README.md

---
size_categories: n<1K
tags:
- rlfh
- argilla
- human-feedback
---

# Dataset Card for inspect_asr_eval_results







This dataset has been created with [Argilla](https://github.com/argilla-io/argilla). As shown in the sections below, this dataset can be loaded into your Argilla server as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets).


## Using this dataset with Argilla

To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:

```python
import argilla as rg

ds = rg.Dataset.from_hub("michaljunczyk/inspect_asr_eval_results")
```

This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation.

## Using this dataset with `datasets`

To load the records of this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code:

```python
from datasets import load_dataset

ds = load_dataset("michaljunczyk/inspect_asr_eval_results")
```

This will only load the records of the dataset, but not the Argilla settings.

## Dataset Structure

This dataset repo contains:

* Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `rg.Dataset.from_hub` and can be loaded independently using the `datasets` library via `load_dataset`.
* The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla.
* A dataset configuration folder conforming to the Argilla dataset format in `.argilla`.

The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**.

### Fields

The **fields** are the features or text of a dataset's records. For example, the 'text' column of a text classification dataset of the 'prompt' column of an instruction following dataset.

| Field Name | Title | Type | Required | Markdown |
| ---------- | ----- | ---- | -------- | -------- |
| audio | Audio file | text | True | True |
| hyp | ASR output | text | True | False |
| ref | Reference transcription | text | True | False |


### Questions

The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking.

| Question Name | Title | Type | Required | Description | Values/Labels |
| ------------- | ----- | ---- | -------- | ----------- | ------------- |
| error_types | Mark all ASR errors present in the hypothesis or select OK - no errors. | multi_label_selection | True | Select all that apply. | ['none', 'spacing', 'punctuation', 'numerical', 'removal', 'addition', 'replacement', 'spelling', 'syntax', 'foreign_language', 'empty', 'hallucination'] |
| asr_error | If applicable, mark error spans in ASR hypothesis. | span | False | Mark and classify ASR errors. | N/A |
| ref_issue | If applicable, mark issues in reference. | label_selection | False | N/A | ['minor', 'major', 'critical'] |
| audio_issue | If applicable, mark issues in audio. | label_selection | False | N/A | ['invalid', 'hard_noise', 'hard_interlocutor'] |


<!-- check length of metadata properties -->





### Data Instances

An example of a dataset instance in Argilla looks as follows:

```json
{
    "_server_id": "f1cb2f9c-4428-48f7-97e2-3c7359c426a8",
    "fields": {
        "audio": "\n\u003caudio controls\u003e\n    \u003csource src=\"https://huggingface.co./datasets/michaljunczyk/bigos-eval-results-secret/resolve/main/inspection_input/audio/amu-cai/pl-asr-bigos-v2-secret/pwr-viu-unk/pwr-viu-unk-test-0003-00283.mp3\" type=\"audio/mpeg\"\u003e\n\u003c/audio\u003e\n",
        "hyp": "Hyphotesis",
        "ref": "Reference transcription wav"
    },
    "id": "dce1711c-1d36-4d2a-86ac-afaf85aacb06",
    "metadata": {
        "subset": "pwr-viu-unk-3"
    },
    "responses": {
        "asr_error": [
            {
                "user_id": "bee532bf-10c0-4a3f-9386-3b5c3522197a",
                "value": []
            }
        ],
        "error_types": [
            {
                "user_id": "bee532bf-10c0-4a3f-9386-3b5c3522197a",
                "value": [
                    "none"
                ]
            }
        ]
    },
    "status": "completed",
    "suggestions": {},
    "vectors": {}
}
```

While the same record in HuggingFace `datasets` looks as follows:

```json
{
    "_server_id": "f1cb2f9c-4428-48f7-97e2-3c7359c426a8",
    "asr_error.responses": [
        []
    ],
    "asr_error.responses.status": [
        "submitted"
    ],
    "asr_error.responses.users": [
        "bee532bf-10c0-4a3f-9386-3b5c3522197a"
    ],
    "audio": "\n\u003caudio controls\u003e\n    \u003csource src=\"https://huggingface.co./datasets/michaljunczyk/bigos-eval-results-secret/resolve/main/inspection_input/audio/amu-cai/pl-asr-bigos-v2-secret/pwr-viu-unk/pwr-viu-unk-test-0003-00283.mp3\" type=\"audio/mpeg\"\u003e\n\u003c/audio\u003e\n",
    "audio_issue.responses": null,
    "audio_issue.responses.status": null,
    "audio_issue.responses.users": null,
    "error_types.responses": [
        [
            "none"
        ]
    ],
    "error_types.responses.status": [
        "submitted"
    ],
    "error_types.responses.users": [
        "bee532bf-10c0-4a3f-9386-3b5c3522197a"
    ],
    "hyp": "Hyphotesis",
    "id": "dce1711c-1d36-4d2a-86ac-afaf85aacb06",
    "ref": "Reference transcription wav",
    "ref_issue.responses": null,
    "ref_issue.responses.status": null,
    "ref_issue.responses.users": null,
    "status": "completed",
    "subset": "pwr-viu-unk-3"
}
```


### Data Splits

The dataset contains a single split, which is `train`.

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation guidelines

Inspect ASR evaluation results and data.

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

[More Information Needed]

### Contributions

[More Information Needed]