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--- |
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license: cc-by-4.0 |
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language: |
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- is |
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--- |
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## Introduction |
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This dataset, derived from the Icelandic Gigaword Corpus, is designed as a more comprehensive alternative to the existing dataset found at |
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https://huggingface.co/datasets/styletts2-community/multilingual-pl-bert/tree/main/is. |
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The original dataset, derived from just 52MB of raw text from the Icelandic Wikipedia, was processed using the espeak-ng backend for |
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normalization and phonemization. However, the Icelandic module of espeak-ng, which has not been updated for over a decade, employs an outdated |
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IPA dialect and a simplistic approach to stress marking. Additionally, the limited phonemization capabilities of the module independently |
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contribute to inaccuracies in the phonetic transcriptions. |
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Significant advancements in the normalization and G2P (Grapheme-to-Phoneme) conversion of Icelandic have been made through the Icelandic |
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Language Technology program. More information about this program can be found [here](https://clarin.is/en/links/LTProjectPlan/). |
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The tools developed in this program have been extensively used to enhance the quality of this dataset. |
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## Dataset |
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This dataset surpasses its predecessor considerably in size, incorporating not only text from the relatively small Icelandic Wikipedia but also |
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from the extensive Icelandic Gigaword corpus. Specifically, we have enriched the |
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[Wikipedia text](https://repository.clarin.is/repository/xmlui/handle/20.500.12537/252) with material from the |
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[News1 corpus](https://repository.clarin.is/repository/xmlui/handle/20.500.12537/237). To adhere to the maximum size limit of 512 MB for the |
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raw text, we combined the complete Wikipedia text with randomly shuffled documents from the News1 corpus until reaching the size cap. |
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In total, the dataset contains `400.676` rows, each corresponding to its associated document in the IGC corpus' XML file. |
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### Cleaning |
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Prior to processing with the [Bert](https://huggingface.co/bert-base-multilingual-cased) tokenizer, the dataset underwent cleaning, deduplication, |
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and language detection to filter out most non-Icelandic text. Documents containing fewer than 10 words were also removed. |
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This preprocessing resulted in the elimination of 8,146 documents from the initial 55,475 in the Wikipedia corpus (approximately 14.7%) |
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and 28,869 from 1,545,671 in the News1 corpus (about 1.9%). The notably higher reduction in the Wikipedia corpus primarily arose from the |
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minimum word count criterion. However, this did not significantly diminish the total volume of text, which only saw a modest decrease from |
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52.3MB to 49.68MB, a reduction of around 5%. |
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### Normalization |
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For normalization, we adapted the [Regina Normalizer](https://github.com/grammatek/regina_normalizer), which employs a BI-LSTM Part-of-Speech |
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(PoS) tagger. Although this makes the process somewhat time-consuming, the adaptions were necessary to handle a variety of edge cases in the diverse |
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and sometimes unclean text within the IGC. The processing of approximately 2.5 GB of raw text took about one day, utilizing 50 CPU cores. |
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### Phonemization |
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Phonemization was conducted using [IceG2P](https://github.com/grammatek/ice-g2p), which is also based on a BI-LSTM model. We made adaptations |
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to ensure the IPA phoneset output aligns with the overall phoneset used in other PL-Bert datasets. Initially, we created and refined a new vocabulary |
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from both the normalized Wikipedia and News1 corpora. Following this, the BI-LSTM model was employed to generate phonetic transcriptions for the dictionary. |
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We also enhanced stress labeling and incorporated secondary stresses after conducting compound analysis. |
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A significant byproduct of this effort is a considerably improved G2P dictionary with more than 2.1 million transcriptions, which we plan to |
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integrate into the G2P module and various other open-source projects involving Icelandic G2P. |
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Ultimately, to ensure textual coherence, all paragraphs with incorrect Grapheme-to-Phoneme (G2P) transcriptions were excluded from the dataset. |
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## License |
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The dataset is distributed under the same CC-by-4.0 license as the original source material from which the data was derived. |
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