--- license: cc-by-sa-3.0 license_name: cc-by-sa configs: - config_name: en data_files: en.json default: true - config_name: en-xl data_files: en-xl.json - config_name: ca data_files: ca.json - config_name: de data_files: de.json - config_name: es data_files: es.json - config_name: el data_files: el.json - config_name: fa data_files: fa.json - config_name: fi data_files: fi.json - config_name: fr data_files: fr.json - config_name: it data_files: it.json - config_name: pl data_files: pl.json - config_name: pt data_files: pt.json - config_name: ru data_files: ru.json - config_name: sv data_files: sv.json - config_name: uk data_files: uk.json - config_name: zh data_files: zh.json language: - en - ca - de - es - el - fa - fi - fr - it - pl - pt - ru - sv - uk - zh tags: - synthetic --- # Multilingual Phonemes 10K Alpha This dataset contains approximately 10,000 pairs of text and phonemes from each supported language. We support 15 languages in this dataset, so we have a total of ~150K pairs. This does not include the English-XL dataset, which includes another 100K unique rows. ## Languages We support 15 languages, which means we have around 150,000 pairs of text and phonemes in multiple languages. This excludes the English-XL dataset, which has 100K unique (not included in any other split) additional phonemized pairs. * English (en) * English-XL (en-xl): ~100K phonemized pairs, English-only * Catalan (ca) * German (de) * Spanish (es) * Greek (el) * Persian (fa): Requested by [@Respair](https://huggingface.co/Respair) * Finnish (fi) * French (fr) * Italian (it) * Polish (pl) * Portuguese (pt) * Russian (ru) * Swedish (sw) * Ukrainian (uk) * Chinese (zh): Thank you to [@eugenepentland](https://huggingface.co/eugenepentland) for assistance in processing this text, as East-Asian languages are the most compute-intensive! ## License + Credits Source data comes from [Wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) and is licensed under CC-BY-SA 3.0. This dataset is licensed under CC-BY-SA 3.0. ## Processing We utilized the following process to preprocess the dataset: 1. Download data from [Wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) by language, selecting only the first Parquet file and naming it with the language code 2. Process using [Data Preprocessing Scripts (StyleTTS 2 Community members only)](https://huggingface.co/styletts2-community/data-preprocessing-scripts) and modify the code to work with the language 3. Script: Clean the text 4. Script: Remove ultra-short phrases 5. Script: Phonemize 6. Script: Save JSON 7. Upload dataset ## Note East-Asian languages are experimental. We do not distinguish between Traditional and Simplified Chinese. The dataset consists mainly of Simplified Chinese in the `zh` split. We recommend converting characters to Simplified Chinese during inference, using a library such as `hanziconv` or `chinese-converter`.