A Slot Is Not Built in One Utterance: Spoken Language Dialogs with Sub-Slots

• URL: http://arxiv.org/abs/2203.10759v1
• Date: Mon, 21 Mar 2022 07:10:19 GMT
• Title: A Slot Is Not Built in One Utterance: Spoken Language Dialogs with Sub-Slots
• Authors: Sai Zhang, Yuwei Hu, Yuchuan Wu, Jiaman Wu, Yongbin Li, Jian Sun, Caixia Yuan and Xiaojie Wang
• Abstract summary: This paper defines a new task named Sub-Slot based Task-Oriented Dialog (SSTOD) The dataset includes a total of 40K dialogs and 500K utterances from four different domains: Chinese names, phone numbers, ID numbers and license plate numbers. We find some new linguistic phenomena and interactive manners in SSTOD which raise critical challenges of building dialog agents for the task.
• Score: 67.69407159704328
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: A slot value might be provided segment by segment over multiple-turn interactions in a dialog, especially for some important information such as phone numbers and names. It is a common phenomenon in daily life, but little attention has been paid to it in previous work. To fill the gap, this paper defines a new task named Sub-Slot based Task-Oriented Dialog (SSTOD) and builds a Chinese dialog dataset SSD for boosting research on SSTOD. The dataset includes a total of 40K dialogs and 500K utterances from four different domains: Chinese names, phone numbers, ID numbers and license plate numbers. The data is well annotated with sub-slot values, slot values, dialog states and actions. We find some new linguistic phenomena and interactive manners in SSTOD which raise critical challenges of building dialog agents for the task. We test three state-of-the-art dialog models on SSTOD and find they cannot handle the task well on any of the four domains. We also investigate an improved model by involving slot knowledge in a plug-in manner. More work should be done to meet the new challenges raised from SSTOD which widely exists in real-life applications. The dataset and code are publicly available via https://github.com/shunjiu/SSTOD.

Related papers

• DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI [92.29874802394167]
  DialogStudio is the largest and most diverse collection of dialogue datasets. Our collection encompasses data from open-domain dialogues, task-oriented dialogues, natural language understanding, conversational recommendation, dialogue summarization, and knowledge-grounded dialogues.
  arXiv  Detail & Related papers  (2023-07-19T17:57:53Z)
• SpokenWOZ: A Large-Scale Speech-Text Benchmark for Spoken Task-Oriented Dialogue Agents [72.42049370297849]
  SpokenWOZ is a large-scale speech-text dataset for spoken TOD. Cross-turn slot and reasoning slot detection are new challenges for SpokenWOZ.
  arXiv  Detail & Related papers  (2023-05-22T13:47:51Z)
• CGoDial: A Large-Scale Benchmark for Chinese Goal-oriented Dialog Evaluation [75.60156479374416]
  CGoDial is a new challenging and comprehensive Chinese benchmark for Goal-oriented Dialog evaluation. It contains 96,763 dialog sessions and 574,949 dialog turns totally, covering three datasets with different knowledge sources. To bridge the gap between academic benchmarks and spoken dialog scenarios, we either collect data from real conversations or add spoken features to existing datasets via crowd-sourcing.
  arXiv  Detail & Related papers  (2022-11-21T16:21:41Z)
• What Did You Say? Task-Oriented Dialog Datasets Are Not Conversational!? [4.022057598291766]
  We outline a taxonomy of conversational and contextual effects, which we use to examine MultiWOZ, SGD and SMCalFlow. We find that less than 4% of MultiWOZ's turns and 10% of SGD's turns are conversational, while SMCalFlow is not conversational at all in its current release.
  arXiv  Detail & Related papers  (2022-03-07T14:26:23Z)
• Dialog without Dialog Data: Learning Visual Dialog Agents from VQA Data [75.7372052716556]
  "Dialog without Dialog" requires agents to develop dialog models that can adapt to new tasks without language level supervision. By factorizing intention and language, our model minimizes linguistic drift after fine-tuning for new tasks.
  arXiv  Detail & Related papers  (2020-07-24T19:35:57Z)
• CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset [58.910961297314415]
  CrossWOZ is the first large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset. It contains 6K dialogue sessions and 102K utterances for 5 domains, including hotel, restaurant, attraction, metro, and taxi.
  arXiv  Detail & Related papers  (2020-02-27T03:06:35Z)
• Goal-Oriented Multi-Task BERT-Based Dialogue State Tracker [0.1864131501304829]
  State Tracking (DST) is a core component of virtual assistants such as Alexa or Siri. In this work, we propose a GOaL-Oriented Multi-task BERT-based dialogue state tracker (GOLOMB)
  arXiv  Detail & Related papers  (2020-02-05T22:56:12Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.