Datasets:

danielrosehill
/

Proofed-ASR-Cleanup-Training-Data

license: cc-by-4.0
language:
  - en
task_categories:
  - automatic-speech-recognition
tags:
  - asr
  - disfluency
  - inverse-text-normalization
  - post-processing
  - parakeet
  - proofed
pretty_name: Proofed ASR Cleanup Training Data
size_categories:
  - n<1K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train/**
      - split: test
        path: data/test/**

Proofed ASR Cleanup Training Data

Audio paired with clean, proofed target text for training an ASR model to do its own post-processing: no fillers, repeats or false starts, numbers and money as digits, self-corrections applied, asides to other people left out, paragraph breaks, whispered speech. Built for Proofed, a fine-tune of NVIDIA Parakeet TDT 0.6B v2 that writes clean text in one pass with no LLM afterwards.

Status (2026-10-24): first snapshot, small. About 75 minutes, single speaker. The per-task takes are still being recorded (targets: recording-targets.md); this repo is rebuilt as they land. Task definitions: taxonomy.

Task	Train takes	Train min	Test takes
replay (plain English, against forgetting)	344	34.3	19
currency	116	11.1	0
disfluency (filled pauses)	51	12.4	4
numerics	37	2.7	4
repetitions	18	3.6	1
false-starts	3	0.3	0
paragraphs	3	0.7	0
whispered	3	0.4	1
asides	2	0.3	0

Self-corrections have no takes yet.

Columns

audio (from file_name): 16 kHz mono WAV, recorded on an Android phone.
text: the clean training target (what Proofed should write).
verbatim_text / spoken_text: what was actually said, where it differs (disfluent, repeated, self-corrected takes); aside_text, aside_position: the aside that must be dropped; paragraph_text: the target with paragraph breaks.
task, tasks, categories: task labels (ids as in the taxonomy).
duration_s, device, microphone, environment, sample_rate, recorded_at, mode, prompt_id, prompt_source, prompt_kind.
source_dataset, source_revision: provenance of each row.

Sources

Built from danielrosehill/Read-Aloud-Voice-Sentences @ c544f891 and the task subsets Hebrish/Disfluent-Read-Sentences, Hebrish/Repeated-Word-Sentences, Hebrish/Currency-Sentences, Hebrish/Spoken-Aside-Sentences, Hebrish/Self-Correction-Sentences (revisions in build_summary.json). Train/test splits follow the source datasets. Code-switching, tech and other domain-vocabulary takes are excluded by design. Read, acted speech: disfluencies were performed from prompts, not spontaneous.

Licence: CC-BY-4.0. Non-commercial research project; public corpora used later in training (DisfluencySpeech, AMI, ICSI, LibriSpeech-PC) are not redistributed here.

Proofed ASR Cleanup Training Data

Contents

Columns

Sources