Automated Interactive System for Dialog Data Collection
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Solution Overview
Problem
Current dialog systems face challenges in efficiently collecting high-quality dialog data for training, as existing methods like Wizard-of-Oz and ghost wizard systems are costly, time-consuming, and lack realism, and are domain-specific, failing to scale effectively for various applications.
Innovation Solution
An automated framework for generating interactive systems from a formalized description language that allows real-time data collection and annotation during human-machine interactions, enabling operators to control dialog systems and log data across multiple domains without interrupting the workflow, using a graphical user interface and modular components like speech recognition and text-to-speech modules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Wizard-of-Oz methodology is used to collect dialog data, then data quality is improved, but cost and time consumption increase significantly
Solution Approach 1:
The patent creates a virtual wizard system that copies the functionality of a human wizard through automated scripts and pre-recorded responses. This virtual wizard can handle multiple dialog sessions simultaneously, providing high-quality annotated data without the time and cost constraints of human operators. The system records and processes dialog interactions automatically, generating training data at scale.
Solution Approach 2:
The system enables self-service data collection by allowing the dialog system to automatically interact with callers, collect responses, and generate annotated dialog data without requiring human wizard intervention for each interaction. The automated framework handles the entire data collection process, from initiating dialog to recording and annotating responses.
2Measurement precision
If Wizard-of-Oz methodology is used to collect dialog data, then data quality is improved, but cost increases significantly
Solution Approach 1:
The patent creates a virtual wizard system that copies the functionality of a human wizard through automated scripts and pre-recorded responses. This virtual wizard can handle multiple dialog sessions simultaneously, providing high-quality annotated data without the time and cost constraints of human operators. The system records and processes dialog interactions automatically, generating training data at scale.
Solution Approach 2:
The system enables self-service data collection by allowing the dialog system to automatically interact with callers, collect responses, and generate annotated dialog data without requiring human wizard intervention for each interaction. The automated framework handles the entire data collection process, from initiating dialog to recording and annotating responses.
3Extent of automation
If ghost wizard system is used for data collection, then data collection is automated, but caller experience deteriorates
Solution Approach 1:
The patent implements a hybrid framework that can operate in multiple modes: fully automated mode for routine interactions, virtual wizard mode for structured data collection, and human agent mode for complex issues. This multi-functionality allows the system to maintain high automation levels while preserving caller experience by routing appropriate interactions to appropriate handlers.
Solution Approach 2:
The virtual wizard acts as an intermediary between the automated system and human agents, or between the system and callers. It can simulate human-like interactions to collect data while maintaining natural conversation flow, or bridge automated responses with human intervention when needed, preventing the harshness of purely automated ghost wizard systems.
4Measurement precision
If conventional WOZ interface is used for data collection, then real-world data can be collected, but the system is domain-specific and lacks scalability
Solution Approach 1:
The patent implements a hybrid framework that can operate in multiple modes: fully automated mode for routine interactions, virtual wizard mode for structured data collection, and human agent mode for complex issues. This multi-functionality allows the system to maintain high automation levels while preserving caller experience by routing appropriate interactions to appropriate handlers.
Solution Approach 2:
The virtual wizard acts as an intermediary between the automated system and human agents, or between the system and callers. It can simulate human-like interactions to collect data while maintaining natural conversation flow, or bridge automated responses with human intervention when needed, preventing the harshness of purely automated ghost wizard systems.
Data Source
AI summary
Systems and methods are described that automatically generate interactive systems configured for collecting dialog data of human-machine interactions in dialog systems. The systems and methods comprise receiving a task flow that describes operations of a dialog system. A formal description of the task flow is generated, and an interactive system comprising a graphical user interface (GUI) is automatically generated from the formal description. The GUI consists of templates for control of the dialog system and real-time collection and annotating of dialog data during a live dialog between only the dialog system and callers to the dialog system. The dialog data consists of data of the live dialog.