Common Voice dataset
E405893
The Common Voice dataset is a large, open-source multilingual speech corpus created by Mozilla to support and democratize voice recognition research and technology.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Common Voice dataset canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4018894 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Common Voice dataset Context triple: [Mozilla, operates, Common Voice dataset]
-
A.
CORDE corpus
The CORDE corpus is a large historical Spanish language corpus compiled by the Royal Spanish Academy, used for studying the evolution and usage of Spanish over time.
-
B.
Versoix
Versoix is a Swiss municipality on the shores of Lake Geneva, known as a residential suburb of Geneva with lakeside promenades and a mix of urban and natural landscapes.
-
C.
Google Cloud Text-to-Speech
Google Cloud Text-to-Speech is a cloud-based service that converts text into natural-sounding speech using advanced deep learning models.
-
D.
Inflection AI
Inflection AI is an artificial intelligence company focused on developing advanced conversational AI systems, co-founded by DeepMind co-founder Mustafa Suleyman.
-
E.
Visible Speech
Visible Speech is a 19th-century phonetic notation system devised by Alexander Melville Bell to visually represent the position and movement of speech organs for any spoken sound.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Common Voice dataset Target entity description: The Common Voice dataset is a large, open-source multilingual speech corpus created by Mozilla to support and democratize voice recognition research and technology.
-
A.
CORDE corpus
The CORDE corpus is a large historical Spanish language corpus compiled by the Royal Spanish Academy, used for studying the evolution and usage of Spanish over time.
-
B.
Versoix
Versoix is a Swiss municipality on the shores of Lake Geneva, known as a residential suburb of Geneva with lakeside promenades and a mix of urban and natural landscapes.
-
C.
Google Cloud Text-to-Speech
Google Cloud Text-to-Speech is a cloud-based service that converts text into natural-sounding speech using advanced deep learning models.
-
D.
Inflection AI
Inflection AI is an artificial intelligence company focused on developing advanced conversational AI systems, co-founded by DeepMind co-founder Mustafa Suleyman.
-
E.
Visible Speech
Visible Speech is a 19th-century phonetic notation system devised by Alexander Melville Bell to visually represent the position and movement of speech organs for any spoken sound.
- F. None of above. chosen
Statements (102)
| Predicate | Object |
|---|---|
| instanceOf |
multilingual dataset
ⓘ
open-source dataset ⓘ speech corpus ⓘ |
| collectionMethod | crowdsourcing ⓘ |
| creator | Mozilla ⓘ |
| dataFormat |
JSON
ⓘ
MP3 ⓘ WAV ⓘ |
| developer | Mozilla ⓘ |
| downloadURL | https://commonvoice.mozilla.org/datasets ⓘ |
| goal |
democratize voice recognition technology
ⓘ
support under-resourced languages ⓘ |
| hasFeature |
accent metadata
ⓘ
speaker age metadata ⓘ speaker gender metadata ⓘ |
| hasLanguage |
Afrikaans
ⓘ
Albanian language ⓘ
surface form:
Albanian
Amharic ⓘ Arabic ⓘ Basque ⓘ Belarusian language ⓘ
surface form:
Belarusian
Bengali ⓘ Bosnian ⓘ Breton ⓘ Cantonese ⓘ Catalan ⓘ Chinese ⓘ Croatian ⓘ Czech ⓘ Danish ⓘ Dutch ⓘ English ⓘ Esperanto ⓘ Finnish language ⓘ
surface form:
Finnish
French ⓘ Georgian language ⓘ
surface form:
Georgian
German ⓘ Greek ⓘ Gujarati ⓘ Hausa ⓘ Hindi ⓘ Hungarian language ⓘ
surface form:
Hungarian
Igbo ⓘ Indonesian ⓘ Interlingua ⓘ Irish ⓘ Italian ⓘ Japanese ⓘ Javanese ⓘ Kabyle ⓘ Kannada ⓘ Kinyarwanda ⓘ Korean ⓘ Kurdish language ⓘ
surface form:
Kurdish
Latvian ⓘ Lithuanian ⓘ Macedonian ⓘ Malay ⓘ Malayalam ⓘ Marathi language ⓘ
surface form:
Marathi
Norwegian language ⓘ
surface form:
Norwegian
Persian ⓘ Polish language ⓘ
surface form:
Polish
Portuguese ⓘ Punjabi language ⓘ
surface form:
Punjabi
Romanian language ⓘ
surface form:
Romanian
Russian ⓘ Scottish Gaelic ⓘ Serbian language ⓘ
surface form:
Serbian
Slovak language ⓘ
surface form:
Slovak
Slovene ⓘ
surface form:
Slovenian
Spanish ⓘ Swahili language ⓘ
surface form:
Swahili
Swedish language ⓘ
surface form:
Swedish
Tagalog ⓘ Tamil ⓘ Tatar language ⓘ
surface form:
Tatar
Telugu ⓘ Thai ⓘ Turkish ⓘ Turkmen language ⓘ
surface form:
Turkmen
Ukrainian ⓘ Urdu language ⓘ
surface form:
Urdu
Vietnamese ⓘ Welsh ⓘ Xhosa ⓘ Yoruba ⓘ Zulu ⓘ |
| hasLicense |
CC0
ⓘ
CC0 ⓘ
surface form:
Creative Commons Zero
|
| hasPart |
audio recordings
ⓘ
speaker metadata ⓘ text transcripts ⓘ |
| hostedBy | Mozilla ⓘ |
| inception | 2017 ⓘ |
| isAccessibleForFree | true ⓘ |
| sponsor | Mozilla Foundation ⓘ |
| use |
automatic speech recognition training
ⓘ
language identification research ⓘ speaker diarization research ⓘ speech technology research ⓘ |
| website | https://commonvoice.mozilla.org ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Common Voice dataset Description of subject: The Common Voice dataset is a large, open-source multilingual speech corpus created by Mozilla to support and democratize voice recognition research and technology.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.