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---
configs:
- config_name: "English"
default: True
data_files:
- split: train
path: Eng-NA/train.csv
- split: valid
path: Eng-NA/valid.csv
- config_name: "English2"
data_files:
- split: train
path: Eng-NA2/train.csv
- split: valid
path: Eng-NA2/valid.csv
- config_name: "French"
data_files:
- split: train
path: French/train.csv
- split: valid
path: French/valid.csv
- config_name: "German"
data_files:
- split: train
path: German/train.csv
- split: valid
path: German/valid.csv
- config_name: "Spanish"
data_files:
- split: train
path: Spanish/train.csv
- split: valid
path: Spanish/valid.csv
- config_name: "Dutch"
data_files:
- split: train
path: Dutch/train.csv
- split: valid
path: Dutch/valid.csv
- config_name: "Mandarin"
data_files:
- split: train
path: Mandarin/train.csv
- split: valid
path: Mandarin/valid.csv
- config_name: "Japanese"
data_files:
- split: train
path: Japanese/train.csv
- split: valid
path: Japanese/valid.csv
- config_name: "Cantonese"
data_files:
- split: train
path: Cantonese/train.csv
- split: valid
path: Cantonese/valid.csv
- config_name: "Estonian"
data_files:
- split: train
path: Estonian/train.csv
- split: valid
path: Estonian/valid.csv
- config_name: "Croatian"
data_files:
- split: train
path: Croatian/train.csv
- split: valid
path: Croatian/valid.csv
- config_name: "Danish"
data_files:
- split: train
path: Danish/train.csv
- split: valid
path: Danish/valid.csv
- config_name: "Basque"
data_files:
- split: train
path: Basque/train.csv
- split: valid
path: Basque/valid.csv
- config_name: "Hungarian"
data_files:
- split: train
path: Hungarian/train.csv
- split: valid
path: Hungarian/valid.csv
- config_name: "Turkish"
data_files:
- split: train
path: Turkish/train.csv
- split: valid
path: Turkish/valid.csv
- config_name: "Farsi"
data_files:
- split: train
path: Farsi/train.csv
- split: valid
path: Farsi/valid.csv
- config_name: "Icelandic"
data_files:
- split: train
path: Icelandic/train.csv
- split: valid
path: Icelandic/valid.csv
- config_name: "Indonesian"
data_files:
- split: train
path: Indonesian/train.csv
- split: valid
path: Indonesian/valid.csv
language:
- en
- de
- fr
- es
- nl
- cmn
- ja
- yue
- et
- hr
- da
- eu
- hu
- tr
- fa
- is
- id
tags:
- language modeling
- cognitive modeling
pretty_name: Phonemized Child Directed Speech
size_categories:
- 100K<n<1M
---
# Phonemized Child Directed Speech Dataset
This dataset contains utterance downloaded from CHILDES which have been pre-processed and converted to phonemic transcriptions by this [processing script](https://github.com/codebyzeb/Corpus-Phonemicizers). Many of the columns from CHILDES have been preserved in case they may be useful for experiments (e.g. number of morphemes, part-of-speech tags, etc.). The key columns added by the processing script are as follows:
| Column | Description |
|:----|:-----|
| `is_child`| Whether the utterance was spoken by a child or not. Note that this is set to `False` for all utterances in this dataset, but the processing script has the ability to preserve child utterances.|
| `processed_gloss`| The pre-processed orthographic utterance. This includes lowercasing, fixing English spelling and adding punctuation marks. This is based on the [AOChildes](https://github.com/UIUCLearningLanguageLab/AOCHILDES) preprocessing.|
| `phonemized_utterance`| A phonemic transcription of the utterance, space-separated with word boundaries marked with the `WORD_BOUNDARY` token.|
| `language_code`| Language code used for producing the phonemic transcriptions. May not match the `language` column provided by CHILDES (e.g. Eng-NA and Eng-UK tend to be transcribed with eng-us and eng-gb). |
| `character_split_utterance`| A space separated transcription of the utterance, produced simply by splitting the processed gloss by character. This is intended to have a very similar format to `phonemized_utterance` for studies comparing phonetic to orthographic transcriptions. |
The last two columns are designed for training character-based (phoneme-based) language models using a simple tokenizer that splits around whitespace. The `processed_gloss` column is suitable for word-based (or subword-based) language models with standard tokenizers.
Note that the data has been sorted by the `target_child_age` column, which stores child age in months. This can be used to limit the training data according to a maximum child age, if you wish.
Each subset of the data is split into a training split containing most of the utterances and an in-distribution validation split containing 10,000 utterances. The following languages are included (ordered by number of phonemes):
| Language | Description | Speakers | Utterances | Words | Phonemes
|:----|:-----|:-----|:----|:-----|:-----|
| English | Taken from 44 corpora in Eng-NA collection of CHILDES and phonemized using language code `en-us`. | 2,692 | 1,646,954 | 7,090,066 | 21,932,139
| German | Taken from 10 corpora in German collection of CHILDES and phonemized using language code `ge`. | 627 | 850,888 | 3,893,168 | 14,058,836
| Indonesian | Taken from 1 corpus in EastAsian/Indonesian collection of CHILDES and phonemized using language code `id`. | 389 | 534,469 | 1,587,526 | 6,367,721
| Mandarin | Taken from 15 corpora in Chinese/Mandarin collection of CHILDES and phonemized using a [pinyin to IPA convertor](https://github.com/stefantaubert/pinyin-to-ipa/tree/master). | 15 | 883 | 326,759 | 1,511,851 | 6,106,770
| French | Taken from 11 corpora in French collection of CHILDES and phonemized using language code `fr-fr`. | 722 | 432,133 | 1,995,063 | 5,510,523
| Spanish | Taken from 18 corpora in Spanish collection of CHILDES and phonemized using language code `es`. | 562 | 286,462 | 1,266,366 | 4,511,261
| Japanese | Taken from 9 corpora in Japanese collection of CHILDES and phonemized using segments with language `japanese`. | 320 | 412,079 | 1,113,194 | 4,346,638
| Dutch | Taken from 5 corpora in DutchAfricaans/Dutch collection of CHILDES and phonemized using language code `nl`. | 86 | 297,497 | 1,246,006 | 4,034,742
| Estonian | Taken from 9 corpora in Other/Estonian collection of CHILDES and phonemized using language code `et`. | 118 | 103,343 | 544,680 | 2,347,066
| Cantonese | Taken from 2 corpora in Chinese/Cantonese collection of CHILDES and phonemized by converting from jyutping to IPA using the [pingyam database](https://github.com/kfcd/pingyam/tree/master). | 80 | 136,727 | 591,314 | 2,118,731
| Croatian | Taken from 1 corpus in Slavic/Croatian collection of CHILDES and phonemized using language code `hr`. | 51 | 55,284 | 214,921 | 813,619
| Icelandic | Taken from 2 corpora in Scandinavian/Icelandic collection of CHILDES and phonemized using language code `is`. | 15 | 50,657 | 197,519 | 772,952
| Danish | Taken from 1 corpus in Scandinavian/Danish collection of CHILDES and phonemized using language code `da`. | 1 | 48,976 | 192,527 | 579,375
| Basque | Taken from 2 corpora in Other/Basque collection of CHILDES and phonemized using language code `eu`. | 150 | 36,614 | 135,866 | 565,633
| Hungarian | Taken from 3 corpora in Other/Hungarian collection of CHILDES and phonemized using language code `hu`. | 65 | 31,633 | 116,917 | 478,444
| Turkish | Taken from 2 corpora in Other/Turkish collection of CHILDES and phonemized using language code `tr`. | 35 | 14,487 | 43,823 | 230,737
| Farsi | Taken from 2 corpora in Other/Farsi collection of CHILDES and phonemized using language code `fa-latn`. | 23 | 13,467 | 28,080 | 116,081
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