Datasets:
Sub-tasks:
dialogue-modeling
Languages:
English
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
Source Datasets:
original
ArXiv:
Tags:
License:
| 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. |