Software Technology for Method for extracting the most important dialogs from live data

APPLE INC. (Cupertino, CA)

Systems and processes are disclosed for the recognition of requests by virtual assistants with live usage data and information about future events. User requests that are received and not acknowledged can be used to develop template templates for candidates. The count can be linked with each candidate request template and is incremented each time a matching candidate request template is received. A template for a candidate that is in line with the threshold could be utilized to teach virtual assistants on how to handle similar requests. The data pertaining to future events can be mined to find relevant data to use in populating both candidate and recognized user request templates. Templates for user requests that have been populated (e.g., whole expected speech patterns) can then be utilized to identify user requests and decipher user intention as future events are relevant.

Electronic devices have access to more functions, services, information and data on the internet as well as other sources. With advancements in technology and software, these devices continue to advance. In many instances, each software program, function, website, or other feature has its own user interface as well as operationalmodels, which can be difficult to master and can be intimidating for novice users. Furthermore, many users could not be aware of the many functions and information available to them. These users might not be able to make use of certain resources effectively, and some users may feel overwhelmed or annoyed by the growing capabilities of consumer devices.

In addition to novice users many other individuals may find it difficult to make use of the numerous options available on consumer devices. For example, individuals who are disabled, handicapped or elderly and distracted, operatinga vehicle, engaged in certain activities or similar activities may have difficulty interfacing with their devices in a safe and efficiently. They may also be unable to navigate the various functions, apps, websites, features and other options available.

A virtual assistant, also known as an intelligent assistant, could provide a better interaction between a person and electronic gadget. It addresses particular user requirements while providing improved functionality to everyone. For instance, a virtual assistant will facilitate the use of the various features, apps and features, websites and other features that may be available.

A virtual assistant can respond to specific requests and even recognize them in certain situations. However, a virtual assistant may not be able to identify or train to respond to all new requests made by users. They may alter as time passes. Users can request information from new sources and seek information in a different manner from a trusted source or request a function with unrecognized terminology or request a feature for an application that is brand new. The virtual assistant may not be able to recognize new terms employed by users in reference to outdated information. Users may request information about the future, for instance, the premiere of a film and the virtual assistant may not be able to recognize the appropriate terminology (e.g. the movie’s new title). Virtual assistants can therefore receive requests from users which they’re not able handle. For instance, as the information source changes over time, or users make new requests, or in different ways, virtual assistants may not be able to recognize similar terms (e.g. the latest movie title).

Processes and systems for recognition of requests by virtual assistants are revealed using live usage data and expected or planned data. A virtual assistant can compare user requests to determine the best way to respond. If the received request is not acknowledged the request could be used to create template templates for request candidates that can be stored and evaluated to determine the importance of each of the candidate request templates. For example, templates for candidate forms derived of user-submitted requests that have not been recognized may be stored in a database. As new candidate templates are received, they may be compared with candidate templates already in the database. A number of matching templates for candidates can be increased to show how often the candidate template was identified from requests. The threshold threshold occurs when the number of requests for templates for candidates exceeds a threshold. This lets the virtual assistant utilize the templates for candidate in order to teach it to identify similar requests (e.g. the language model can also be taught using template templates of candidates).

A virtual assistant can be trained using data that will be used in future requests. There are many ways to get data related to the future. Addresses, names, and similar information can be extracted from the received data. This data can then be used to populate existing templates for user requests or to seed new ones (e.g. whole user’s speech). You can use the template templates that are populated to create a virtual assistant that it is able to be able to recognize and respond to user requests in the event that the data in the future is relevant.

In different scenarios, data relating to future events may be incorporated into template templates for candidate requests that a virtual assistant may not be able to recognize. For instance, names, dates and addresses as well as the like extracted from data relating to future eventscan be used to populate or seed template for candidates that have been deemed salient in relation to the frequency they have been received. The populated candidate request templates can be used to teach an assistant virtual instructing the virtual assistant to recognize and respond to the corresponding unpopulated candidate request templates.

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