Training-Sources / README.md
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---
license: cc-by-4.0
pretty_name: Fritter Training Sources
tags: [index, speech, asr, tts, fritter]
configs:
- config_name: sources
data_files: sources.jsonl
default: true
- config_name: releases
data_files: releases.jsonl
---
<img src="fritter-icon-256.png" width="96" alt="Fritter icon">
# Fritter Training Sources
An index of the datasets the [Fritter](https://huggingface.co/Fritter-ASR) speech models are trained on. It holds
no audio; each row links to the dataset itself.
- **`sources`**: every dataset involved and how Fritter uses it (`fritter_asr`: used, partial, not used, indirect).
All training audio comes from one primary dataset, [`danielrosehill/Read-Aloud-Voice-Sentences`](https://huggingface.co/datasets/danielrosehill/Read-Aloud-Voice-Sentences);
the topic datasets listed with it are subsets of it, there for browsing by topic.
- **`releases`**: each published model version, its training run and the exact revision of the primary dataset it
was trained on.
## How Fritter (ASR) is trained
23 of 29 topic subsets are used. The training mix is the speaker's English takes that are not
code-switching, with these tags left out: `israeli-places`, `israeli-streets`, `israeli-tv`, `israeli-names`, `tanach`, `biblical-verses`, `talmud`, `rabbinic-works`, `rabbis`, `halacha`, `name-cipher`, `paragraphs`, `weird-voices`. About 10% of each mix is LibriSpeech replay, so general
English does not degrade. From v1.2 each release continues from the previous one on the new takes plus a
sample of earlier ones.
| Dataset | Fritter ASR | Takes | Hours |
|---|---|---|---|
| [`danielrosehill/Read-Aloud-Voice-Sentences`](https://huggingface.co/datasets/danielrosehill/Read-Aloud-Voice-Sentences) | used | 28,570 | 43.75 |
| [`openslr/librispeech_asr`](https://huggingface.co/datasets/openslr/librispeech_asr) | used | | |
| [`Hebrish/Acronym-Sentences`](https://huggingface.co/datasets/Hebrish/Acronym-Sentences) | used | 99 | 0.12 |
| [`Hebrish/Background-Speech`](https://huggingface.co/datasets/Hebrish/Background-Speech) | used | 12 | 0.02 |
| [`Hebrish/Brand-Name-Sentences`](https://huggingface.co/datasets/Hebrish/Brand-Name-Sentences) | used | 378 | 0.70 |
| [`Hebrish/Currency-Sentences`](https://huggingface.co/datasets/Hebrish/Currency-Sentences) | used | 160 | 0.24 |
| [`Hebrish/Disfluent-Read-Sentences`](https://huggingface.co/datasets/Hebrish/Disfluent-Read-Sentences) | used | 55 | 0.22 |
| [`Hebrish/Expanded-Acronym-Sentences`](https://huggingface.co/datasets/Hebrish/Expanded-Acronym-Sentences) | used | 50 | 0.07 |
| [`Hebrish/Hard-ASR-Sentences`](https://huggingface.co/datasets/Hebrish/Hard-ASR-Sentences) | used | 68 | 0.07 |
| [`Hebrish/Irish-English-Sentences`](https://huggingface.co/datasets/Hebrish/Irish-English-Sentences) | used | 258 | 0.38 |
| [`Hebrish/Noisy-Condition-Sentences`](https://huggingface.co/datasets/Hebrish/Noisy-Condition-Sentences) | used | 7,202 | 10.10 |
| [`Hebrish/Pronunciation-Variants`](https://huggingface.co/datasets/Hebrish/Pronunciation-Variants) | used | 170 | 0.23 |
| [`Hebrish/Repeated-Word-Sentences`](https://huggingface.co/datasets/Hebrish/Repeated-Word-Sentences) | used | 19 | 0.06 |
| [`Hebrish/Self-Correction-Sentences`](https://huggingface.co/datasets/Hebrish/Self-Correction-Sentences) | used | 27 | 0.04 |
| [`Hebrish/Singing-Sentences`](https://huggingface.co/datasets/Hebrish/Singing-Sentences) | used | 16 | 0.02 |
| [`Hebrish/Spoken-Aside-Sentences`](https://huggingface.co/datasets/Hebrish/Spoken-Aside-Sentences) | used | 5 | 0.01 |
| [`Hebrish/Whispered-Sentences`](https://huggingface.co/datasets/Hebrish/Whispered-Sentences) | used | 312 | 0.49 |
| [`danielrosehill/AI-Interactions-Sentences`](https://huggingface.co/datasets/danielrosehill/AI-Interactions-Sentences) | used | 583 | 0.74 |
| [`danielrosehill/General-English-Sentences`](https://huggingface.co/datasets/danielrosehill/General-English-Sentences) | used | 1,910 | 2.89 |
| [`danielrosehill/Homophone-Context-Sentences`](https://huggingface.co/datasets/danielrosehill/Homophone-Context-Sentences) | used | 158 | 0.25 |
| [`danielrosehill/Linux-Admin-Sentences`](https://huggingface.co/datasets/danielrosehill/Linux-Admin-Sentences) | used | 530 | 0.86 |
| [`danielrosehill/Personal-Vocabulary-Sentences`](https://huggingface.co/datasets/danielrosehill/Personal-Vocabulary-Sentences) | used | 191 | 0.25 |
| [`danielrosehill/Smart-Home-Sentences`](https://huggingface.co/datasets/danielrosehill/Smart-Home-Sentences) | used | 185 | 0.29 |
| [`danielrosehill/Tech-Sentences`](https://huggingface.co/datasets/danielrosehill/Tech-Sentences) | used | 7,495 | 11.63 |
| [`danielrosehill/Voice-Command-Sentences`](https://huggingface.co/datasets/danielrosehill/Voice-Command-Sentences) | used | 1,266 | 0.69 |
| [`Hebrish/Israeli-Name-Sentences`](https://huggingface.co/datasets/Hebrish/Israeli-Name-Sentences) | not used | 117 | 0.17 |
| [`Hebrish/Jewish-Religious-Terminology-Sentences`](https://huggingface.co/datasets/Hebrish/Jewish-Religious-Terminology-Sentences) | not used | 2,146 | 3.86 |
| [`Hebrish/Judaica-Sentences`](https://huggingface.co/datasets/Hebrish/Judaica-Sentences) | not used | 772 | 1.46 |
| [`Hebrish/Weird-Voice-Sentences`](https://huggingface.co/datasets/Hebrish/Weird-Voice-Sentences) | not used | 6 | 0.01 |
| [`Hebrish/Yiddish-Sentences`](https://huggingface.co/datasets/Hebrish/Yiddish-Sentences) | partial | 348 | 0.55 |
| [`danielrosehill/English-Hebrew-Codeswitching-Sentences`](https://huggingface.co/datasets/danielrosehill/English-Hebrew-Codeswitching-Sentences) | not used | 8,233 | 14.05 |
Sizes measured 2026-11-08.
## Releases
| Model | Version | Run | Primary dataset revision |
|---|---|---|---|
| Fritter (ASR) | v1.0 | `r11-general` | `520e7506e379` |
| Fritter (ASR) | v1.1 | `r25-general` | `5ce184058554` |
| Fritter (ASR) | v1.2 | `r30-general` | `306a7450433d` |
| Fritter (ASR) | v1.3 | `r35-general` | `39f21d714103` |
| Fritter TTS | v1 | `fritter-tts-v1` | not recorded |
Generated by `scripts/fritter_training_sources.py` in the training repository. Regenerated after each release.