Carlos Hernández Mena


2023

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ASR Language Resources for Faroese
Carlos Hernández Mena | Annika Simonsen | Jon Gudnason
Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)

The aim of this work is to present a set of novel language resources in Faroese suitable for the field of Automatic Speech Recognition including: an ASR corpus comprised of 109 hours of transcribed speech data, acoustic models in systems such as WAV2VEC2, NVIDIA-NeMo, Kaldi and PocketSphinx; a set of n-gram language models and a set of pronunciation dictionaries with two different variants of Faroese. We also show comparison results between the distinct acoustic models presented here. All the resources exposed in this document are publicly available under creative commons licences.

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Standardising Pronunciation for a Grapheme-to-Phoneme Converter for Faroese
Sandra Lamhauge | Iben Debess | Carlos Hernández Mena | Annika Simonsen | Jon Gudnason
Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)

Pronunciation dictionaries allow computational modelling of the pronunciation of words in a certain language and are widely used in speech technologies, especially in the fields of speech recognition and synthesis. On the other hand, a grapheme-to-phoneme tool is a generalization of a pronunciation dictionary that is not limited to a given and finite vocabulary. In this paper, we present a set of standardized phonological rules for the Faroese language; we introduce FARSAMPA, a machine-readable character set suitable for phonetic transcription of Faroese, and we present a set of grapheme-to-phoneme models for Faroese, which are publicly available and shared under a creative commons license. We present the G2P converter and evaluate the performance. The evaluation shows reliable results that demonstrate the quality of the data.