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Commercial
Slovenian Speech Recognition Dataset
Slovenian speech dataset contains over 10 hours of telephone-recorded dialogues from 20+ native speakers, delivered in MP3 and WAV formats with low background noise and minute-long segments. The dataset includes structured annotations (ID, language, format, duration), making it well-suited for Slovenian speech recognition, spoken language processing, and training language models built on high-quality continuous and spontaneous speech data.
-
- Hours
- 10+
-
- Speakers
- 20+
- NLP
- LLM
- Machine Learning
- Audio Processing
- ASR
- Voice Recognition
- NLP
- LLM
- Machine Learning
- Audio Processing
- ASR
- Voice Recognition
Slovenian speech dataset contains over 10 hours of telephone-recorded dialogues from 20+ native speakers, delivered in MP3 and WAV formats with low background noise and minute-long segments. The dataset includes structured annotations (ID, language, format, duration), making it well-suited for Slovenian speech recognition, spoken language processing, and training language models built on high-quality continuous and spontaneous speech data.
- NLP
- LLM
- Machine Learning
- Audio Processing
- ASR
- Voice Recognition
-
- Hours
- 10+
-
- Speakers
- 20+
Dataset Info
| Characteristic | Data |
| Description | Audio of telephone dialogues in Slovenian for training NLP models in real-world conversational scenarios |
| Data types | Audio |
| Tasks | Speech recognition, NLP |
| Country | Slovenia (SVN) |
| Hours of telephone dialogue | 10+ |
| Number of speakers | 20+ |
| Labeling | Annotation (ID, Language, Format, Minutes) |
| Recording device | Telephone |
Technical
Characteristics
| Characteristic | Data |
| Audio Format | MP3, WAV |
| Recording condition | Low background noise |
| Duration | Mean = 1 min |
Dataset Use Cases
FAQs
Can I request a sample of the dataset before purchasing?
Yes. You can request a free sample of the Slovenian audio dataset to evaluate audio clarity, annotation structure, and compatibility with your recognition systems. This allows you to test speech quality before purchasing the full dataset.
How was the speech data collected?
The speech material was collected using telephone devices via controlled crowdsourcing. All recordings were captured under low background noise conditions to ensure consistent speech quality suitable for training language models and continuous speech systems.
How are Unidata datasets licensed?
Unidata datasets follow a dual-licensing model. Free samples are available for testing, while full Slovenian speech datasets can be accessed exclusively through purchase.
Do Unidata datasets comply with GDPR and data privacy laws?
Yes. All datasets are curated in compliance with GDPR and applicable privacy regulations. Each recording is collected from lawful and ethically approved sources, ensuring responsible handling of speech data.
How does Unidata store its datasets?
Datasets are securely stored on AWS cloud infrastructure following ISO 27001 and ISO 27701 standards. This guarantees a secure, privacy-focused environment for managing and distributing Slovenian language datasets.
How long does it take to receive the dataset?
After you submit a request, Unidata will contact you to confirm requirements and complete documentation. Once the agreement is signed and payment is processed, the Slovenian speech dataset is delivered within 3–10 days.
Is this real-world data or synthetic data?
This dataset consists exclusively of real-world speech recordings. All audio was captured from native Slovenian speakers during actual telephone conversations, providing authentic spontaneous speech for recognition systems.
Why are real telephone conversations useful for speech recognition training?
Telephone conversations represent realistic audio conditions similar to those encountered in everyday voice applications. Training with conversational recordings helps models improve their ability to handle natural speech, different speaking styles, and practical communication scenarios.
Still have questions about using Unidata datasets?
Read our user-guides
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