Notes:
Dialog systems, also known as conversational agents or chatbots, are interactive systems that are designed to communicate with users in natural language. They are used in a wide range of applications, including customer service, virtual assistants, and education.
There are several key aspects of dialog systems:
- Natural language processing (NLP): Dialog systems use natural language processing (NLP) techniques to understand and interpret user input, and to generate appropriate responses. This involves tasks such as speech recognition, language understanding, and text generation.
- Dialog management: Dialog systems need to be able to manage the flow of the conversation and keep track of the context and state of the conversation. This involves tasks such as determining when to ask a question or provide information, and handling user requests and feedback.
- Contextual understanding: Dialog systems need to be able to understand the context of the conversation and use this information to generate appropriate responses. This may involve tasks such as entity recognition and intent classification.
- Personalization and customization: Dialog systems can be customized to provide personalized responses based on user preferences, history, and other factors. This can help to improve the user experience and make the conversation feel more natural and engaging.
- Multimodality: Dialog systems may support multiple modes of communication, such as text, speech, and visual output. This can make them more flexible and able to adapt to different user needs and preferences.
References:
- Natural Language Dialog Systems and Intelligent Assistants (2015)
- Natural Interaction with Robots, Knowbots and Smartphones: Putting Spoken Dialog Systems into Practice (2014)
- Advances in Commercial Deployment of Spoken Dialog Systems (2011)
See also:
100 Best Dialog System Videos | 100 Best Unity3d Dialog System Videos | Neural Dialog Systems | Neural Turing Machine & Dialog Systems 2018
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