Datasets:

Hebrish
/

Hebrish-Validation

license: cc-by-4.0
task_categories:
  - automatic-speech-recognition
language:
  - en
  - he
tags:
  - audio
  - code-switching
  - hebrish
  - validation
pretty_name: Hebrish Validation
configs:
  - config_name: default
    data_files:
      - split: validation
        path: data/validation-*.parquet
  - config_name: long
    data_files:
      - split: validation
        path: long/validation-*.parquet

Hebrish Validation

A validation benchmark for the Hebrish English-Hebrew code-switching speech recognition models (Sabich and the other lines). Each row is one continuous read of a fixed script of about one minute, with the script as the exact reference transcript. Takes are recorded in the Hebrish capture app; the device each one was recorded on is in its device column.

It complements the public benchmark test set v2, Hebrish/English-Hebrew-Codeswitching-ASR-Benchmark (short sentences); it does not replace it. Here the model hears long-form speech the way it is dictated: whole paragraphs, ordinary devices and rooms.

Never used for training. These recordings are excluded from the Hebrish training corpus and from every dataset derived from it. The script sentences are not in any sentence bank used for recording training data.

Scripts

Three categories, written in English with Hebrew words in the Hebrish romanization:

Category	What it tests
`codeswitch`	everyday English with romanized Hebrew terms (kupat cholim, ishur, tzaharon)
`tech`	English technical vocabulary (Kubernetes, PostgreSQL, TLS)
`mixed`	both in one script

Transcripts keep to plain ASCII letters, digits and . , ? ! ' : - / % $.

Versioning

Set v1.0 (2026-11-02). Scripts change only with a new set version. script_revision (the first 12 hex digits of the SHA-256 of the reference text) pins the exact text each recording was read from.

Speakers

So far one speaker, Daniel Rosehill (male, Irish-born, living in Israel). Recordings by other speakers are very welcome: contact the Hebrish project through https://hebrish.app/feedback.

Columns

Column	What it is
`audio`	the recording, mono FLAC (48 kHz / 24-bit from the capture app; see `sample_rate`, `bit_depth`)
`text`	the reference transcript (the script)
`script_id`	the script, e.g. `cs-01`, `tech-02`, `mixed-03`
`category`	`codeswitch`, `tech` or `mixed`
`set_version`	the script set, e.g. `v1.0`
`script_revision`	SHA-256 prefix of `text`
`duration_s`, `sample_rate`, `bit_depth`	audio format
`device`	the device and browser the take was recorded on
`microphone`	the input used, where the phone reports it
`speaker`	who read it
`created_at`	when it was recorded (UTC)
`take_id` (= `id`)	the recording's id. A script can have several takes; an evaluator should use the latest per script and speaker.

Index without the audio: meta/validation.jsonl (each row's shard and the byte range of its FLAC in it).

from datasets import load_dataset
ds = load_dataset("Hebrish/Hebrish-Validation", split="validation")

Long-form config (`long`)

The same takes joined into longer files, so a model is also scored on minutes of continuous dictation. One row per group and speaker: codeswitch, tech and mixed (that category's four scripts, about 3 to 4 minutes each) and all (all twelve, about 10 minutes). Each uses the latest take of every script, in script order, joined with 1.0 s of silence; text is the scripts' texts in the same order, separated by a blank line. Columns: audio, text, group, set_version, script_ids, take_ids and script_revisions (the takes used, in order), gap_s, duration_s, sample_rate, bit_depth, speaker, built_at. Rebuilt when takes change.

long = load_dataset("Hebrish/Hebrish-Validation", "long", split="validation")

Licence

CC BY 4.0, as the rest of the Hebrish datasets.