Datasets:

phonemetransformers
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IPA-CHILDES

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Subset (31)

EnglishNA · 2.56M rows

Split (1)

train · 2.56M rows

processed_gloss stringlengths 2 482	ipa_transcription stringlengths 15 2.02k	character_split_utterance stringlengths 17 2.13k	is_child bool 2 classes	id int64 306k 17.8M	gloss stringlengths 1 481	stem stringlengths 1 435	type stringclasses 14 values	language stringclasses 11 values	num_morphemes int64 -2,147,483,648 102	num_tokens int64 1 97	part_of_speech stringlengths 1 442	speaker_role stringclasses 26 values	target_child_age float64 3 144 ⌀	target_child_sex stringclasses 3 values	collection_id int64 2 21	corpus_id int64 34 337	speaker_id int64 1.64k 23.5k	target_child_id int64 -2,147,483,648 23.5k	transcript_id int64 3.63k 44.5k
did they.	d ɪ d WORD_BOUNDARY ð eɪ WORD_BOUNDARY	d i d WORD_BOUNDARY t h e y . WORD_BOUNDARY	false	2,855,307	did they	do they	trail off	eng	3	2	mod pro:sub	Investigator	null	unknown	2	76	4,227	-2,147,483,648	11,240
yeah.	j ɛ h WORD_BOUNDARY	y e a h . WORD_BOUNDARY	false	2,855,339	yeah	yeah	declarative	eng	1	1	co	Investigator	null	unknown	2	76	4,227	-2,147,483,648	11,240
remember us doing that.	ɹ ɪ m ɛ m b ə ɹ ɹ WORD_BOUNDARY ʌ s WORD_BOUNDARY d uː ɪ ŋ WORD_BOUNDARY ð æ t WORD_BOUNDARY	r e m e m b e r WORD_BOUNDARY u s WORD_BOUNDARY d o i n g WORD_BOUNDARY t h a t . WORD_BOUNDARY	false	2,855,352	remember us doing that	remember us do that	declarative	eng	5	4	v pro:obj part comp	Mother	null	unknown	2	76	5,704	-2,147,483,648	11,240
so they didn't have this to this extent but.	s oʊ WORD_BOUNDARY ð eɪ WORD_BOUNDARY d ɪ d n t WORD_BOUNDARY h æ v WORD_BOUNDARY ð ɪ s WORD_BOUNDARY t ə WORD_BOUNDARY ð ɪ s WORD_BOUNDARY ɛ k s t ɛ n t WORD_BOUNDARY b ʌ t WORD_BOUNDARY	s o WORD_BOUNDARY t h e y WORD_BOUNDARY d i d n ' t WORD_BOUNDARY h a v e WORD_BOUNDARY t h i s WORD_BOUNDARY t o WORD_BOUNDARY t h i s WORD_BOUNDARY e x t e n t WORD_BOUNDARY b u t . WORD_BOUNDARY	false	2,855,366	so they didn't have this to this extent but	so they do have this to this extent but	trail off	eng	11	9	co pro:sub mod v det:dem prep det:dem n conj	Mother	null	unknown	2	76	5,704	-2,147,483,648	11,240
yeah yeah.	j ɛ h WORD_BOUNDARY j ɛ h WORD_BOUNDARY	y e a h WORD_BOUNDARY y e a h . WORD_BOUNDARY	false	2,855,388	yeah yeah	yeah yeah	declarative	eng	2	2	co co	Investigator	null	unknown	2	76	4,227	-2,147,483,648	11,240
and i don't remember the animals last time but.	æ n d WORD_BOUNDARY aɪ WORD_BOUNDARY d oʊ n t WORD_BOUNDARY ɹ ɪ m ɛ m b ə ɹ WORD_BOUNDARY ð ɪ WORD_BOUNDARY æ n ɪ m ə l z WORD_BOUNDARY l æ s t WORD_BOUNDARY t aɪ m WORD_BOUNDARY b ʌ t WORD_BOUNDARY	a n d WORD_BOUNDARY i WORD_BOUNDARY d o n ' t WORD_BOUNDARY r e m e m b e r WORD_BOUNDARY t h e WORD_BOUNDARY a n i m a l s WORD_BOUNDARY l a s t WORD_BOUNDARY t i m e WORD_BOUNDARY b u t . WORD_BOUNDARY	false	2,855,400	and I don't remember the animals last time but	and I do remember the animal last time but	trail off	eng	11	9	coord pro:sub mod v det:art n adj n conj	Mother	null	unknown	2	76	5,704	-2,147,483,648	11,240
mhm yeah okay.	ɛ m eɪ t̠ʃ ɛ m WORD_BOUNDARY j ɛ h WORD_BOUNDARY oʊ k eɪ WORD_BOUNDARY	m h m WORD_BOUNDARY y e a h WORD_BOUNDARY o k a y . WORD_BOUNDARY	false	2,855,415	mhm yeah okay	mhm yeah okay	declarative	eng	3	3	co co co	Investigator	null	unknown	2	76	4,227	-2,147,483,648	11,240
well i think i think she's doing good she's a great kid.	w ɛ l WORD_BOUNDARY aɪ WORD_BOUNDARY θ ɪ ŋ k WORD_BOUNDARY aɪ WORD_BOUNDARY θ ɪ ŋ k WORD_BOUNDARY ʃ iː z WORD_BOUNDARY d uː ɪ ŋ WORD_BOUNDARY ɡ ʊ d WORD_BOUNDARY ʃ iː z WORD_BOUNDARY ʌ WORD_BOUNDARY ɡ ɹ eɪ t WORD_BOUNDARY k ɪ d WORD_BOUNDARY	w e l l WORD_BOUNDARY i WORD_BOUNDARY t h i n k WORD_BOUNDARY i WORD_BOUNDARY t h i n k WORD_BOUNDARY s h e ' s WORD_BOUNDARY d o i n g WORD_BOUNDARY g o o d WORD_BOUNDARY s h e ' s WORD_BOUNDARY a WORD_BOUNDARY g r e a t WORD_BOUNDARY k i d . WORD_BOUNDARY	false	2,855,439	well I think I think she's doing good she's a great kid	well I I think she do good she a great kid	declarative	eng	14	12	co pro:sub pro:sub v pro:sub part adj pro:sub det:art adj n	Investigator	null	unknown	2	76	4,227	-2,147,483,648	11,240
yeah she's fun.	j ɛ h WORD_BOUNDARY ʃ iː z WORD_BOUNDARY f ʌ n WORD_BOUNDARY	y e a h WORD_BOUNDARY s h e ' s WORD_BOUNDARY f u n . WORD_BOUNDARY	false	2,855,463	yeah she's fun	yeah she fun	declarative	eng	4	3	co pro:sub n	Mother	null	unknown	2	76	5,704	-2,147,483,648	11,240
and she persevered.	æ n d WORD_BOUNDARY ʃ iː WORD_BOUNDARY p ɜː s ɪ v ɪ ɹ d WORD_BOUNDARY	a n d WORD_BOUNDARY s h e WORD_BOUNDARY p e r s e v e r e d . WORD_BOUNDARY	false	2,855,480	and she persevered	and she persevere	declarative	eng	4	3	coord pro:sub v	Investigator	null	unknown	2	76	4,227	-2,147,483,648	11,240
yeah she did.	j ɛ h WORD_BOUNDARY ʃ iː WORD_BOUNDARY d ɪ d WORD_BOUNDARY	y e a h WORD_BOUNDARY s h e WORD_BOUNDARY d i d . WORD_BOUNDARY	false	2,855,499	yeah she did	yeah she do	declarative	eng	4	3	co pro:sub v	Mother	null	unknown	2	76	5,704	-2,147,483,648	11,240
so.	s oʊ WORD_BOUNDARY	s o . WORD_BOUNDARY	false	2,855,526	so	so	trail off	eng	1	1	co	Investigator	null	unknown	2	76	4,227	-2,147,483,648	11,240
and the woman came and cut it off early and i was like oh what happened she was like oh she's asleep.	æ n d WORD_BOUNDARY ð ə WORD_BOUNDARY w ʊ m ə n WORD_BOUNDARY k eɪ m WORD_BOUNDARY æ n d WORD_BOUNDARY k ʌ t WORD_BOUNDARY ɪ t WORD_BOUNDARY ɔ f WORD_BOUNDARY ɜː l i WORD_BOUNDARY æ n d WORD_BOUNDARY aɪ WORD_BOUNDARY w ʌ z WORD_BOUNDARY l aɪ k WORD_BOUNDARY oʊ WORD_BOUNDARY w ʌ t WORD_BOUNDARY h æ p ə n d WORD_BOUNDARY ʃ iː WORD_BOUNDARY w ʌ z WORD_BOUNDARY l aɪ k WORD_BOUNDARY oʊ WORD_BOUNDARY ʃ iː z WORD_BOUNDARY ʌ s l iː p WORD_BOUNDARY	a n d WORD_BOUNDARY t h e WORD_BOUNDARY w o m a n WORD_BOUNDARY c a m e WORD_BOUNDARY a n d WORD_BOUNDARY c u t WORD_BOUNDARY i t WORD_BOUNDARY o f f WORD_BOUNDARY e a r l y WORD_BOUNDARY a n d WORD_BOUNDARY i WORD_BOUNDARY w a s WORD_BOUNDARY l i k e WORD_BOUNDARY o h WORD_BOUNDARY w h a t WORD_BOUNDARY h a p p e n e d WORD_BOUNDARY s h e WORD_BOUNDARY w a s WORD_BOUNDARY l i k e WORD_BOUNDARY o h WORD_BOUNDARY s h e ' s WORD_BOUNDARY a s l e e p . WORD_BOUNDARY	false	2,855,564	and the woman came and cut it off early and I was like oh what happened she was like oh she's asleep	and the woman come and cut it off early and I be like oh what happen she be like oh she asleep	declarative	eng	30	22	coord det:art n v coord v pro:per adv adv coord pro:sub cop co co pro:int v pro:sub cop co co pro:sub adv	Mother	null	unknown	2	76	5,704	-2,147,483,648	11,240
because she was sitting there and then she just.	b ɪ k ʌ z WORD_BOUNDARY ʃ iː WORD_BOUNDARY w ʌ z WORD_BOUNDARY s ɪ t ɪ ŋ WORD_BOUNDARY ð ɛ ɹ WORD_BOUNDARY æ n d WORD_BOUNDARY ð ɛ n WORD_BOUNDARY ʃ iː WORD_BOUNDARY d̠ʒ ʌ s t WORD_BOUNDARY	b e c a u s e WORD_BOUNDARY s h e WORD_BOUNDARY w a s WORD_BOUNDARY s i t t i n g WORD_BOUNDARY t h e r e WORD_BOUNDARY a n d WORD_BOUNDARY t h e n WORD_BOUNDARY s h e WORD_BOUNDARY j u s t . WORD_BOUNDARY	false	2,855,587	because she was sitting there and then she just	because she be sit there and then she just	trail off	eng	12	9	conj pro:sub aux part adv coord adv:tem pro:sub adv	Mother	null	unknown	2	76	5,704	-2,147,483,648	11,240

Subsets and Splits

IPA Frequency in CHILDES

The query reveals the most frequent International Phonetic Alphabet (IPA) elements in a sample of 10,000 English words, providing a clear insight into common phonetic characteristics.

IPA Elements Frequency Chart

Identifies and ranks the most frequent IPA elements from 1000000 samples, providing a clear view of phonetic prominence in the dataset.

IPA Frequency Analysis

Reveals the most common IPA elements in the dataset, displaying their frequencies and providing a visual chart, which can help in understanding the phonetic structure of the English pronunciation dataset.