British English Speech Recognition Dataset
The dataset consists of 200 hours of high-quality telephone dialogues from 310 native speakers in the UK, with detailed annotations (transcriptions, timestamps, speaker ID, gender, and background noise) to support speech recognition systems, NLP tasks, and machine learning models requiring diverse British English audio datasets.
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-
- Speakers
- 310
-
- Hours
- 200
-
- Sentence Accuracy Rate
- 95%
- NLP
- LLM
- Machine Learning
- Audio Processing
- ASR
- Voice Recognition
-
- Speakers
- 310
-
- Hours
- 200
-
- Sentence Accuracy Rate
- 95%
Dataset Info
| Characteristic | Data |
| Description | Audio of telephone dialogues in English for training NLP models in real-world conversational scenarios. |
| Data types | Audio |
| Tasks | Speech recognition, NLP |
| Country | The United Kingdom (GBK) |
| Hours of telephone dialogue | 200 |
| Number of speakers | 310 |
| Labeling | Annotation (transcription text, timestamp, speaker ID, gender, noise) |
| Gender | Male (42%), Female (58%) |
| Recording device | Android smartphone, iPhone |
Statistics
-
- Distribution by gender
Technical
Characteristics
| Characteristic | Data |
| Audio Format | Uncompressed WAV |
| Sampling Rate | 16kHz |
| Bit Depth | 16bit |
| Number of Channels | Mono |
| Recording condition | Low background noise (indoor) |
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