Arabic Speech Recognition Dataset
Arabic speech dataset provides over 10 hours of telephone-quality dialogues recorded by 20+ native Arabic speakers from the UAE, offering clean, high-quality audio data suitable for training speech recognition systems, dialogue models, and Arabic language processing tools. The dataset contains annotated audio recordings (ID, language, format, duration) in M4A, MP3, WAV, and AAC, captured with low background noise.
-
- Hours
- 10+
-
- Speakers
- 20+
- NLP
- LLM
- Machine Learning
- Audio Processing
- ASR
- Voice Recognition
Arabic speech dataset provides over 10 hours of telephone-quality dialogues recorded by 20+ native Arabic speakers from the UAE, offering clean, high-quality audio data suitable for training speech recognition systems, dialogue models, and Arabic language processing tools. The dataset contains annotated audio recordings (ID, language, format, duration) in M4A, MP3, WAV, and AAC, captured with low background noise.
- NLP
- LLM
- Machine Learning
- Audio Processing
- ASR
- Voice Recognition
-
- Hours
- 10+
-
- Speakers
- 20+
Dataset Info
| Characteristic | Data |
| Description | Audio of telephone dialogues in Arabic for training NLP models in real-world conversational scenarios |
| Data types | Audio |
| Tasks | Speech recognition, NLP |
| Country | United Arab Emirates (ARE) |
| 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, WAV, AAC |
| Recording condition | Low background noise |
| Duration | Mean = 11 min |
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