SAWDUST: a Semi-Automated Wizard Dialogue Utterance Selection Tool for domain-independent large-domain dialogue
نویسندگان
چکیده
We present a tool that allows human wizards to select appropriate response utterances for a given dialogue context from a set of utterances observed in a dialogue corpus. Such a tool can be used in Wizard-of-Oz studies and for collecting data which can be used for training and/or evaluating automatic dialogue models. We also propose to incorporate such automatic dialogue models back into the tool as an aid in selecting utterances from a large dialogue corpus. The tool allows a user to rank candidate utterances for selection according to these automatic models.
منابع مشابه
Toward Habitable Assistance from Spoken Dialogue Systems
Spoken dialogue is increasingly central to systems that assist people. As the tasks that people and machines speak about together become more complex, however, users’ dissatisfaction with those systems is an important concern. This paper presents a novel approach to learning for spoken dialogue systems. It describes embedded wizardry, a methodology for learning from skilled people, and applies ...
متن کاملWizard of Oz Experiments on Speech Dialogue Systems Design and Realisation with a New Integrated Simulation Environment
The Wizard of Oz simulation technique is an approved aid for designing speech dialogue systems. There are a number of tools for simulation which have been used successfully, but which are inflexible in terms of the application domain, support for additional modalities, or integration with existing dialogue design tools. This thesis describes the design and realisation of Wizard of Oz experiment...
متن کاملFish or Fowl: A Wizard of Oz Evaluation of Dialogue Strategies in the Restaurant Domain
Recent work on evaluation of spoken dialogue systems suggests that the information presentation phase of complex dialogues is often the primary contributor to dialogue duration. This indicates that better algorithms are needed for the presentation of complex information in speech. Currently however we lack data about the tasks and dialogue strategies on which to base such algorithms. In this pa...
متن کاملDialogue Management based on Multi-domain Corpus
Dialogue Management (DM) is a key issue in Spoken Dialogue System. Most of the existing data-driven DM schemes train the dialogue policy for some specific domain (or vertical domain), only using the dialogue corpus in this domain, which might suffer from the scarcity of dialogue corpus in some domains. In this paper, we divide Dialogue Act (DA), as semantic representation of utterance, into DA ...
متن کاملThe Negochat Corpus of Human-agent Negotiation Dialogues
Annotated in-domain corpora are crucial to the successful development of dialogue systems of automated agents, and in particular for developing natural language understanding (NLU) components of such systems. Unfortunately, such important resources are scarce. In this work, we introduce an annotated natural language human-agent dialogue corpus in the negotiation domain. The corpus was collected...
متن کامل