File size: 7,620 Bytes
e5b2709 aa712cb a4bea2e aa712cb a4bea2e aa712cb a4bea2e 9130cda 5543b40 a4bea2e 5543b40 a4bea2e e5b2709 aa712cb a4bea2e 6b1418c a4bea2e 5543b40 6b1418c 9130cda 5543b40 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 |
---
configs:
- config_name: "English"
default: True
data_files:
- split: train
path: Eng-NA/train.csv
- split: valid
path: Eng-NA/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
|