Datasets:

ConvLab
/

tm2

@@ -1,10 +1,34 @@
-# Dataset Card for Taskmaster-1
 - **Repository:** https://github.com/google-research-datasets/Taskmaster/tree/master/TM-2-2020
 - **Paper:** https://arxiv.org/pdf/1909.05358.pdf
 - **Leaderboard:** None
 - **Who transforms the dataset:** Qi Zhu(zhuq96 at gmail dot com)
 ### Dataset Summary
 The Taskmaster-2 dataset consists of 17,289 dialogs in the seven domains. 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, as seen for example in the restaurants, flights, hotels, and movies verticals. The music browsing and sports conversations are almost exclusively search- and recommendation-based. 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.

+---
+language:
+- en
+license:
+- cc-by-4.0
+multilinguality:
+- monolingual
+pretty_name: Taskmaster-2
+size_categories:
+- 10K<n<100K
+task_categories:
+- conversational
+---
+# Dataset Card for Taskmaster-2
 - **Repository:** https://github.com/google-research-datasets/Taskmaster/tree/master/TM-2-2020
 - **Paper:** https://arxiv.org/pdf/1909.05358.pdf
 - **Leaderboard:** None
 - **Who transforms the dataset:** Qi Zhu(zhuq96 at gmail dot com)
+To use this dataset, you need to install [ConvLab-3](https://github.com/ConvLab/ConvLab-3) platform first. Then you can load the dataset via:
+```
+from convlab.util import load_dataset, load_ontology, load_database
+dataset = load_dataset('tm2')
+ontology = load_ontology('tm2')
+database = load_database('tm2')
+```
+For more usage please refer to [here](https://github.com/ConvLab/ConvLab-3/tree/master/data/unified_datasets).
 ### Dataset Summary
 The Taskmaster-2 dataset consists of 17,289 dialogs in the seven domains. 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, as seen for example in the restaurants, flights, hotels, and movies verticals. The music browsing and sports conversations are almost exclusively search- and recommendation-based. 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.