asr_6gram_lm

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Authors : Carlos Daniel Hernández Mena ([email protected]).

Language : Icelandic.

Recommended use : speech recognition.

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Description

"6-GRAM Language Model in Icelandic for NeMo (Binary Format) 22.06" is a word level n-gram language model in binary format suitable for recognizers based on the NVIDIA-NeMo framework [1].

This language model was originally created to be used in the field of Automatic Speech Recognition (ASR). In specific, it was designed for the following NeMo recipe, developed by the Language and Voice Lab (LVL) at Reykjavík University in 2022:

https://github.com/cadia-lvl/samromur-asr/tree/n5_samromur/n5_samromur

Nevertheless, due to the flexibility of this kind of resources and their possible application in other tasks, systems or code recipes; it was decided to publish this model as an independent item.

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The Language Model

The language model was created using the Icelandic Gigaword Corpus [2]. The
Gigaword corpus contains text from newspaper articles, parliamentary speeches, adjudications, books, transcribed radio/television news and more. The normalization process of the sentences utilized to generate the language model includes to allowing only characters belonging to the Icelandic alphabet, expanding numbers and abbreviations, and removing punctuation marks [3]. The resulting text has a length of more than 44 million lines of text (5.3GB approximately), and it was used to create a pruned 6-gram language model with the SRILM toolkit [4].

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Citation

When publishing results based on the models please refer to:

Mena, Carlos; "6-GRAM Language Model in Icelandic for NeMo (Binary Format) 22.06". Web Download. Reykjavik University: Language and Voice Lab, 2022.

Contact: Carlos Mena ([email protected])

License: CC BY 4.0

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Acknowledgements

This initiative was funded by the Language Technology Programme for Icelandic 2019-2023. The programme, which is managed and coordinated by Almannarómur, is funded by the Icelandic Ministry of Education, Science and Culture.

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References

[1] Kuchaiev, O., Li, J., Nguyen, H., Hrinchuk, O., Leary, R., Ginsburg, B., ... & Cohen, J. M. (2019). Nemo: a toolkit for building ai applications using neural modules. arXiv preprint arXiv:1909.09577.

[2] Steingrímsson, S., Helgadóttir, S., Rögnvaldsson, E., Barkarson, S., & Guðnason, J. (2018, May). Risamálheild: A very large Icelandic text corpus. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018).

[3] Nikulásdóttir, A. B., Helgadóttir, I. R., Pétursson, M., & Guðnason, J. (2018, May). Open ASR for Icelandic: Resources and a baseline system. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018).

[4] Stolcke, A. (2002). SRILM-an extensible language modeling toolkit. In Seventh international conference on spoken language processing.

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