IVA-Guided IVR Interaction Using Natural Language Commands
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Solution Overview
Problem
Interacting with Interactive Voice Response (IVR) systems is often time-consuming and cumbersome, requiring users to navigate complex menus and wait for live agents, leading to inefficient use of time and potential dissatisfaction.
Innovation Solution
Implementing an intelligent virtual assistant (IVA) system that allows users to interact with IVR systems using natural language commands and haptic inputs, enabling streamlined navigation and response to IVR prompts through a communication tool that includes a graphical user interface (GUI) for visual representation of menu options.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional IVR systems are used, then system simplicity is maintained, but user interaction quality deteriorates due to lack of personalization and context awareness
Solution Approach 1:
The IVR system is segmented into multiple independent modules including speech recognition module, natural language processing module, dialog management module, and speech synthesis module. Each module handles specific functions independently, allowing the system to provide sophisticated personalization and context awareness while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The IVR system is designed as a universal platform that can handle multiple types of user interactions (voice commands, natural language queries, dialog-based tasks) and adapt to different contexts. The system universally processes various input types and provides personalized responses across different scenarios, improving user interaction quality without requiring separate specialized systems.
2Ease of operation
If speech recognition and natural language processing are added to IVR, then user interaction quality improves through personalization, but system complexity increases
Solution Approach 1:
User profiles and preferences are pre-configured and stored in the system before actual interactions occur. The dialog management module pre-processes user inputs and maintains context information in advance, allowing the system to provide personalized responses without complex real-time processing. Historical interaction data is pre-analyzed to establish user patterns, reducing the complexity of on-the-fly personalization.
Solution Approach 2:
A dialog management module acts as an intermediary between the speech recognition/natural language processing components and the core IVR system. This mediator layer processes and structures the complex language inputs, manages dialog state, and coordinates with user profiles, thereby isolating the complexity of language processing from the rest of the system while enabling sophisticated personalization.
3Ease of operation
If context-aware processing is implemented, then user experience improves, but processing time increases
Solution Approach 1:
Context information and user profiles are pre-loaded and maintained in ready-state memory structures before interactions begin. The system pre-processes and stores relevant contextual data, allowing rapid retrieval during user interactions without requiring time-consuming analysis at the moment of processing. This preliminary preparation enables context-aware responses with minimal additional processing time.
Data Source
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AI summary
Systems and methods are provided for initiating an Intelligent Virtual Assistant (IVA) for facilitating user interaction with an automated call handling system such as Interactive Voice Response (IVR) system. A computer-implemented method may obtain a command for initiating an IVA system during a call between a mobile device operated by a user and an automated call handling system. Next, the method may obtain a first natural language command from the mobile device, determine a first user action based on the first natural language command, and transmit the determined user action to the automated call handling system. Finally, the method may obtain a first audio response from the automated call handling system in response to the transmitted user action, and transmit the first audio response to the user upon determining that the first audio response includes information associated with the first user request.