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Task: ASR
Release Date: 3/23/2026
Format: MP3
Size: 3.16 GB
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A collection of read speech recordings in Dutch (Nederlands).
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.
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.
nl)This datasheet is for cv-corpus-25.0-2026-03-09 of the Mozilla Common Voice Scripted Speech dataset for Dutch [Nederlands - nl]. The dataset contains 115815 clips representing 140.62 hours of recorded speech (126.22 hours validated) from 1874 speakers, recorded from a text corpus of 271,413 sentences.
| Code | Accent | Clips | Speakers |
|---|---|---|---|
| netherlands | Nederlands Nederlands | 80,548 (69.5%) | 593 (31.6%) |
| belgium | Belgisch Nederlands | 8,966 (7.7%) | 151 (8.1%) |
| suriname | Surinaams Nederlands | 737 (0.6%) | 1 (0.1%) |
| curacao | Nederlands van Curaçao | 195 (0.2%) | 2 (0.1%) |
| france | Frans Nederlands | 109 (0.1%) | 6 (0.3%) |
| germany | Duits Nederlands | 60 (0.1%) | 5 (0.3%) |
| aruba | Nederlands van Aruba | 51 (0.0%) | 1 (0.1%) |
| south_africa | Zuid-Afrikaans Nederlands | 10 (0.0%) | 1 (0.1%) |
| - | Other | 1,576 (1.4%) | 40 (2.1%) |
The dataset includes the following self-declared age and gender distributions. A coverage summary is shown below each table.
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 | 59,904 (51.7%) | 527 (28.1%) |
| female_feminine | Female, feminine | 11,579 (10.0%) | 155 (8.3%) |
| transgender | Transgender | - | - |
| non-binary | Non-binary | - | - |
| do_not_wish_to_say | Prefer not to say | - | - |
| - | Unspecified | 44,332 (38.3%) | 1,296 (69.2%) |
Gender declared: 71,483 of 115,815 clips (61.7%), 578 of 1,874 speakers (30.8%)
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 | 2,147 (1.9%) | 38 (2.0%) |
| twenties | Twenties | 21,030 (18.2%) | 281 (15.0%) |
| thirties | Thirties | 13,850 (12.0%) | 179 (9.6%) |
| fourties | Fourties | 21,326 (18.4%) | 114 (6.1%) |
| fifties | Fifties | 13,184 (11.4%) | 68 (3.6%) |
| sixties | Sixties | 2,119 (1.8%) | 36 (1.9%) |
| seventies | Seventies | 96 (0.1%) | 6 (0.3%) |
| eighties | Eighties | 15 (0.0%) | 1 (0.1%) |
| nineties | Nineties | 5 (0.0%) | 1 (0.1%) |
| - | Unspecified | 42,043 (36.3%) | 1,271 (67.8%) |
Age declared: 73,772 of 115,815 clips (63.7%), 603 of 1,874 speakers (32.2%)
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 103,951 (89.8%) |
| Invalidated | 6,139 (5.3%) |
| Other | 5,725 (4.9%) |
Training splits
| Split | Clips |
|---|---|
| Train | 46,392 (44.6%) |
| Dev | 12,247 (11.8%) |
| Test | 12,247 (11.8%) |
Training split coverage: 70,886 of 103,951 validated clips (68.2%)
The dataset contains 103951 validated, 6139 invalidated, and 5725 unresolved clips. The average clip duration is 4.371 seconds.
Validated sentences: 260,894
| Category | Count |
|---|---|
| Unvalidated sentences | 10,519 |
| Pending sentences | 10,410 |
| Rejected sentences | 109 |
| Reported sentences | 407 |
The corpus contains 271,413 sentences: 260,894 validated and 10,519 unvalidated (10,410 pending review, 109 rejected), with 407 reported for review.
There follows a randomly selected sample of five sentences from the corpus.
Dit is een echt succesverhaal.
We hebben uw steun niet nodig, maar ik hoop wel dat we hem krijgen.
Hoe gevoeliger een onderwerp is, des te omzichtiger het moet worden behandeld.
Er kunnen verschillende maatregelen genomen worden.
We moeten onze prioriteiten eens op een rijtje zetten.
| Source | Sentences |
|---|---|
| europarl | 191,664 (73.5%) |
| sentence-collector | 61,717 (23.7%) |
| danielsjf | 4,028 (1.5%) |
| Other | 3,383 (1.3%) |
| Code | Domain | Clips | Speakers |
|---|---|---|---|
| general | General | 455 (0.4%) | 34 (1.8%) |
| agriculture_food | Agriculture and Food | 18 (0.0%) | 6 (0.3%) |
| automotive_transport | Automotive and Transport | 21 (0.0%) | 11 (0.6%) |
| finance | Finance | 8 (0.0%) | 4 (0.2%) |
| service_retail | Service and Retail | - | - |
| healthcare | Healthcare | 56 (0.0%) | 9 (0.5%) |
| history_law_government | History, Law and Government | 59 (0.1%) | 7 (0.4%) |
| media_entertainment | Media and Entertainment | 3 (0.0%) | 2 (0.1%) |
| nature_environment | Nature and Environment | 56 (0.0%) | 9 (0.5%) |
| news_current_affairs | News and Current Affairs | 4 (0.0%) | 3 (0.2%) |
| technology_robotics | Technology and Robotics | 5 (0.0%) | 3 (0.2%) |
| language_fundamentals | Language Fundamentals | 179 (0.2%) | 20 (1.1%) |
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.tsvThe 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.tsvThe 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)
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.
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