Important components in Siri

Released by Apple, Siri adopts a new artificial intelligence framework, making it refreshing not only in commercial propaganda, but also in its technical architecture and implementation. Although Siri was originally attached to the iPhone platform, it is clear that this dependence is not strong. We believe this system will continue to expand to more types of intelligent control hardware. To figure out why we said so, users should firstly know more about the important components in Siri.
Important components As a personalized intelligent assistant designed for iPhone, Siri is very helpful in many aspects. Why is Siri so powerful? That is because there are many important components in Siri, such as input system, active ontology and language pattern recognition system.
Input system: the input system of Siri supports multi-modal input. That is to say, the input system can not only support the well-known speech recognition, but also support text input, GUI interface operation and so on operations. Besides, the input system of Siri is able to perform disambiguation to early input content by using language interpreter. What’s more, the input system is able to provide conscious guidance to users’ inputs in order to make these inputs mapped to services that can be provided by this system. In this way, Siri can reflect its value and users can get help at the same time.
Active ontology: as one of the most important components in Siri, “active ontology” can be understood as a particular execution environment and place for the overall system. Execution system will call all system data, dictionaries, models and procedures. Then, it will parse users’ inputs and get their real intention in the “active ontology”. At last, it will call external services based on the real intention. During the execution of program, there are many different kinds of data and models in “active ontology”: domain models, user personalization information, language patterns, vocabularies and domain entity databases.
Language pattern recognition system: language pattern recognition system is actually a module used to perform pattern matching to users’ input layer, grammar layer and idioms. In Siri, the codes of matching patterns are achieved in the form of internal regular expression or state machine. After the specified language pattern has been identified, Siri is able to determine the type of task that users’ input content refers to.
Execution system: as is well-known, execution system is crucial in every system. There is no exception in Siri. The execution system of Siri helps to execute the tasks required by users. Oppositely, without execution system, no task will be completed by Siri.
Output system: the output system of Siri will finally show users the provided ultimate results or

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the content in the middle of the session. The output system of Siri supports voice, email, text and many other multi-modal outputs. In addition, the output system has many personalization features, such as interface custom.

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