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Task: ASR
Release Date: 6/17/2026
Format: MP3
Size: 34.88 MB
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A collection of read speech recordings in Alsatian (Elsassisch).
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.
gsw)This datasheet is for cv-corpus-26.0-2026-06-12 of the Mozilla Common Voice Scripted Speech dataset for Alsatian [Elsassisch - gsw]. The dataset contains 1124 clips representing 1.78 hours of recorded speech (0.78 hours validated) from 43 speakers, recorded from a text corpus of 100 sentences.
Elsassisch (Alsatian in English, Alsacien in French) is a language spoken in the Alsace region in the East of France. As of 2022, 46 % of the population of the region declares speaking Alsatian. The term Alsatian refers to a linguistic continuum that includes varieties of Alemannic and Franconian. It shares the Alemannic language family with Swiss German and the Franconian language family with Luxembourgish.
Note on the language code : There is currently no language code for specifically Alsatian. GSW is the code of Swiss German. However, the Common Voice community for Swiss German has chosen to be included under the umbrella of German, and thus isn't using the language code. It has been agreed to use GSW for Alsatian in the context of Common Voice. This does not mean that Alsatian is the same as Swiss German (even if some features are shared), and care should be taken to not mix up the two languages.
| Code | Variant | Clips | Speakers |
|---|---|---|---|
| gsw-FR-nordalem | Nordniederàlemmànisch (Rishoffe, Zàwere, Bùsswìller, Hawenau, Brüemt, Stroossbùri, Molse, Dàmbàch, Schlettstàtt, Pfàlzbùri usw.) | 475 (42.3%) | 15 (34.9%) |
| gsw-FR-sudnalem | Südniederàlemmànisch (Kolmer, Gawìller, Mìlhüüsa, Àltkìrich, usw.) | 62 (5.5%) | 3 (7.0%) |
| gsw-FR-rhinfran | Rhinfränkisch (Bùckenùmm, Lìtzelstän, Bitsch, Saargemìnn usw.) | 38 (3.4%) | 1 (2.3%) |
| Code | Accent | Clips | Speakers |
|---|---|---|---|
| - | 115 (10.2%) | 3 (7.0%) |
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 | - | - |
| female_feminine | Female, feminine | 516 (45.9%) | 18 (41.9%) |
| transgender | Transgender | - | - |
| non-binary | Non-binary | - | - |
| do_not_wish_to_say | Prefer not to say | - | - |
| - | Unspecified | 608 (54.1%) | 25 (58.1%) |
Gender declared: 516 of 1,124 clips (45.9%), 18 of 43 speakers (41.9%)
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 | - | - |
| twenties | Twenties | 6 (0.5%) | 1 (2.3%) |
| thirties | Thirties | 43 (3.8%) | 2 (4.7%) |
| fourties | Fourties | 50 (4.4%) | 2 (4.7%) |
| fifties | Fifties | 261 (23.2%) | 11 (25.6%) |
| sixties | Sixties | 540 (48.0%) | 15 (34.9%) |
| seventies | Seventies | 73 (6.5%) | 2 (4.7%) |
| eighties | Eighties | 5 (0.4%) | 1 (2.3%) |
| nineties | Nineties | - | - |
| - | Unspecified | 146 (13.0%) | 11 (25.6%) |
Age declared: 978 of 1,124 clips (87.0%), 32 of 43 speakers (74.4%)
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 493 (43.9%) |
| Invalidated | 58 (5.2%) |
| Other | 573 (51.0%) |
Training splits
| Split | Clips |
|---|---|
| Train | 31 (6.3%) |
| Dev | 28 (5.7%) |
| Test | 28 (5.7%) |
Training split coverage: 87 of 493 validated clips (17.6%)
The dataset contains 493 validated, 58 invalidated, and 573 unresolved clips. The average clip duration is 5.718 seconds.
Validated sentences: 87
| Category | Count |
|---|---|
| Unvalidated sentences | 13 |
| Pending sentences | 12 |
| Rejected sentences | 1 |
| Reported sentences | 2 |
The corpus contains 100 sentences: 87 validated and 13 unvalidated (12 pending review, 1 rejected), with 2 reported for review.
There follows a randomly selected sample of five sentences from the corpus.
D’letschte Wùche hàn ùns viel Changement gebroocht.
Na, wie seht's üss, sener jetz ferti met de Arwet?
Gutnacht isch geh jetzt ins Bett
Dü wùrsch ne schùn kenne lehre.
Villicht meh àls ìhr.
| Source | Sentences |
|---|---|
| Salbschtzitat | 22 (25.3%) |
| D'r Millionengartner, Ferdinand Bastian, 1900, https://methal.eu/ui/text/html/bastian-dr-millionengartner/ | 12 (13.8%) |
| Sainte-Cécile! Julius Greber, 1897, https://methal.eu/ui/text/tei/greber-sainte-cecile/ | 8 (9.2%) |
| D'r Prophet, Gustave Stoskopf, 1902, https://methal.eu/ui/text/html/stoskopf-dr-prophet/ | 6 (6.9%) |
| D'Madam fahrt Velo, Adolphe Horsch, 1901, https://methal.eu/ui/text/tei/horsch-d-madam-fahrt-velo/ | 6 (6.9%) |
| D'r Herr Maire, Gustave Stoskopf, 1898, https://methal.eu/ui/text/tei/stoskopf-dr-herr-maire/ | 6 (6.9%) |
| Heimlichi Lieb, Ernst Fuchs, 1914, https://methal.eu/ui/text/html/fuchs-heimlichi-lieb/ | 6 (6.9%) |
| E Hochzitter im Kleiderkaschte, Julius Greber, 1900, https://methal.eu/ui/text/html/greber-e-hochzitter-im-kleiderkaschte/ | 6 (6.9%) |
| L'oubli? (Das Vergessen?) Hermann Günther, 1905, https://methal.eu/ui/text/html/gunther-l-oubli/ | 5 (5.7%) |
| Other | 10 (11.5%) |
| Code | Domain | Clips | Speakers |
|---|---|---|---|
| general | General | 247 (22.0%) | 25 (58.1%) |
| agriculture_food | Agriculture and Food | - | - |
| automotive_transport | Automotive and Transport | - | - |
| finance | Finance | - | - |
| service_retail | Service and Retail | 26 (2.3%) | 18 (41.9%) |
| healthcare | Healthcare | 15 (1.3%) | 10 (23.3%) |
| history_law_government | History, Law and Government | 3 (0.3%) | 3 (7.0%) |
| media_entertainment | Media and Entertainment | 865 (77.0%) | 41 (95.3%) |
| nature_environment | Nature and Environment | - | - |
| news_current_affairs | News and Current Affairs | 16 (1.4%) | 11 (25.6%) |
| technology_robotics | Technology and Robotics | - | - |
| language_fundamentals | Language Fundamentals | - | - |
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
sentence - the sentence to be read aloud
sentence_id - unique identifier for the sentence
sentence_domain - domain classification(s) of the sentence
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
locale - locale code of the language
segment - if sentence belongs to a custom dataset segment, it will be listed here
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