|
--- |
|
annotations_creators: |
|
- crowdsourced |
|
language_creators: |
|
- crowdsourced |
|
language: |
|
- en |
|
license: |
|
- cc-by-4.0 |
|
multilinguality: |
|
- monolingual |
|
size_categories: |
|
- 1K<n<10K |
|
source_datasets: |
|
- original |
|
task_categories: |
|
- text-generation |
|
- fill-mask |
|
task_ids: |
|
- dialogue-modeling |
|
paperswithcode_id: taskmaster-2 |
|
pretty_name: Taskmaster-2 |
|
dataset_info: |
|
- config_name: flights |
|
features: |
|
- name: conversation_id |
|
dtype: string |
|
- name: instruction_id |
|
dtype: string |
|
- name: utterances |
|
list: |
|
- name: index |
|
dtype: int32 |
|
- name: speaker |
|
dtype: string |
|
- name: text |
|
dtype: string |
|
- name: segments |
|
list: |
|
- name: start_index |
|
dtype: int32 |
|
- name: end_index |
|
dtype: int32 |
|
- name: text |
|
dtype: string |
|
- name: annotations |
|
list: |
|
- name: name |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 7073487 |
|
num_examples: 2481 |
|
download_size: 23029880 |
|
dataset_size: 7073487 |
|
- config_name: food-ordering |
|
features: |
|
- name: conversation_id |
|
dtype: string |
|
- name: instruction_id |
|
dtype: string |
|
- name: utterances |
|
list: |
|
- name: index |
|
dtype: int32 |
|
- name: speaker |
|
dtype: string |
|
- name: text |
|
dtype: string |
|
- name: segments |
|
list: |
|
- name: start_index |
|
dtype: int32 |
|
- name: end_index |
|
dtype: int32 |
|
- name: text |
|
dtype: string |
|
- name: annotations |
|
list: |
|
- name: name |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 1734825 |
|
num_examples: 1050 |
|
download_size: 5376675 |
|
dataset_size: 1734825 |
|
- config_name: hotels |
|
features: |
|
- name: conversation_id |
|
dtype: string |
|
- name: instruction_id |
|
dtype: string |
|
- name: utterances |
|
list: |
|
- name: index |
|
dtype: int32 |
|
- name: speaker |
|
dtype: string |
|
- name: text |
|
dtype: string |
|
- name: segments |
|
list: |
|
- name: start_index |
|
dtype: int32 |
|
- name: end_index |
|
dtype: int32 |
|
- name: text |
|
dtype: string |
|
- name: annotations |
|
list: |
|
- name: name |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 7436667 |
|
num_examples: 2357 |
|
download_size: 22507266 |
|
dataset_size: 7436667 |
|
- config_name: movies |
|
features: |
|
- name: conversation_id |
|
dtype: string |
|
- name: instruction_id |
|
dtype: string |
|
- name: utterances |
|
list: |
|
- name: index |
|
dtype: int32 |
|
- name: speaker |
|
dtype: string |
|
- name: text |
|
dtype: string |
|
- name: segments |
|
list: |
|
- name: start_index |
|
dtype: int32 |
|
- name: end_index |
|
dtype: int32 |
|
- name: text |
|
dtype: string |
|
- name: annotations |
|
list: |
|
- name: name |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 7112301 |
|
num_examples: 3056 |
|
download_size: 21189893 |
|
dataset_size: 7112301 |
|
- config_name: music |
|
features: |
|
- name: conversation_id |
|
dtype: string |
|
- name: instruction_id |
|
dtype: string |
|
- name: utterances |
|
list: |
|
- name: index |
|
dtype: int32 |
|
- name: speaker |
|
dtype: string |
|
- name: text |
|
dtype: string |
|
- name: segments |
|
list: |
|
- name: start_index |
|
dtype: int32 |
|
- name: end_index |
|
dtype: int32 |
|
- name: text |
|
dtype: string |
|
- name: annotations |
|
list: |
|
- name: name |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 2814030 |
|
num_examples: 1603 |
|
download_size: 8981720 |
|
dataset_size: 2814030 |
|
- config_name: restaurant-search |
|
features: |
|
- name: conversation_id |
|
dtype: string |
|
- name: instruction_id |
|
dtype: string |
|
- name: utterances |
|
list: |
|
- name: index |
|
dtype: int32 |
|
- name: speaker |
|
dtype: string |
|
- name: text |
|
dtype: string |
|
- name: segments |
|
list: |
|
- name: start_index |
|
dtype: int32 |
|
- name: end_index |
|
dtype: int32 |
|
- name: text |
|
dtype: string |
|
- name: annotations |
|
list: |
|
- name: name |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 7341998 |
|
num_examples: 3276 |
|
download_size: 21472680 |
|
dataset_size: 7341998 |
|
- config_name: sports |
|
features: |
|
- name: conversation_id |
|
dtype: string |
|
- name: instruction_id |
|
dtype: string |
|
- name: utterances |
|
list: |
|
- name: index |
|
dtype: int32 |
|
- name: speaker |
|
dtype: string |
|
- name: text |
|
dtype: string |
|
- name: segments |
|
list: |
|
- name: start_index |
|
dtype: int32 |
|
- name: end_index |
|
dtype: int32 |
|
- name: text |
|
dtype: string |
|
- name: annotations |
|
list: |
|
- name: name |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 5738818 |
|
num_examples: 3481 |
|
download_size: 19549440 |
|
dataset_size: 5738818 |
|
--- |
|
|
|
# Dataset Card for Taskmaster-2 |
|
|
|
## Table of Contents |
|
- [Dataset Description](#dataset-description) |
|
- [Dataset Summary](#dataset-summary) |
|
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
|
- [Languages](#languages) |
|
- [Dataset Structure](#dataset-structure) |
|
- [Data Instances](#data-instances) |
|
- [Data Fields](#data-fields) |
|
- [Data Splits](#data-splits) |
|
- [Dataset Creation](#dataset-creation) |
|
- [Curation Rationale](#curation-rationale) |
|
- [Source Data](#source-data) |
|
- [Annotations](#annotations) |
|
- [Personal and Sensitive Information](#personal-and-sensitive-information) |
|
- [Considerations for Using the Data](#considerations-for-using-the-data) |
|
- [Social Impact of Dataset](#social-impact-of-dataset) |
|
- [Discussion of Biases](#discussion-of-biases) |
|
- [Other Known Limitations](#other-known-limitations) |
|
- [Additional Information](#additional-information) |
|
- [Dataset Curators](#dataset-curators) |
|
- [Licensing Information](#licensing-information) |
|
- [Citation Information](#citation-information) |
|
- [Contributions](#contributions) |
|
|
|
## Dataset Description |
|
|
|
- **Homepage:** [Taskmaster-1](https://research.google/tools/datasets/taskmaster-1/) |
|
- **Repository:** [GitHub](https://github.com/google-research-datasets/Taskmaster/tree/master/TM-2-2020) |
|
- **Paper:** [Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset](https://arxiv.org/abs/1909.05358) |
|
- **Leaderboard:** N/A |
|
- **Point of Contact:** [Taskmaster Googlegroup](taskmaster-datasets@googlegroups.com) |
|
|
|
### Dataset Summary |
|
|
|
Taskmaster is dataset for goal oriented conversations. The Taskmaster-2 dataset consists of 17,289 dialogs |
|
in the seven domains which include restaurants, food ordering, movies, hotels, flights, music and sports. |
|
Unlike Taskmaster-1, which includes both written "self-dialogs" and spoken two-person dialogs, |
|
Taskmaster-2 consists entirely of spoken two-person dialogs. In addition, while Taskmaster-1 is |
|
almost exclusively task-based, Taskmaster-2 contains a good number of search- and recommendation-oriented dialogs. |
|
All dialogs in this release were created using a Wizard of Oz (WOz) methodology in which crowdsourced |
|
workers played the role of a 'user' and trained call center operators played the role of the 'assistant'. |
|
In this way, users were led to believe they were interacting with an automated system that “spoke” |
|
using text-to-speech (TTS) even though it was in fact a human behind the scenes. |
|
As a result, users could express themselves however they chose in the context of an automated interface. |
|
|
|
### Supported Tasks and Leaderboards |
|
|
|
[More Information Needed] |
|
|
|
### Languages |
|
|
|
The dataset is in English language. |
|
|
|
## Dataset Structure |
|
|
|
### Data Instances |
|
|
|
A typical example looks like this |
|
|
|
``` |
|
{ |
|
"conversation_id": "dlg-0047a087-6a3c-4f27-b0e6-268f53a2e013", |
|
"instruction_id": "flight-6", |
|
"utterances": [ |
|
{ |
|
"index": 0, |
|
"segments": [], |
|
"speaker": "USER", |
|
"text": "Hi, I'm looking for a flight. I need to visit a friend." |
|
}, |
|
{ |
|
"index": 1, |
|
"segments": [], |
|
"speaker": "ASSISTANT", |
|
"text": "Hello, how can I help you?" |
|
}, |
|
{ |
|
"index": 2, |
|
"segments": [], |
|
"speaker": "ASSISTANT", |
|
"text": "Sure, I can help you with that." |
|
}, |
|
{ |
|
"index": 3, |
|
"segments": [], |
|
"speaker": "ASSISTANT", |
|
"text": "On what dates?" |
|
}, |
|
{ |
|
"index": 4, |
|
"segments": [ |
|
{ |
|
"annotations": [ |
|
{ |
|
"name": "flight_search.date.depart_origin" |
|
} |
|
], |
|
"end_index": 37, |
|
"start_index": 27, |
|
"text": "March 20th" |
|
}, |
|
{ |
|
"annotations": [ |
|
{ |
|
"name": "flight_search.date.return" |
|
} |
|
], |
|
"end_index": 45, |
|
"start_index": 41, |
|
"text": "22nd" |
|
} |
|
], |
|
"speaker": "USER", |
|
"text": "I'm looking to travel from March 20th to 22nd." |
|
} |
|
] |
|
} |
|
``` |
|
|
|
### Data Fields |
|
|
|
Each conversation in the data file has the following structure: |
|
|
|
- `conversation_id`: A universally unique identifier with the prefix 'dlg-'. The ID has no meaning. |
|
- `utterances`: A list of utterances that make up the conversation. |
|
- `instruction_id`: A reference to the file(s) containing the user (and, if applicable, agent) instructions for this conversation. |
|
|
|
Each utterance has the following fields: |
|
|
|
- `index`: A 0-based index indicating the order of the utterances in the conversation. |
|
- `speaker`: Either USER or ASSISTANT, indicating which role generated this utterance. |
|
- `text`: The raw text of the utterance. In case of self dialogs (one_person_dialogs), this is written by the crowdsourced worker. In case of the WOz dialogs, 'ASSISTANT' turns are written and 'USER' turns are transcribed from the spoken recordings of crowdsourced workers. |
|
- `segments`: A list of various text spans with semantic annotations. |
|
|
|
Each segment has the following fields: |
|
|
|
- `start_index`: The position of the start of the annotation in the utterance text. |
|
- `end_index`: The position of the end of the annotation in the utterance text. |
|
- `text`: The raw text that has been annotated. |
|
- `annotations`: A list of annotation details for this segment. |
|
|
|
Each annotation has a single field: |
|
|
|
- `name`: The annotation name. |
|
|
|
|
|
|
|
### Data Splits |
|
|
|
There are no deafults splits for all the config. The below table lists the number of examples in each config. |
|
|
|
| Config | Train | |
|
|-------------------|--------| |
|
| flights | 2481 | |
|
| food-orderings | 1050 | |
|
| hotels | 2355 | |
|
| movies | 3047 | |
|
| music | 1602 | |
|
| restaurant-search | 3276 | |
|
| sports | 3478 | |
|
|
|
|
|
## Dataset Creation |
|
|
|
### Curation Rationale |
|
|
|
[More Information Needed] |
|
|
|
### Source Data |
|
|
|
[More Information Needed] |
|
|
|
#### Initial Data Collection and Normalization |
|
|
|
[More Information Needed] |
|
|
|
#### Who are the source language producers? |
|
|
|
[More Information Needed] |
|
|
|
### Annotations |
|
|
|
[More Information Needed] |
|
|
|
#### 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 |
|
|
|
The dataset is licensed under `Creative Commons Attribution 4.0 License` |
|
|
|
### Citation Information |
|
|
|
[More Information Needed] |
|
``` |
|
@inproceedings{48484, |
|
title = {Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset}, |
|
author = {Bill Byrne and Karthik Krishnamoorthi and Chinnadhurai Sankar and Arvind Neelakantan and Daniel Duckworth and Semih Yavuz and Ben Goodrich and Amit Dubey and Kyu-Young Kim and Andy Cedilnik}, |
|
year = {2019} |
|
} |
|
``` |
|
### Contributions |
|
|
|
Thanks to [@patil-suraj](https://github.com/patil-suraj) for adding this dataset. |
