---
license: cc-by-4.0
language:
- en
task_categories:
- automatic-speech-recognition
- text-classification
- token-classification
tags:
- voice-notes
- task-extraction
- disfluency
- long-form
- real-speech
pretty_name: Annotated Voice Notes
size_categories:
- n<1K
---

# Annotated Voice Notes

A small, hand-picked set of real voice notes. It is kept small on purpose. Each
note has its audio, a raw AssemblyAI transcript, and a written annotation that
explains why it was included and what it is good for.

This is not a bulk corpus. Every recording was chosen because it shows something
specific, such as tasks buried in rambling speech, heavy disfluency, or a long
take. The annotation says what that is.

## Fields

| Field | Description |
|---|---|
| `audio` | The recording, in its original format (MP3) |
| `id` | Stable sample id (`avn-NNNN`) |
| `title` | Short description |
| `recorded_at` | ISO 8601 with offset |
| `recording_context` | How and where it was recorded |
| `purposes` | Machine-readable list of the uses it was included for |
| `purpose_explanation` | Why it is in the dataset |
| `notes` | Observations on structure, disfluencies and likely ASR errors |
| `tags` | Topic tags |
| `duration_s`, `word_count` | From the ASR output |
| `transcript_raw` | AssemblyAI output, uncorrected, with disfluencies kept |
| `asr_engine`, `asr_settings` | Model and settings that produced the transcript |

Transcripts are **raw**. They are not corrected against the audio, so known and
suspected ASR errors are listed in `notes` and left in the text.

## Samples

| id | Title | Length | Purposes |
|---|---|---|---|
| avn-0001 | Apartment remaining-fixes walkthrough | 22:19 | task extraction, disfluency, long-form |

## Purposes vocabulary

- `task_extraction`: tasks expressed loosely, not as a clean list
- `disfluency`: fillers, false starts, self-corrections, restarts
- `long_form_task_recording`: several minutes of continuous task-bearing speech