Dataset-Index / README.md
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Index 2026-10-27
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metadata
license: cc-by-4.0
pretty_name: Hebrish Dataset Index
tags:
  - hebrish
  - asr
  - code-switching
  - index
configs:
  - config_name: default
    data_files: index.json

Hebrish Dataset Index

An index of every public dataset in the Hebrish project and which models were trained on what. Machine-readable: index.json. Generated by scripts/build_dataset_index.py in the training repo; last built 2026-10-27.

  • 56 datasets (39 published, the rest registered tasks whose subset appears once takes are recorded).
  • 24 models.

How training data works here

Every take is recorded once, into the master dataset danielrosehill/Read-Aloud-Voice-Sentences. The per-topic datasets (code-switching, tech, acronyms, whispered, ...) are views of it, published for browsing and reuse. A speech model trains on the master at a pinned revision, through a blend: a rule for which rows it takes. in_blends on each dataset says which blends include its rows.

Blend Used by Rule
cs Jachnun (and the first Shakshuka runs) code-switching rows, Daniel's own English (about 2/3 of the English share), LibriSpeech-PC replay, plus the task tags ['currency']
all Sabich, Shakshuka v1.0+ and the Sabich variants every row of the master dataset at the run's revision, including every task tag present then, except ['name-cipher', 'paragraphs', 'weird-voices']; replay about 10%. From Sabich v2.1, priority-word takes (Hebrish/ASR-Error-List) appear 3 times.

Models

Model Task Data (blend @ revision, or dataset) Source
Jachnun PoC-1 speech-recognition cs @ b31aeabb confirmed
Jachnun PoC-2 speech-recognition cs @ 3bdaa2a5 confirmed
Jachnun PoC-3 speech-recognition cs @ b4731062 confirmed
Jachnun PoC-4 speech-recognition cs @ 4fcca820 confirmed
Jachnun PoC-5 speech-recognition cs @ fcf5aec1 confirmed
Shakshuka PoC-1 speech-recognition cs @ fcf5aec1 confirmed
Jachnun v1.0 speech-recognition cs @ 550bfcaa confirmed
Shakshuka PoC-2 speech-recognition cs @ 550bfcaa confirmed
Sabich v1.0 speech-recognition all @ f956dbb1 confirmed
Shakshuka v1.0 speech-recognition all @ e918e381 confirmed
Sabich-Parakeet-110M v1.0 speech-recognition all @ e918e381 confirmed
Sabich-Qwen3-ASR-1.7B PoC speech-recognition all @ e918e381 confirmed
Sabich-Canary-Qwen-2.5B v1.0 speech-recognition all @ cf84f7e4 confirmed
Sabich-asr4all-M v1.0 speech-recognition all @ cf84f7e4 confirmed
Sabich-asr4all-S v1.0 speech-recognition all @ cf84f7e4 confirmed
Sabich v2.0 speech-recognition all @ 110d144a confirmed
Shakshuka v2.0 speech-recognition all @ 110d144a confirmed
Sabich v2.1 speech-recognition all @ 2cec2ebc confirmed
Meorav v2.1 text-to-speech Hebrish/Hebrish-TTS-Voice-Recordings confirmed
Meorav v2.0 text-to-speech Hebrish/Hebrish-TTS-Voice-Recordings confirmed
Meorav PoC-1 text-to-speech Hebrish/Hebrish-TTS-Voice-Recordings confirmed
Whisper-Hebrish v2 speech-recognition danielrosehill/Read-Aloud-Voice-Sentences confirmed
Whisper-Hebrish small, ACFT speech-recognition danielrosehill/Read-Aloud-Voice-Sentences confirmed
Token classifier v1 token-classification Hebrish/hebrew-latin-code-switching confirmed

Every recording is one speaker's voice (Daniel Rosehill). He sometimes changes his speaking speed on purpose and sometimes says a word the way people commonly mispronounce it; the transcript is always the sentence as written.