Common Voice Scripted Speech 25.0 - Macedonian

License:

CC0-1.0

Steward:

Common Voice

Task: ASR

Release Date: 3/22/2026

Format: MP3

Size: 1.02 GB

Description

A collection of read speech recordings in Macedonian (Македонски).

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

Македонски — Macedonian (`mk`)

This datasheet is for cv-corpus-25.0-2026-03-09 of the Mozilla Common Voice Scripted Speech dataset for Macedonian [Македонски - mk]. The dataset contains 41227 clips representing 55.04 hours of recorded speech (24.97 hours validated) from 468 speakers, recorded from a text corpus of 6,694 sentences.

Language

Accents

Code	Accent	Clips	Speakers
-		11,503 (27.9%)	93 (19.9%)

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	11,321 (27.5%)	12 (2.6%)
female_feminine	Female, feminine	15,959 (38.7%)	77 (16.5%)
transgender	Transgender	-	-
non-binary	Non-binary	-	-
do_not_wish_to_say	Prefer not to say	35 (0.1%)	2 (0.4%)
-	Unspecified	13,912 (33.7%)	408 (87.2%)

Gender declared: 27,315 of 41,227 clips (66.3%), 60 of 468 speakers (12.8%)

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	1,052 (2.6%)	10 (2.1%)
twenties	Twenties	14,747 (35.8%)	56 (12.0%)
thirties	Thirties	10,927 (26.5%)	29 (6.2%)
fourties	Fourties	8,114 (19.7%)	35 (7.5%)
fifties	Fifties	807 (2.0%)	13 (2.8%)
sixties	Sixties	1,251 (3.0%)	7 (1.5%)
seventies	Seventies	-	-
eighties	Eighties	-	-
nineties	Nineties	-	-
-	Unspecified	4,329 (10.5%)	361 (77.1%)

Age declared: 36,898 of 41,227 clips (89.5%), 107 of 468 speakers (22.9%)

Data splits for modelling

Clip buckets

Bucket	Clips
Validated	18,703 (45.4%)
Invalidated	1,055 (2.6%)
Other	21,469 (52.1%)

Training splits

Split	Clips
Train	2,067 (11.1%)
Dev	1,815 (9.7%)
Test	1,828 (9.8%)

Training split coverage: 5,710 of 18,703 validated clips (30.5%)

The dataset contains 18703 validated, 1055 invalidated, and 21469 unresolved clips. The average clip duration is 4.807 seconds.

Text corpus

Validated sentences: 6,123

Category	Count
Unvalidated sentences	571
Pending sentences	400
Rejected sentences	171
Reported sentences	161

The corpus contains 6,694 sentences: 6,123 validated and 571 unvalidated (400 pending review, 171 rejected), with 161 reported for review.

Sample

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

Во меѓувреме, корисно би било барем работите да ги наречеме со вистинските имиња.
На небото се појавува виножито.
Кој е телефонскиот број на Ива?
Решив да ги отворам двете стаклени окна и да проветрам.
Кучињата скитници огромни, посакуваш да си бил едно од нив во претходниот живот.

Sources

Source	Sentences
sentence-collector	5,095 (83.2%)
okno.mk	262 (4.3%)
time.mk	187 (3.1%)
??? ?? ???????	119 (1.9%)
https://raw.githubusercontent.com/kjanko/deep-speech-mk-sentences/master/kjanko.txt	70 (1.1%)
Other	390 (6.4%)

Text domains

Code	Domain	Clips	Speakers
general	General	219 (0.5%)	103 (22.0%)
agriculture_food	Agriculture and Food	14 (0.0%)	12 (2.6%)
automotive_transport	Automotive and Transport	-	-
finance	Finance	7 (0.0%)	7 (1.5%)
service_retail	Service and Retail	-	-
healthcare	Healthcare	27 (0.1%)	23 (4.9%)
history_law_government	History, Law and Government	9 (0.0%)	9 (1.9%)
media_entertainment	Media and Entertainment	7 (0.0%)	7 (1.5%)
nature_environment	Nature and Environment	21 (0.1%)	20 (4.3%)
news_current_affairs	News and Current Affairs	-	-
technology_robotics	Technology and Robotics	1 (0.0%)	1 (0.2%)
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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Community links

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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