Common Voice Scripted Speech 25.0 - Yiddish

License:

CC0-1.0

Steward:

Common Voice

Task: ASR

Release Date: 3/22/2026

Format: MP3

Size: 42.70 MB

Description

A collection of read speech recordings in Yiddish (אידיש).

Specifics

Licensing

Creative Commons Zero v1.0 Universal (CC0-1.0)

https://spdx.org/licenses/CC0-1.0.html

Considerations

Restrictions/Special Constraints

None provided.

Forbidden Usage

It is forbidden to attempt to determine the identity of speakers in the Common Voice datasets. It is forbidden to re-host or re-share this dataset.

Processes

Intended Use

This dataset is intended to be used for training and evaluating automatic speech recognition (ASR) models. It may also be used for applications relating to computer-aided language learning (CALL) and language or heritage revitalisation.

Metadata

אידיש — Yiddish (`yi`)

This datasheet is for cv-corpus-25.0-2026-03-09 of the Mozilla Common Voice Scripted Speech dataset for Yiddish [אידיש - yi]. The dataset contains 1999 clips representing 2.2 hours of recorded speech (2.04 hours validated) from 124 speakers, recorded from a text corpus of 1,635 sentences.

Language

Accents

Code	Accent	Clips	Speakers
-		1,004 (50.2%)	14 (11.3%)

Demographic information

The dataset includes the following self-declared age and gender distributions. A coverage summary is shown below each table.

Gender

Self-declared gender information. The table shows clip and speaker counts with percentages. Speakers who did not declare a gender are listed as Unspecified. A dash (-) indicates zero.

Code	Gender	Clips	Speakers
male_masculine	Male, masculine	5 (0.3%)	1 (0.8%)
female_feminine	Female, feminine	-	-
transgender	Transgender	-	-
non-binary	Non-binary	-	-
do_not_wish_to_say	Prefer not to say	-	-
-	Unspecified	1,994 (99.7%)	124 (100.0%)

Gender declared: 5 of 1,999 clips (0.3%), 0 of 124 speakers (0.0%)

Age

Self-declared age information. The table shows clip and speaker counts with percentages. Speakers who did not declare an age are listed as Unspecified. A dash (-) indicates zero.

Code	Age	Clips	Speakers
teens	Teens	217 (10.9%)	1 (0.8%)
twenties	Twenties	123 (6.2%)	8 (6.5%)
thirties	Thirties	128 (6.4%)	2 (1.6%)
fourties	Fourties	-	-
fifties	Fifties	-	-
sixties	Sixties	-	-
seventies	Seventies	-	-
eighties	Eighties	-	-
nineties	Nineties	-	-
-	Unspecified	1,531 (76.6%)	120 (96.8%)

Age declared: 468 of 1,999 clips (23.4%), 4 of 124 speakers (3.2%)

Data splits for modelling

Clip buckets

Bucket	Clips
Validated	1,849 (92.5%)
Invalidated	87 (4.4%)
Other	63 (3.2%)

Training splits

Split	Clips
Train	483 (26.1%)
Dev	460 (24.9%)
Test	451 (24.4%)

Training split coverage: 1,394 of 1,849 validated clips (75.4%)

The dataset contains 1849 validated, 87 invalidated, and 63 unresolved clips. The average clip duration is 3.975 seconds.

Text corpus

Validated sentences: 1,550

Category	Count
Unvalidated sentences	85
Pending sentences	1
Rejected sentences	84
Reported sentences	17

The corpus contains 1,635 sentences: 1,550 validated and 85 unvalidated (1 pending review, 84 rejected), with 17 reported for review.

Sample

There follows a randomly selected sample of five sentences from the corpus.

איז ער געגאנגען צו אים
דורכ'ן זיי באַשיצן פון דאַרפן אַריבערגיין אַן ענליכן גורל
נאך יארן וואס די מדינת ישראל פאליציי באנוצט זיך מיט וואסער קאנאנאן
אין דער מעטראָפּאָליע ניו יאָרק
גאָט זאָל אױף אים אָנשיקן פֿון די צען מכּות די בעסטע.

Sources

Source	Sentences
sentence-collector	667 (43.0%)
i made them myself	494 (31.9%)
https://yiddishwit.com/List.html	234 (15.1%)
תהלימל ניגון	32 (2.1%)
אייגענע	22 (1.4%)
Self	21 (1.4%)
original work	16 (1.0%)
Other	64 (4.1%)

Text domains

Code	Domain	Clips	Speakers
general	General	13 (0.7%)	10 (8.1%)
agriculture_food	Agriculture and Food	-	-
automotive_transport	Automotive and Transport	-	-
finance	Finance	2 (0.1%)	2 (1.6%)
service_retail	Service and Retail	-	-
healthcare	Healthcare	-	-
history_law_government	History, Law and Government	1 (0.1%)	1 (0.8%)
media_entertainment	Media and Entertainment	-	-
nature_environment	Nature and Environment	3 (0.2%)	3 (2.4%)
news_current_affairs	News and Current Affairs	-	-
technology_robotics	Technology and Robotics	-	-
language_fundamentals	Language Fundamentals	-	-

Fields

Clips

Each row of a tsv file represents a single audio clip, and contains the following information:

client_id - hashed UUID of a given user
path - relative path of the audio file
text - supposed transcription of the audio
up_votes - number of people who said audio matches the text
down_votes - number of people who said audio does not match text
age - age of the speaker1
gender - gender of the speaker1
accents - accents of the speaker1
variant - variant of the language1
segment - if sentence belongs to a custom dataset segment, it will be listed here
prompt_upvotes - number of upvotes the sentence prompt received
prompt_reports - number of reports the sentence prompt received
is_edited - whether the clip's transcription has been edited

`validated_sentences.tsv`

The validated_sentences.tsv file contains one row per validated sentence in the text corpus:

sentence_id - unique identifier for the sentence
sentence - the sentence text
variant - the variant of the language
sentence_domain - the domain(s) the sentence belongs to
source - the source the sentence was collected from
is_used - whether the sentence is still in circulation for recording
clips_count - number of clips recorded for this sentence

`unvalidated_sentences.tsv`

The unvalidated_sentences.tsv file contains one row per unvalidated sentence in the text corpus:

sentence_id - unique identifier for the sentence
sentence - the sentence text
variant - the variant of the language
sentence_domain - the domain(s) the sentence belongs to
source - the source the sentence was collected from
up_votes - number of upvotes the sentence received
down_votes - number of downvotes the sentence received
status - current status of the sentence (pending or rejected)

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Licence

This dataset is released under the Creative Commons Zero (CC-0) licence. By downloading this data you agree to not determine the identity of speakers in the dataset.

Footnotes

For a full list of age, gender, and accent options, see the demographics spec. These will only be reported if the speaker opted in to provide that information. ↩ ↩2 ↩3 ↩4