European audio data catalogue
European audio datasets. 50+ dialects. One team.
Browse production-ready European audio by language, environment, vertical, or compliance requirement. Every dataset includes speaker demographics, device metadata, acoustic conditions, and full consent provenance.
- Datasets on catalogue
- 53
- Hours of audio
- 70,250
- European dialects
- 50+
- Contributors
- 210,000+
150+ languages covered · Full demographic metadata · GDPR-native consent · EU AI Act documentation
Filter dimensions
Find What Your Model Needs
Most audio vendors give you a spreadsheet. We give you a catalog built for how ML engineers actually evaluate training data.
Every programme is specified across the dimensions that determine whether audio ships to production or fails in deployment.
Filter by language architecture
Not just "German" but Swiss German (Zürich), Swiss German (Bern), Austrian German (Vienna), Bavarian, Swabian. Not just "English" but Glaswegian, Scouse, Belfast, Dublin. Select the specific variant your users actually speak.
Filter by acoustic conditions
Studio reference. Office ambient. Automotive highway at 120 km/h. Factory floor with heavy machinery. Hospital ward. Call center crosstalk. Warehouse logistics. Maritime bridge. Each environment is tagged with SNR ranges and noise classification.
Filter by elicitation type
Scripted read speech for baseline phoneme coverage. Spontaneous conversation for real-world variation. Command and control for voice interface training. Emotional expression for prosodic models. Specify what your architecture requires.
Filter by speaker demographics
Age bands. Gender distribution. Native vs. non-native. Regional origin. Education level. Occupation category. Every speaker profile is documented. Build balanced datasets or target specific populations.
Filter by device characteristics
Professional studio microphone. Smartphone (iOS/Android, model-specific). Laptop built-in. Headset. Far-field array. In-vehicle microphone array. Know exactly what hardware captured your training data.
Filter by compliance requirements
GDPR consent with revocation support. Biometric-safe processing under Article 9. EU AI Act Article 10 documentation. Full provenance chain. De-identified variants available. Select the governance level your legal team requires.
The catalogue
Eight Dataset Families
Every dataset we hold, listed with its hour count. Filter by family or search by language, dialect, city or acoustic environment. Selecting a family shows the brief for that family above the rows.
The problem
Your model trained on standard German hits 8% WER on broadcast news and 35% WER on a customer from Zürich. Training data recorded in Berlin doesn't transfer to Bavaria. British English benchmarks collapse in Glasgow.
Why it matters
Dialect variation isn't an edge case. For pan-European deployment, regional speech is the majority of your production traffic. Models trained on standard accents systematically exclude large user populations.
What we provide
Native speakers recorded in their home regions, with documented geographic origin, dialect classification, and sub-regional variation. Deep vertical coverage, not thin horizontal breadth.
The problem
Real European speakers switch languages mid-sentence. A Frankfurt banker mixes English and German. A Brussels professional alternates French and Dutch. Your monolingual training data can't follow the conversation.
Why it matters
Code-switching is the default in European business, tech, and urban contexts. Models trained on monolingual corpora fail on real-world multilingual users. Intent recognition breaks when the language changes.
What we provide
Authentic bilingual speakers producing natural code-switching. Annotated language boundaries. Both intra-sentential switching (mid-sentence) and inter-sentential switching (sentence-level alternation).
The problem
Your ASR works perfectly in the lab. Then it enters production. Highway wind noise. Factory machinery. Hospital alarms. The gap between benchmark WER and production WER is 2.8x to 5.7x.
Why it matters
Studio recordings don't prepare models for deployment. Clean speech corpora create a domain mismatch that no amount of fine-tuning on clean data will fix. You need training data from the acoustic environments where your model will actually run.
What we provide
Speech recorded in real operational environments with calibrated noise levels. SNR metadata. Noise type classification. Device and microphone position documentation.
The problem
Your general-purpose ASR doesn't know that "cabg" means coronary artery bypass graft. It transcribes "Brent crude" as "brand crude." Domain vocabulary isn't optional: it's the difference between 5% WER and 25% WER.
Why it matters
Every vertical has specialized terminology that general speech models never encountered in training. Medical, financial, legal, and technical domains require purpose-built corpora.
What we provide
Industry-specific vocabulary coverage. Domain expert speakers. Realistic operational contexts. Terminology validation by subject matter experts.
The problem
Speech biomarker research requires audio from clinical populations. Parkinson's tremor. Post-stroke dysarthria. Cognitive decline markers. Healthy control datasets don't capture pathological speech patterns.
Why it matters
Healthcare AI needs training data from real patient populations, collected with appropriate consent and privacy protections. Clinical audio requires specialized collection protocols and ethical oversight.
What we provide
Clinical-speech programmes are designed per engagement: collection under clinical research protocols with ethics approval, longitudinal tracking, and condition-specific recruitment, configured and verified with the customer before any collection.
The problem
Your TTS sounds robotic because it was trained on neutral read speech. Your sentiment model can't distinguish anger from frustration. Prosodic variation requires purpose-built training data.
Why it matters
Next-generation voice AI requires emotional range. Character voices. Dynamic dialogue. Customer sentiment detection. Neutral corpora can't teach these patterns.
What we provide
Acted and spontaneous emotional speech. Valence and arousal annotations. Prosodic contour documentation. Voice actor and natural speaker variants.
The problem
Sami has 30,000 speakers. Basque has 750,000. Frisian has 500,000. These communities deserve voice AI that works, but commercial providers ignore them. Your European deployment isn't complete without regional and minority coverage.
Why it matters
EU accessibility requirements increasingly cover minority language support. Public sector deployments in Norway, Finland, Spain require regional language capability. Low-resource languages need purpose-built collection, not thin crowd-sourced samples.
What we provide
Community-partnered collection. Cultural and linguistic consultation. Dialect documentation. Orthographic and phonetic transcription.
The problem
You're fine-tuning Whisper or training a custom ASR, and you need clean, legally unambiguous, consent-verified audio. Public datasets have unclear provenance. Your legal team wants to know exactly where every hour came from.
Why it matters
EU AI Act Article 10 requires documented training data provenance. Undocumented data creates regulatory exposure. Foundation model training requires bulletproof consent chains.
What we provide
Studio-quality reference recordings with unambiguous consent. Zero synthetic contamination. Full speaker demographics. Explicit commercial licensing.
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Swiss German Zürich Conversational
2,400 hours of spontaneous dialogue from Zürich canton. Urban and suburban speakers. Alemannic dialect features documented.
Request this sampleDialects and Regional Speech2,400 hours -
Swiss German Bern Regional
1,800 hours covering Bernese Oberland, Emmental, and Seeland sub-dialects. Rural and small-town speakers.
Request this sampleDialects and Regional Speech1,800 hours -
Bavarian Multi-Regional
3,200 hours across Upper Bavaria, Lower Bavaria, and Upper Palatinate. Munich urban contrasted with rural Altbayern.
Request this sampleDialects and Regional Speech3,200 hours -
Austrian German Vienna
2,100 hours of Viennese German. Service industry, professional, and casual registers.
Request this sampleDialects and Regional Speech2,100 hours -
Glaswegian Conversational
1,400 hours of working-class and professional Glasgow speech. Central Belt variation.
Request this sampleDialects and Regional Speech1,400 hours -
Scouse Liverpool Urban
900 hours of Merseyside English. Multi-generational coverage.
Request this sampleDialects and Regional Speech900 hours -
Andalusian Spanish Multi-City
2,800 hours covering Seville, Málaga, Granada, and Cádiz. Seseo, ceceo, and aspirated /s/ variants documented.
Request this sampleDialects and Regional Speech2,800 hours -
Catalan Barcelona Regional
1,600 hours of Central Catalan. Native and bilingual speakers with code-switching to Spanish.
Request this sampleDialects and Regional Speech1,600 hours -
English-German Frankfurt Business
1,800 hours. Finance, consulting, and tech contexts. Intra-sentential switching dominant.
Request this sampleCode-Switching and Multilingual Speech1,800 hours -
English-German Berlin Tech
1,200 hours. Startup and software development contexts. High English lexical borrowing.
Request this sampleCode-Switching and Multilingual Speech1,200 hours -
English-French Brussels Professional
1,400 hours. EU institutional, legal, and business contexts.
Request this sampleCode-Switching and Multilingual Speech1,400 hours -
English-French Paris Urban
1,100 hours. Service industry and professional contexts. North African French influence.
Request this sampleCode-Switching and Multilingual Speech1,100 hours -
French-Arabic Paris Marseille
1,600 hours. First and second-generation speakers. Maghrebi Arabic features.
Request this sampleCode-Switching and Multilingual Speech1,600 hours -
German-Turkish Berlin Cologne
1,300 hours. Second and third-generation speakers. Kiezdeutsch features documented.
Request this sampleCode-Switching and Multilingual Speech1,300 hours -
English-Spanish Barcelona Miami
900 hours. Catalan-influenced Spanish with English switching.
Request this sampleCode-Switching and Multilingual Speech900 hours -
Swedish-Finnish Helsinki Bilingual
700 hours. Finland-Swedish speakers with Finnish code-switching.
Request this sampleCode-Switching and Multilingual Speech700 hours -
Automotive Highway European
4,200 hours across 18 vehicle models. 80-130 km/h conditions. HVAC on/off. Windows up/down. Driver and passenger positions.
Request this sampleNoisy and Real-World Environments4,200 hours -
Automotive Urban Stop-Start
2,800 hours. City traffic conditions. Engine idle. Intersection stops. Turn signal and indicator noise.
Request this sampleNoisy and Real-World Environments2,800 hours -
Factory Floor Manufacturing
1,600 hours. CNC machinery. Conveyor systems. Forklift traffic. PPE-muffled speech (masks, ear protection).
Request this sampleNoisy and Real-World Environments1,600 hours -
Warehouse Logistics
1,200 hours. Pallet handling. Forklift operations. Scanner beeps. Ambient ventilation.
Request this sampleNoisy and Real-World Environments1,200 hours -
Hospital Ward Ambient
1,400 hours. Medical alarms. Paging systems. Multi-speaker clinical environments. Patient room and corridor acoustics.
Request this sampleNoisy and Real-World Environments1,400 hours -
Call Center Crosstalk
2,200 hours. Adjacent agent bleed. Headset audio. 8kHz telephony compression. Hold music background.
Request this sampleNoisy and Real-World Environments2,200 hours -
Maritime Bridge Operations
600 hours. Engine room proximity. Radio chatter. Weather exposure. Norwegian and English mixed commands.
Request this sampleNoisy and Real-World Environments600 hours -
Offshore Platform Industrial
500 hours. Machinery noise. Wind exposure. Safety equipment environments. Norwegian-English code-switching.
Request this sampleNoisy and Real-World Environments500 hours -
Automotive Voice Command European
3,400 hours. Navigation, media control, climate, and communication commands. 15 languages. Wake word and barge-in scenarios.
Request this sampleVertical-Specific Datasets3,400 hours -
Clinical Dictation German
2,100 hours across 28 specialties. Board-certified physician speakers. Cardiology, radiology, pathology, emergency medicine emphasis.
Request this sampleVertical-Specific Datasets2,100 hours -
Clinical Dictation French
1,800 hours. 22 specialties. Parisian and regional accents. Inpatient and outpatient contexts.
Request this sampleVertical-Specific Datasets1,800 hours -
Financial Trading German English
800 hours. Trading floor recordings. FX, equities, and fixed income terminology. Multi-speaker crosstalk.
Request this sampleVertical-Specific Datasets800 hours -
Legal Dictation German
1,100 hours. Contract law, corporate law, litigation. Formal and informal registers.
Request this sampleVertical-Specific Datasets1,100 hours -
Energy Sector Norwegian English
700 hours. Oil and gas operations. Offshore and onshore contexts. Technical terminology.
Request this sampleVertical-Specific Datasets700 hours -
Maritime Operations Nordic
500 hours. Bridge commands. Port communications. Safety procedures. Norwegian, Swedish, Danish, English.
Request this sampleVertical-Specific Datasets500 hours -
Parkinson's Disease German
180 hours. Early and mid-stage patients. Medication on/off states. Tremor and rigidity markers.
Request this sampleClinical and Pathology Speech180 hours -
Post-Stroke Dysarthria European
220 hours. Aphasia types documented. Recovery progression. Six languages.
Request this sampleClinical and Pathology Speech220 hours -
Mild Cognitive Impairment Nordic
160 hours. Memory clinic patients. Age-matched healthy controls. Longitudinal samples.
Request this sampleClinical and Pathology Speech160 hours -
Depression Screening German
140 hours. PHQ-9 validated severity levels. Prosodic and lexical markers.
Request this sampleClinical and Pathology Speech140 hours -
Respiratory Condition Markers
120 hours. Asthma, COPD, post-COVID. Breathing patterns and voice quality changes.
Request this sampleClinical and Pathology Speech120 hours -
Acted Emotion German Full Range
800 hours. Professional voice actors. Six primary emotions plus blends. High and low intensity variants.
Request this sampleEmotional and Prosodic Speech800 hours -
Acted Emotion English (UK) Full Range
900 hours. Regional actors. RP and regional accent variants. Character archetypes.
Request this sampleEmotional and Prosodic Speech900 hours -
Spontaneous Emotion Call Center
1,400 hours. Real customer interactions (consent-obtained). Frustration, satisfaction, confusion, urgency labeled.
Request this sampleEmotional and Prosodic Speech1,400 hours -
Whispered Speech European
300 hours. Five languages. ASMR-adjacent and privacy-context whispers.
Request this sampleEmotional and Prosodic Speech300 hours -
Shouted and Projected Speech
400 hours. Sports context. Emergency context. Crowd noise overlay variants.
Request this sampleEmotional and Prosodic Speech400 hours -
Gaming Character Archetypes
600 hours. Fantasy, sci-fi, historical character types. European voice actors.
Request this sampleEmotional and Prosodic Speech600 hours -
Northern Sami Norway Finland
120 hours. Native speakers from Kautokeino, Karasjok, and Finnish Lapland. Read and spontaneous speech.
Request this sampleMinority and Low-Resource Languages120 hours -
Basque Euskara Regional
340 hours. Gipuzkoan, Bizkaian, and standard Batua variants. Urban and rural speakers.
Request this sampleMinority and Low-Resource Languages340 hours -
Catalan Full Regional
1,200 hours. Central, Valencian, Balearic, and Northwestern variants.
Request this sampleMinority and Low-Resource Languages1,200 hours -
Welsh North and South
280 hours. Gwynedd and Carmarthenshire variants. First-language and learner speakers.
Request this sampleMinority and Low-Resource Languages280 hours -
Breton Brittany Regional
140 hours. Elderly native speakers. Revitalization context learners.
Request this sampleMinority and Low-Resource Languages140 hours -
Frisian West Frisian
160 hours. Netherlands province speakers. Dutch code-switching documented.
Request this sampleMinority and Low-Resource Languages160 hours -
Faroese Iceland Comparison
90 hours. Faroese primary with Icelandic mutual intelligibility pairs.
Request this sampleMinority and Low-Resource Languages90 hours -
Nordic Reference Corpus Clean
2,400 hours. Norwegian, Swedish, Danish, Finnish, Icelandic. Studio conditions. CC-BY-SA licensing.
Request this sampleSynthetic-Safe Grounding Datasets2,400 hours -
German Reference Multi-Accent Clean
3,200 hours. Standard German with Austrian, Swiss, and regional variants. Studio conditions.
Request this sampleSynthetic-Safe Grounding Datasets3,200 hours -
European Phoneme Coverage Balanced
1,800 hours. Twelve languages. Phonetically balanced sentence sets. IPA alignment.
Request this sampleSynthetic-Safe Grounding Datasets1,800 hours -
Demographic Balanced European
4,200 hours. Age, gender, and regional quotas across ten countries. Bias evaluation documentation included.
Request this sampleSynthetic-Safe Grounding Datasets4,200 hours
No dataset matches that search. Clear it to see all 53 again.
High-value collections
High-Value Collections
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Swiss German Complete Regional
6,200 hours across Zürich, Bern, Basel, Lucerne, and St. Gallen cantons. An Alemannic German corpus scoped for commercial AI training, with documented dialect features. Includes spontaneous conversation, read speech, and command-and-control scenarios. Sub-dialect classification at municipality level. Urban/rural speaker distribution documented. Recorded 2022-2024 on smartphones and professional equipment.
Why it matters
Swiss German is mutually unintelligible with Standard German. Models trained on High German fail systematically on Swiss users. This corpus closes the gap.
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Nordic Languages Bundle
14,000 hours across Norwegian (Bokmål, Nynorsk, five dialect regions), Swedish (four dialect regions including Finland-Swedish), Danish (Copenhagen and Jutlandic), Finnish, and Icelandic. Scripted and unscripted variants. Full demographic metadata across age, gender, and regional origin.
Why it matters
No competitor offers comparable Nordic depth. Speechmatics lists these languages but doesn't publish dialect-specific coverage. This bundle covers Nordic deployment end-to-end.
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European Automotive In-Cabin
8,400 hours across 22 vehicle models from eight manufacturers. Highway (100-140 km/h), urban, and idle conditions. HVAC states documented. Driver and passenger positions. 18 languages with native-accent speakers. Infotainment commands, navigation requests, and spontaneous conversation.
Why it matters
In-cabin acoustic conditions cannot be synthesized. Augmenting studio recordings with noise overlays doesn't replicate real vehicle transfer functions. This corpus captures ground-truth in-vehicle speech.
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Clinical Dictation European
6,800 hours across German, French, Spanish, Italian, and Dutch. 35+ medical specialties. Board-certified and practicing physicians. Inpatient and outpatient contexts. GDPR Article 9 consent protocols. De-identified variants available.
Why it matters
Medical terminology causes 3-5x WER degradation versus general speech. Specialty-specific vocabulary (cardiology vs. radiology vs. pathology) requires purpose-built corpora. This dataset covers the clinical documentation use case at scale.
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British Isles Complete Accent Collection
8,200 hours covering Glaswegian, Scouse, Geordie, Belfast, Dublin, Cork, Welsh English, West Country, Yorkshire, and Birmingham. Native speakers recorded in home environments. Multi-generational samples. Spontaneous conversation and elicited speech.
Why it matters
British English isn't one accent. Models trained on RP or general British data fail on regional speakers. Customer service, healthcare, and public sector applications require regional coverage.
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European Call Center Multilingual
12,400 hours across 22 languages. Real call center recordings (consent-obtained). Customer service, technical support, complaints, and sales contexts. Emotional state annotations. PII fully redacted. 8kHz telephony and VoIP quality variants.
Why it matters
Call center audio has unique acoustic characteristics: narrow bandwidth, compression artifacts, headset coloration, crosstalk. Models trained on wideband audio degrade on telephony. This corpus matches production conditions.
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Code-Switching European Business
6,800 hours of bilingual speech across eight language pairs. English-German (Frankfurt, Berlin), English-French (Paris, Brussels), French-Arabic (Paris, Marseille), German-Turkish (Berlin, Cologne), and others. Intra-sentential and inter-sentential switching annotated.
Why it matters
Monolingual models fail on multilingual users. Code-switching is standard in European business, tech, and urban contexts. This corpus enables real-world multilingual ASR.
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Emotional Speech European Acted
3,200 hours of professional voice actor recordings. Six primary emotions at three intensity levels. German, English (UK), French, Spanish, and Italian. Valence and arousal annotations. Prosodic contour documentation.
Why it matters
TTS systems require emotional range. Sentiment analysis requires labeled emotional speech. Neutral corpora can't teach these patterns. Professional acted speech provides ground-truth emotional expression.
Delivered metadata
What Ships With Every Dataset
Audio without metadata is unusable. You can't fine-tune on speakers you can't characterize. You can't balance training sets without demographic data. You can't satisfy compliance requirements without consent documentation.
Every YPAI dataset includes structured metadata at the recording, speaker, and collection-session levels.
Recording-level metadata
- Duration (milliseconds)
- Sample rate (typically 16kHz or 48kHz)
- Bit depth
- File format
- Recording date
- Device type and model
- Microphone type
- Acoustic environment classification
- Signal-to-noise ratio estimate
- Clipping detection flag
- Silence ratio
Speaker-level metadata
- Unique speaker ID (pseudonymized)
- Age band
- Gender
- Native language
- Dialect/accent classification
- Geographic origin (country, region, city where applicable)
- Education level
- Occupation category
- Self-reported language proficiency (CEFR scale for non-native)
- Years of residence in recording location
Session-level metadata
- Collection date
- Collection method (app, studio, field recording)
- Recording environment description
- Noise classification
- Device positioning
- Elicitation type (scripted, spontaneous, command, emotional)
Consent and provenance
- Consent ID linking to master consent record
- Consent version (for updated consent forms)
- Consent scope (what the audio may be used for)
- Revocation status (propagated from master consent system)
- Collection organization
- Collection protocol reference
- Annotation lineage (who annotated what, when, using which guidelines)
EU AI Act Article 10 documentation
- Demographic distribution analysis
- Geographic representation analysis
- Known limitations and gaps
- Data quality measures
- Bias evaluation methodology
- Training data sheet in standardized format
Industry solutions
Browse by Industry
Each vertical links straight into the catalogue, filtered to the datasets that serve it. Where a full solution page exists, it is linked too.
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Automotive Voice AI
In-cabin recordings. Highway, urban, and idle conditions. 70+ language and dialect combinations. Wake word and command datasets. Navigation, media, climate, and communication scenarios.
- 70+ language/dialect combinations
- 22 vehicle models
- 18 languages with native speakers
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Healthcare and Clinical Speech
Physician dictation across 35+ specialties. Ambient clinical conversation. Medical terminology in European languages. De-identified variants. GDPR Article 9 consent.
- 35+ medical specialties
- 6,800+ hours available
- De-identified variants
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Finance and Call Center
Trading floor recordings. Call center customer service. Financial terminology. PCI-DSS pre-scrubbed variants. Emotional state annotations.
- 12,400 hours call center
- 22 languages
- Emotional annotations
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Industrial and Manufacturing
Factory floor speech. Warehouse logistics. Maritime operations. Offshore platforms. PPE-muffled speech. Industrial noise environments.
- Real operational environments
- SNR metadata
- Safety equipment contexts
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Gaming and Entertainment
Emotional speech for TTS. Character archetypes. Voice actor recordings. Prosodic variation. Whispered and projected speech.
- 3,200 hours emotional speech
- Character archetypes
- European voice actors
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Broadcasting and Media
Multi-speaker panel discussions. Sports commentary. News broadcast. Proper noun emphasis. Live captioning training data.
- Multi-speaker scenarios
- Sports and news
- European broadcasting