A dialog system or conversational agent (CA) is a computer system intended to converse with a human, with a coherent structure. Dialog systems have employed text, speech, graphics, haptics, gestures and other modes for communication on both the input and output channel.
What does and does not constitute a dialog system may be debatable. The typical GUI wizard does engage in some sort of dialog, but it includes very few of the common dialog system components, and dialog state is trivial.
There are many different architectures for dialog systems. What sets of components are included in a dialog system, and how those components divide up responsibilities differs from system to system. Principal to any dialog system is the dialog manager, which is a component that manages the state of the dialog, and dialog strategy. A typical activity cycle in a dialog system contains the following phases:
- The user speaks, and the input is converted to plain text by the system's input recognizer/decoder, which may include:
- The text is analyzed by a Natural language understanding unit (NLU), which may include:
- The semantic information is analyzed by the dialog manager, that keeps the history and state of the dialog and manages the general flow of the conversation.
- Usually, the dialog manager contacts one or more task managers, that have knowledge of the specific task domain.
- The dialog manager produces output using an output generator, which may include:
- Finally, the output is rendered using an output renderer, which may include:
Dialog systems that are based on a text-only interface (e.g. text-based chat) contain only stages 2–5.
Types of systems
Dialog systems fall into the following categories, which are listed here along a few dimensions. Many of the categories overlap and the distinctions may not be well established.
- by modality
- by device
- by style
- by initiative
- system initiative
- user initiative
- mixed initiative
Dialog systems can support a broad range of applications in business enterprises, education, government, healthcare, and entertainment. For example:
- Responding to customers' questions about products and services via a company’s website or intranet portal
- Customer service agent knowledge base: Allows agents to type in a customer’s question and guide them with a response
- Guided selling: Facilitating transactions by providing answers and guidance in the sales process, particularly for complex products being sold to novice customers
- Help desk: Responding to internal employee questions, e.g., responding to HR questions
- Website navigation: Guiding customers to relevant portions of complex websites—a Website concierge
- Technical support: Responding to technical problems, such as diagnosing a problem with a product or device
- Personalized service: Conversational agents can leverage internal and external databases to personalize interactions, such as answering questions about account balances, providing portfolio information, delivering frequent flier or membership information, for example
- Training or education: They can provide problem-solving advice while the user learns
- Simple dialog systems are widely used to decrease human workload in call centres. In this and other industrial telephony applications, the functionality provided by dialog systems is known as interactive voice response or IVR.
In some cases, conversational agents can interact with users using artificial characters. These agents are then referred to as embodied agents.
Toolkits and architectures
A survey of current frameworks, languages and technologies for defining dialog systems.
|Name & Links||System Type||Description||Affiliation[s]||Environment[s]||Comments|
|AIML||Chatterbot language||XML dialect for creating natural language software agents||Richard Wallace|
|ChatScript||Chatterbot language||Language/Engine for creating natural language software agents||Bruce Wilcox|
||a state-based speech interface prototyping environment||OGI School of Science and Engineering
|publications are from 1999.|
|NLUI Server||Domain-independent toolkit||complete multilingual framework for building natural language user interface systems||LinguaSys||out-of-box support of mixed-initiative dialogs|
|Olympus||complete framework for implementing spoken dialog systems||Carnegie Mellon University|||
|Spoken dialog||multimodal dialog markup language||developed initially by AT&T then administered by an industry consortium and finally a W3C specification||Example||primarily for telephony.|
|SALT||markup language||multimodal dialog markup language||Microsoft||"has not reached the level of maturity of VoiceXML in the standards process".|
|Quack.com - QXML||Development Environment||company bought by AOL|
|OpenDial||Domain-independent toolkit||hybrid symbolic/statistical framework for spoken dialog systems, implemented in Java||University of Oslo|
- Jufarsky & Martin (2009), Speech and language processing. Pearson International Edition, ISBN 978-0-13-504196-3, Chapter 24
- Lester, J.; Branting, K.; Mott, B. (2004), "Conversational Agents" (PDF), The Practical Handbook of Internet Computing, Chapman & Hall
- Will, Thomas (2007). Creating a Dynamic Speech Dialogue. VDM Verlag Dr. Müller. ISBN 978-3-8364-4990-8.
||This article's use of external links may not follow Wikipedia's policies or guidelines. (November 2011)|
- The Conversational Interface: Our Next Great Leap Forward, 2003, article on the CI by futurist John Smart.
- Dialogue Processing in Spoken Language Systems
- Voice User Interface Design
- Spoken Dialogue Technology: Towards the Conversational Interface
- Machine Conversations
- Dialog system at BookRags.
- Dialogue system links by Staffan Larsson.
- Machine learning approaches to building spoken dialogue systems: the CLASSiC project.