| | --- |
| | 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. |
