---
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](https://huggingface.co/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](https://huggingface.co/datasets/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).

```python
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.

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

## Licence

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