Datasets:
File size: 2,914 Bytes
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license: cc-by-4.0
language:
- en
task_categories:
- automatic-speech-recognition
pretty_name: Linux Admin Sentences
tags:
- speech
- asr
- fine-tuning
- single-speaker
- tech-vocabulary
- linux
- sysadmin
size_categories:
- n<1K
configs:
- config_name: default
data_files:
- split: train
path: data/train/**
- split: test
path: data/test/**
---
# Linux Admin Sentences
Dictation-style English sentences about Linux desktop and server administration (KDE Plasma, GNOME, systemd, storage, networking, homelab), read aloud by one speaker. The focus is names that a speech model writes as an ordinary English word: Konsole (console), Okular (ocular), Thunar (thunder), LUKS (looks), Btrfs, GRUB. Sentences to read: [Linux-Admin-Sentence-Bank](https://huggingface.co/datasets/danielrosehill/Linux-Admin-Sentence-Bank).
**Website: [hebrish.app](https://hebrish.app)**: get the Hebrish keyboard for Android and the desktop apps, see the results, and find every model, dataset and demo in one place.
**This is a subset of [`danielrosehill/Read-Aloud-Voice-Sentences`](https://huggingface.co/datasets/danielrosehill/Read-Aloud-Voice-Sentences)**, the full, undifferentiated
dataset. It contains every phone recording there whose `categories` include `linux` and not `code_switch`. Rows are copied
unchanged, with the same ids, columns and train/test split, by `scripts/sync_subsets.py` in the
project repository. Do not edit this dataset directly: fix the row in the main dataset and re-sync.
The subset grows as new takes are published.
**Speaker:** Daniel Rosehill, the dataset's author, who was born in Ireland and speaks English with an **Irish accent**, and who lives in Jerusalem. Every recording is his voice.
All audio was recorded on a **OnePlus Nord 3 5G** phone using its **internal microphone**, with browser echo cancellation, noise suppression and auto gain turned off.
## Layout
```
data/train/audio/<id>.wav 16 kHz mono 16-bit PCM
data/train/metadata.jsonl
data/test/... held-out set, never trained on
```
The `test` split is **term-disjoint**: a held-out term never appears in `train`.
`load_dataset("danielrosehill/Linux-Admin-Sentences")` works directly.
## Columns
The columns are the same as in the main dataset: `text` (ground truth, punctuated and cased like
Parakeet v2 output), `text_he` (the same transcript with its Hebrew terms in Hebrew script, for
Hebrew-capable models), `categories`, `target_terms`, `prompt_source`, `prompt_origin` (manual / dataset / generated), `edited`, `duration_s`,
`environment`, `conditions`, `device`, `speaker`, `speaker_gender` and `recorded_at`. The main dataset's card describes them.
## Licence
CC-BY-4.0, with sentence-text attribution per `prompt_source` as described in the
[main dataset's licence section](https://huggingface.co/datasets/danielrosehill/Read-Aloud-Voice-Sentences#licence-and-attribution).
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