-trained language models (PLMs) encode syntactic features. However, the probing methods are usually biased by the PLMs’ memorization of common word co-occurrences, even if they do not form syntactic relations. This paper presents…

Cited by 1Source ↗PDF ↗Scholar ↗
2022

AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages

ACL 2022long

Pretrained multilingual models are able to perform cross-lingual transfer in a zero-shot setting, even for languages unseen during pretraining. However, prior work evaluating performance on unseen languages has largely been limited to low-level, syntactic tasks, and it remains unclear if zero-shot l…

2020

Neural Machine Translation Models with Back-Translation for the Extremely Low-Resource Indigenous Language Bribri

COLING 2020main

This paper presents a neural machine translation model and dataset for the Chibchan language Bribri, with an average performance of BLEU 16.9±1.7. This was trained on an extremely small dataset (5923 Bribri-Spanish pairs), providing evidence for the applicability of NMT in extremely low-resource env…