
# EVI

## Dataset Description
- **Paper:** [EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification](https://arxiv.org/abs/2204.13496)
- **Repository:** [Github](https://github.com/PolyAI-LDN/evi-paper)

EVI is a challenging spoken multilingual dataset
with 5,506 dialogues in English, Polish, and French
that can be used for benchmarking and developing
knowledge-based enrolment, identification, and identification for spoken dialogue systems.

## Example
EVI can be downloaded and used as follows:

```py
from datasets import load_dataset
evi = load_dataset("PolyAI/evi", "en-GB") # for British English

# to download data from all locales use:
# evi = load_dataset("PolyAI/evi", "all")

# see structure
print(evi)
```

## Dataset Structure

We show detailed information of the example for the `en-GB` configuration of the dataset.
All other configurations have the same structure.

### Data Instances

An example of a data instance of the config `en-GB` looks as follows:

```
{
    "language": 0,
    "dialogue_id": "CA0007220161df7be23f4554704c8720f5",
    "speaker_id": "e80e9bdd33eda593f16a1b6f2fb228ff",
    "turn_id": 0,
    "target_profile_id": "en.GB.608",
    "asr_transcription": "w20 a b",
    "asr_nbest'": ["w20 a b", "w20 a bee", "w20 a baby"],
    "path": "audios/en/CA0007220161df7be23f4554704c8720f5/0.wav",
    "audio": {
        "path": "/home/georgios/.cache/huggingface/datasets/downloads/extracted/0335ebc25feace53243133b49ba17ba18e26f0f97cb083ffdf4e73dd7427b443/audios/en/CA0007220161df7be23f4554704c8720f5/0.wav",
        "array": array([ 0.00024414,  0.00024414,  0.00024414, ...,  0.00024414,
       -0.00024414,  0.00024414], dtype=float32),
       "sampling_rate": 8000,
    }
}
```

### Data Fields
The data fields are the same among all splits.
- **language** (int): ID of language
- **dialogue_id** (str): the ID of the dialogue
- **speaker_id** (str): the ID of the speaker
- **turn_id** (int)": the ID of the turn
- **target_profile_id** (str): the ID of the target profile
- **asr_transcription** (str): ASR transcription of the audio file
- **asr_nbest** (list): n-best ASR transcriptions of the audio file
- **path** (str): Path to the audio file
- **audio** (dict): Audio object including loaded audio array, sampling rate and path of audio


### Data Splits
Every config only has the `"test"` split containing *ca.* 1,800 dialogues.

## Dataset Creation

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

All datasets are licensed under the [Creative Commons license (CC-BY)](https://creativecommons.org/licenses/).

### Citation Information

```
@inproceedings{Spithourakis2022evi,
    author      = {Georgios P. Spithourakis and
                   Ivan Vuli\'{c} and
                   Micha\l{} Lis and
                   I\~{n}igo Casanueva
                   and Pawe\l{} Budzianowski},
    title       = {{EVI}: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification},
    year        = {2022},
    note        = {Data available at https://github.com/PolyAI-LDN/evi-paper},
    url         = {https://arxiv.org/abs/2204.13496},
    booktitle   = {Findings of NAACL (publication pending)}
}
```

### Contributions
Thanks to [@polinaeterna](https://github.com/polinaeterna) for helping with adding this dataset
annotations_creators:crowdsourced annotations_creators:machine-generated language_creators:crowdsourced language_creators:expert-generated multilinguality:multilingual language:en language:fr language:pl license:cc-by-4.0 arxiv:2204.13496 region:us
{"annotations_creators": ["crowdsourced", "machine-generated"], "language_creators": ["crowdsourced", "expert-generated"], "language": ["en", "fr", "pl"], "license": ["cc-by-4.0"], "multilinguality": ["multilingual"], "paperswithcode_id": "evi-multilingual-spoken-dialogue-tasks-and-1", "language_bcp47": ["en", "en-GB", "fr", "fr-FR", "pl"]}
TAGS
#annotations_creators-crowdsourced #annotations_creators-machine-generated #language_creators-crowdsourced #language_creators-expert-generated #multilinguality-multilingual #language-English #language-French #language-Polish #license-cc-by-4.0 #arxiv-2204.13496 #region-us 


# EVI

## Dataset Description
- Paper: EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification
- Repository: Github

EVI is a challenging spoken multilingual dataset
with 5,506 dialogues in English, Polish, and French
that can be used for benchmarking and developing
knowledge-based enrolment, identification, and identification for spoken dialogue systems.

## Example
EVI can be downloaded and used as follows:



## Dataset Structure

We show detailed information of the example for the 'en-GB' configuration of the dataset.
All other configurations have the same structure.

### Data Instances

An example of a data instance of the config 'en-GB' looks as follows:



### Data Fields
The data fields are the same among all splits.
- language (int): ID of language
- dialogue_id (str): the ID of the dialogue
- speaker_id (str): the ID of the speaker
- turn_id (int)": the ID of the turn
- target_profile_id (str): the ID of the target profile
- asr_transcription (str): ASR transcription of the audio file
- asr_nbest (list): n-best ASR transcriptions of the audio file
- path (str): Path to the audio file
- audio (dict): Audio object including loaded audio array, sampling rate and path of audio


### Data Splits
Every config only has the '"test"' split containing *ca.* 1,800 dialogues.

## Dataset Creation



## Considerations for Using the Data

### Social Impact of Dataset



### Discussion of Biases



### Other Known Limitations



## Additional Information

### Dataset Curators


### Licensing Information

All datasets are licensed under the Creative Commons license (CC-BY).





### Contributions
Thanks to @polinaeterna for helping with adding this dataset
# EVI ## Dataset Description
- Paper: EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification
- Repository: Github

EVI is a challenging spoken multilingual dataset
with 5,506 dialogues in English, Polish, and French
that can be used for benchmarking and developing
knowledge-based enrolment, identification, and identification for spoken dialogue systems. ## Example
EVI can be downloaded and used as follows: ## Dataset Structure

We show detailed information of the example for the 'en-GB' configuration of the dataset.
All other configurations have the same structure. ### Data Instances

An example of a data instance of the config 'en-GB' looks as follows: ### Data Fields
The data fields are the same among all splits.
- language (int): ID of language
- dialogue_id (str): the ID of the dialogue
- speaker_id (str): the ID of the speaker
- turn_id (int)": the ID of the turn
- target_profile_id (str): the ID of the target profile
- asr_transcription (str): ASR transcription of the audio file
- asr_nbest (list): n-best ASR transcriptions of the audio file
- path (str): Path to the audio file
- audio (dict): Audio object including loaded audio array, sampling rate and path of audio ### Data Splits
Every config only has the '"test"' split containing *ca.* 1,800 dialogues. ## Dataset Creation ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information

All datasets are licensed under the Creative Commons license (CC-BY). ### Contributions
Thanks to @polinaeterna for helping with adding this dataset
TAGS
#annotations_creators-crowdsourced #annotations_creators-machine-generated #language_creators-crowdsourced #language_creators-expert-generated #multilinguality-multilingual #language-English #language-French #language-Polish #license-cc-by-4.0 #arxiv-2204.13496 #region-us 
 # EVI ## Dataset Description
- Paper: EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification
- Repository: Github

EVI is a challenging spoken multilingual dataset
with 5,506 dialogues in English, Polish, and French
that can be used for benchmarking and developing
knowledge-based enrolment, identification, and identification for spoken dialogue systems. ## Example
EVI can be downloaded and used as follows: ## Dataset Structure

We show detailed information of the example for the 'en-GB' configuration of the dataset.
All other configurations have the same structure. ### Data Instances

An example of a data instance of the config 'en-GB' looks as follows: ### Data Fields
The data fields are the same among all splits.
- language (int): ID of language
- dialogue_id (str): the ID of the dialogue
- speaker_id (str): the ID of the speaker
- turn_id (int)": the ID of the turn
- target_profile_id (str): the ID of the target profile
- asr_transcription (str): ASR transcription of the audio file
- asr_nbest (list): n-best ASR transcriptions of the audio file
- path (str): Path to the audio file
- audio (dict): Audio object including loaded audio array, sampling rate and path of audio ### Data Splits
Every config only has the '"test"' split containing *ca.* 1,800 dialogues. ## Dataset Creation ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information

All datasets are licensed under the Creative Commons license (CC-BY). ### Contributions
Thanks to @polinaeterna for helping with adding this dataset
passage: TAGS
#annotations_creators-crowdsourced #annotations_creators-machine-generated #language_creators-crowdsourced #language_creators-expert-generated #multilinguality-multilingual #language-English #language-French #language-Polish #license-cc-by-4.0 #arxiv-2204.13496 #region-us 
# EVI## Dataset Description
- Paper: EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification
- Repository: Github

EVI is a challenging spoken multilingual dataset
with 5,506 dialogues in English, Polish, and French
that can be used for benchmarking and developing
knowledge-based enrolment, identification, and identification for spoken dialogue systems.## Example
EVI can be downloaded and used as follows:## Dataset Structure

We show detailed information of the example for the 'en-GB' configuration of the dataset.
All other configurations have the same structure.### Data Instances

An example of a data instance of the config 'en-GB' looks as follows:### Data Fields
The data fields are the same among all splits.
- language (int): ID of language
- dialogue_id (str): the ID of the dialogue
- speaker_id (str): the ID of the speaker
- turn_id (int)": the ID of the turn
- target_profile_id (str): the ID of the target profile
- asr_transcription (str): ASR transcription of the audio file
- asr_nbest (list): n-best ASR transcriptions of the audio file
- path (str): Path to the audio file
- audio (dict): Audio object including loaded audio array, sampling rate and path of audio### Data Splits
Every config only has the '"test"' split containing *ca.* 1,800 dialogues.## Dataset Creation## Considerations for Using the Data### Social Impact of Dataset### Discussion of Biases### Other Known Limitations## Additional Information### Dataset Curators