“We were very happy with the quality of the data that we purchased. It will assist our efforts to improve our product. The team at Unidata was very responsive to our needs, and provided the data format needed to complete our tasks. We are happy to state that Unidata delivers a high quality product in an effective and efficient manner.”
Commercial
Vietnamese Speech Recognition Dataset
Vietnamese speech dataset features over 10 hours of telephone-quality audio recordings from native Vietnamese speakers, providing a diverse speech corpus for recognition tasks and training data for NLP models. This Vietnamese audio dataset contains real conversational dialogues with detailed annotations, making it well-suited for machine learning, multi-dialect processing, and benchmarking speech-driven AI systems.
-
- Hours
- 10+
-
- Speakers
- 20+
- NLP
- LLM
- Machine Learning
- Audio Processing
- ASR
- Voice Recognition
- NLP
- LLM
- Machine Learning
- Audio Processing
- ASR
- Voice Recognition
Vietnamese speech dataset features over 10 hours of telephone-quality audio recordings from native Vietnamese speakers, providing a diverse speech corpus for recognition tasks and training data for NLP models. This Vietnamese audio dataset contains real conversational dialogues with detailed annotations, making it well-suited for machine learning, multi-dialect processing, and benchmarking speech-driven AI systems.
- NLP
- LLM
- Machine Learning
- Audio Processing
- ASR
- Voice Recognition
-
- Hours
- 10+
-
- Speakers
- 20+
Dataset Info
| Characteristic | Data |
| Description | Audio of telephone dialogues in Vietnamese for training NLP models in real-world conversational scenarios |
| Data types | Audio |
| Tasks | Speech recognition, NLP |
| Country | Vietnam (VNM) |
| Hours of telephone dialogue | 10+ |
| Number of speakers | 20+ |
| Labeling | Annotation (ID, Language, Format, Minutes) |
| Recording device | Telephone |
Technical
Characteristics
| Characteristic | Data |
| Audio Format | M4A, MP3 |
| Recording condition | Low background noise |
| Duration | Mean = 11 min |
Dataset Use Cases
FAQs
Can I request a sample before purchasing the dataset?
Yes. Unidata provides free samples so you can evaluate the audio data, annotation quality, and relevance to your recognition tasks before completing your purchase. This helps ensure compatibility with your models and training pipelines.
How was the data collected?
The dataset was collected via vetted crowdsourcing platforms, capturing natural telephone conversations from native Vietnamese speakers. Contributors followed standardized scripts and guidelines to preserve clarity and reduce background noise.
How are Unidata datasets licensed?
Unidata follows a dual-licensing model: free samples are available for testing, while full datasets are provided exclusively through paid licensing. This ensures proper usage rights and supports long-term dataset maintenance.
Do Unidata datasets comply with GDPR and privacy regulations?
Yes. All Unidata datasets adhere to GDPR and global data protection standards. Every audio sample is sourced through legally permissible collection methods, protecting participants’ personal rights.
How are Unidata datasets stored?
All datasets are securely stored on AWS cloud infrastructure with compliance to ISO 27001 and ISO 27701. This guarantees safe handling of speech data, maximum availability, and strong privacy controls.
How long does it take to receive the dataset?
After submitting your request, our team will verify details and prepare the required documents. Following payment and agreement, delivery typically occurs within 3–10 days.
Is this real-world data or synthetic data?
This dataset contains real-world audio recordings from native Vietnamese speakers. No synthetic or generated speech is included, making it ideal for training recognition systems designed for authentic human interactions.
Why is diverse Vietnamese speech valuable for natural language processing models?
Vietnamese has unique pronunciation patterns and regional language variations that require representative training data. Using authentic speech examples helps NLP and speech recognition models improve accuracy and better understand real human communication.
Still have questions about using Unidata datasets?
Read our user-guides
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