---
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
---

# Multilingual Phonemes 10K Alpha

### By [mrfakename](https://twitter.com/realmrfakename)

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.

This dataset is for training **open source** models only.

## 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

This dataset is for training **open source** models only.

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`.