Datasets:
File size: 1,442 Bytes
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task_categories:
- automatic-speech-recognition
language:
- en
tags:
- microbiology
- science
- synthetic
- kokoro
- speech
---
# Kokoro Science and Microbiology STT Synthetic Dataset
Synthetic English scientific speech generated with `hexgrad/Kokoro-82M`.
## Current contents
- **8,995 utterances**
- **20.000 measured hours**
- 16 kHz mono embedded FLAC audio
- `text`: desired ASR transcript
- `tts_text`: pronunciation-friendly text supplied to Kokoro
## Corpus generations
- `v1_10h_original`: original approximately 10-hour release
- `v2_20h_expansion`: second tranche bringing the dataset to 20 measured hours
## v2 expansion focus
- mM vs mL and µM vs µL unit/context contrasts
- dilution notation and CFU enumeration
- microbiology organisms and selective media
- antimicrobial susceptibility and MIC language
- molecular biology and qPCR terminology
- laboratory QC and reporting language
## Categories
- `microbiology`: 3,795
- `units_concentrations`: 1,032
- `quantitative_science`: 695
- `enumeration`: 606
- `laboratory_methods`: 590
- `molecular_biology`: 527
- `antimicrobial_susceptibility`: 455
- `chemistry`: 382
- `quality_science`: 254
- `biochemistry_general_science`: 197
- `unit_contrasts`: 167
- `general_science`: 136
- `scientific_language`: 84
- `laboratory_qc`: 75
Synthetic speech is useful for domain adaptation, but real-human scientific speech should remain an independent validation target.
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