Patent Description:
<CIT> describes, in accordance with its abstract, a non-transitory computer-readable storage medium that stores one or more programs including instructions, which when executed by an electronic device, cause the electronic device to receive natural-language speech input from one of a plurality of users, the natural-language speech input having a set of acoustic properties; and determine whether the natural-language speech input corresponds to both a user-customizable lexical trigger and a set of acoustic properties associated with the user; where in accordance with a determination that the natural language speech input corresponds to both a user-customizable lexical trigger and a set of acoustic properties associated with the user, invoke a virtual assistant; and in accordance with a determination that either the natural language speech input fails to correspond to a user-customizable lexical trigger or the natural-language speech input fails to have a set of acoustic properties associated with the user, forego invocation of a virtual assistant.

At least one aspect is directed to a system to retrieve digital components in a voice activated data packet based computer network environment includes a natural language processor component. The natural language processor component isexecuted by a data processing system. The natural language processing component receives, via an interface of the data processing system, data packets comprising an input audio signal detected by a sensor of a computing device. The natural language processor component parses the input audio signal to identify a request, a content provider, and a trigger keyword corresponding to the request. The system includes a direct action application programming interface that generates, based on the trigger keyword, an action data structure responsive to the request and the identified content provider. The system includes a navigation component to: establish a session with the identified content provider; render, without a graphical user interface, a digital component received, via the session, from the content provider, to an image file for analysis with a machine vision component of the navigation component; select an interaction model associated with the content provider; identify using the selected interaction model one or more of input fields buttons, menus, image fields, images, or text of the digital component by performing a machine vision analysis of the image file; and generate a data array based on the information identified in the digital component using the interaction model and the action data structure. The system transmits, via the interface of the data processing system, the data array to the content provider to interact with the digital component to complete the request.

At least one aspect is directed to a method to retrieve and interact with digital components in a voice activated data packet based computer network environment. The method can include receiving, by a natural language processor component executed by a data processing system and via an interface of the data processing system, data packets that can include an input audio signal detected by a sensor of a computing device. The method can include parsing, by the natural language processor component, the input audio signal to identify a request, a content provider, and a trigger keyword corresponding to the request. The method can include generating, by a direct action application programming interface, based on the trigger keyword, an action data structure. The action data structure can be generated responsive to the request and the content provider. The method can include establishing, by a navigation component, a session with the content provider. The method can include rendering, by the navigation component, a digital component received, via the session, from the remote data processing system. The method can include selecting, by the navigation component, an interaction model associated with the remote data processing system. The method can include generating, by the navigation component, a data array based on the interaction model and the action data structure. The method can include transmitting, by the data processing system and via the interface of the data processing system, the data array to the remote data processing system.

The foregoing general description and following description of the drawings and detailed description are exemplary and explanatory and are intended to provide further explanation of the invention as claimed. Other objects, advantages, and novel features will be readily apparent to those skilled in the art from the following brief description of the drawings and detailed description.

Following below are more detailed descriptions of various concepts related to, and implementations of, methods, apparatuses, and systems of retrieving and interacting digital components in an audio-based computer network. The various concepts introduced above and discussed in greater detail below may be implemented in any of numerous ways, as the described concepts are not limited to any particular manner of implementation.

The present disclosure is generally directed systems and methods that increase the scalability of onboarding network resources, such as a digital component, to a voice or image based network. The system can include a data processing system that enables the navigating of and interaction with digital components, such as a webpage, portion thereof, or other online document using voice, image, or speech input and output interfaces on computing device. The system can receive and processes a speech input (also referred to herein as an input audio signal) to identify a digital component. The system can identify a content provider that provides the digital component. The voice input (or other non-text input such as an image input) can include verbal instructions associated with at least one resource of a defined type that can be accessed in the digital component. The resource can be, include, or correspond to an action to complete via the identified digital component or a specific item or webpage contained in or otherwise identified by the digital component. The system can create a session with the content provider hosting the digital component. The system can render the digital component received from the content provider. The system can headlessly render the digital component without a user interface. The system can analyze, using an interaction model, the rendered digital component to navigate to the resource using the interaction model. The system can select the interaction model from a first model type and a second model type. The first model type can be or include a generic model that can incorporate a first training data set that is based on a collection of websites having resources of the same type as the resource identified in the speech input. The second model type can be or include a specific model that incorporates a second training data set specific to resources of the digital component. Both of the model sets can include data for determining access to respective resources or navigating the digital component. The system can provide information related to the associated resources to the computing device for one or more subsequent operations based on the received instructions to access the respective resource. The system can also update the interaction models based on one or more determinations made when navigating the digital component to access the resource or additional resources.

The system can input data into the digital component. The data can be provided by a user and stored in a secure storage wallet on the computing device or system. The data can be provided to the system automatically during the creation of the session with the digital component or when required during the created session for one or more subsequent operations.

The system can generate the generic models by obtaining and storing information regarding one or more of terminology, layout, categories and hyperlinks that are common to accessing a respective type of resource on a plurality of different digital components. The system can generate the specific model by obtaining and storing information regarding one or more of terminology, layout, menus, categories, and hyperlinks of resources respective to the digital component identified in the speech input.

Onboarding of network resources into a voice-activated network such that other network resources can interact with the network resources can be technologically difficult because a unique interface may need to be created for each resource. For example, the owners of the resource may need to create an application program interface (API) that enables the provider of the voice-based computing device to interact with the resource. The provider of the voice-based computing device may also need to generate a program that enables the computing device to interact with the resource via the provided API. The provider of the voice-based computing device can provide the API, which the resource owner can incorporate into their digital component. This onboarding process can be time consuming, computationally inefficient and may require the cooperation of the two parties.

The onboarding process may be required to conduct a transaction with the resource, to gain access to a secure part of the resource, or exchange sensitive information. Techniques for interacting with these resources with a voice-input interface to conduct transactions and exchange data may require tight integration of the resource interface of the voice-based computing device so that a computing device can navigate through a resource using a speech command issued to the particular user interface module. Such resource specific integration that may need to be predefined between the interface module and the respective resource can be necessary to ensure that the user of the computing device is provide with a secure, fast, and seamless experience. This is because prior security configuration of how secure data is obtainable to the interface module (e.g., from a secure wallet on the computing device), as well as prior integration with the particular resource may be required so that the interface module knows the layout of the resource inputs, components, or other interaction objects.

Accordingly, interfacing with resources that have not gone through the onboarding process to establish a tight integration between the voice-based computing device and the resource may not be possible. The completion of actions with a resource using the voice-based computing device may not be possible without an integration with each and every resource.

Furthermore, the voice (or image or video) based computing device can use a number of speech recognition based interface modules. Depending on the module that a particular interface module uses, a pre-defined integration with each respective interface module may be required for each resource that the voice-based computing device could interact with.

Techniques that provide such integrations with voice-based computing device to enable navigation and interaction with a resource can suffer from the above explained drawbacks of requiring very specific and close pre-defined integration for each resource. These techniques may not be scalable and cannot be applied to all resources. For example, a website or a domain that offer the functionality to allow a speech controlled user interface module to navigate the website, may need to limit the functionality to one type of interface module rather than being able to interact with any voice input recognition module.

Accordingly, there exists a need for provision of a generic and scalable technique enabling voice-based computing devices to navigate and interact with all resources using a speech, voice, or image input recognition interface module.

The present disclosure provides the following technical steps for enabling a real time and scalable technique operable with all resources that provide products, services, or other actions. A user can initiate a command via a voice-based computing device, such as "OK, I want to obtain product X on website Y, please let me know the price and availability. " The system (e.g., a data processing system) can use natural language processing to parse and interpret the input audio signal. For example, the system can obtain a user's credentials for website Y via a secure wallet. The system can initiate a session with website Y. The server can headlessly render website Y. The system can then navigate website Y using one of a specific or generic interaction model to obtain the price and availability to product X. The price and availability can be provided to the user's computing device via an output audio file that is presented to the user via a transducer (e.g., speaker) on or associated with the computing device. The user can confirm the purchase or provide additional details to the system via a second input audio signal that the system can parse. In this example, the system enabled the user to interact with website Y without requiring any specific integration between the system and the voice-based computing device. The technique provides a method and system that can in real time interact with a website, network resource, or other digital component using trained interaction models and without the specific integration.

The techniques described herein can be generic and scalable to all types of digital component and can enable the interaction of the data processing system with the digital components without pre-integration or coordination between the digital component provider and the provider of the voice-based computing device.

The above technical solution is provided by the technical features of a server side headless rendering of respective digital components to establish a mapping between the server and the domain of the website. Using as least one trained interaction model the system can identify the structure, elements, input elements, and other components of the digital component. The above steps can occur seamlessly and automatically in real time to further provide an effective end user experience of processing the input audio signal to interact with a digital component.

<FIG> illustrates a block diagram of an example system <NUM> to select and interact with digital components via a computer network. The system <NUM> can include content selection infrastructure. The system <NUM> can include a data processing system <NUM>. The data processing system <NUM> can communicate with one or more of a content provider computing device <NUM> or client computing devices <NUM> via a network <NUM>. The network <NUM> can include computer networks such as the Internet, local, wide, metro, or other area networks, intranets, satellite networks, and other communication networks such as voice or data mobile telephone networks and combinations thereof. The network <NUM> can access information resources such as web pages, web sites, domain names, or uniform resource locators that can be presented, output, rendered, or displayed on at least one computing device <NUM>, such as a laptop, desktop, tablet, personal digital assistant, smart phone, home assistant device, portable computer(s), or speaker. For example, via the network <NUM> a user of the computing device <NUM> can access information or data provided by the content provider device <NUM>.

The data processing system <NUM> can include an interface <NUM>, a natural language processor component <NUM>, and a session handler component <NUM>. The data processing system <NUM> can also include a direction action application programming interface <NUM>, a navigation component <NUM>, and an audio signal generator component <NUM>. The data processing system <NUM> can also include a data repository <NUM> on which parameters <NUM>, policies <NUM>, interaction models <NUM>, and templates <NUM> are stored.

The network <NUM> can be used by the data processing system <NUM> to access information resources such as web pages, web sites, domain names, or uniform resource locators that can be presented, output, rendered, or displayed by the client computing device <NUM>. The web pages, web sites, and the other digital content stored or otherwise provided by the content provider device <NUM> can be referred to as digital components or content items. Via the network <NUM> a user of the client computing device <NUM> can access information or data (e.g., digital components such as content items) provided by the content provider computing device <NUM>.

The digital component can be rendered via a display device of the computing device <NUM> or can be rendered on the data processing system <NUM>. Rendering can include displaying the digital component or other content item on a display device that may or may not be part of the computing device <NUM>. In some implementations, the computing device <NUM> does not include a display device for rendering the digital component. For example, the computing device <NUM> can only render digital components by playing the digital component via a speaker of the computing device <NUM>. The data processing system <NUM> can act as an intermediary and enable the computing device <NUM> to interact with the digital component in an audio based fashion.

The network <NUM> may be any type or form of network and may include any of the following: a point-to-point network, a broadcast network, a wide area network, a local area network, a telecommunications network, a data communication network, a computer network, an ATM (Asynchronous Transfer Mode) network, a SONET (Synchronous Optical Network) network, a SDH (Synchronous Digital Hierarchy) network, a wireless network and a wireline network. The network <NUM> may include a wireless link, such as an infrared channel or satellite band. The topology of the network <NUM> may include a bus, star, or ring network topology. The network may include mobile telephone networks using any protocol or protocols used to communicate among mobile devices, including advanced mobile phone protocol ("AMPS"), time division multiple access ("TDMA"), code-division multiple access ("CDMA"), global system for mobile communication ("GSM"), general packet radio services ("GPRS") or universal mobile telecommunications system ("UMTS"). Different types of data may be transmitted via different protocols, or the same types of data may be transmitted via different protocols.

The system <NUM> can include at least one data processing system <NUM>. The data processing system <NUM> can include at least one logic device such as a computing device having a processor to communicate via the network <NUM>, for example with the computing device <NUM> or the content provider device <NUM> (content provider <NUM>). The data processing system <NUM> can include at least one computation resource, server, processor or memory. For example, the data processing system <NUM> can include a plurality of computation resources or servers located in at least one data center. The data processing system <NUM> can include multiple, logically-grouped servers and facilitate distributed computing techniques. The logical group of servers may be referred to as a data center, server farm or a machine farm. The servers can also be geographically dispersed. A data center or machine farm may be administered as a single entity, or the machine farm can include a plurality of machine farms. The servers within each machine farm can be heterogeneous - one or more of the servers or machines can operate according to one or more type of operating system platform.

Servers in the machine farm can be stored in high-density rack systems, along with associated storage systems, and located in an enterprise data center. For example, consolidating the servers in this way may improve system manageability, data security, the physical security of the system, and system performance by locating servers and high performance storage systems on localized high performance networks. Centralization of all or some of the data processing system <NUM> components, including servers and storage systems, and coupling them with advanced system management tools allows more efficient use of server resources, which saves power and processing requirements and reduces bandwidth usage.

The system <NUM> can include, access, or otherwise interact with at least one content provider device <NUM>. The content provider device <NUM> can include at least one logic device such as a computing device having a processor to communicate via the network <NUM>. The content provider device <NUM> can include at least one computation resource, server, processor or memory. For example, the content provider device <NUM> can include a plurality of computation resources or servers located in at least one data center.

The content provider computing device <NUM> can provide digital components to the data processing system <NUM> and the computing device <NUM>. The digital components can be webpages that include graphics, text, hyperlinks, and machine executable instructions. The digital components can be displayed visually to an end user, such as, via a web browser rendering the webpage and displaying the rendered webpage to the user on a display. The digital component can be or include a webpage including an offer, good, service, or information. For example, the digital component can be a website that sales clothing.

The computing device <NUM> can include, interface, or otherwise communicate with at least one sensor <NUM>, transducer <NUM>, audio driver <NUM>, or pre-processor <NUM>. The sensor <NUM> can include, for example, an ambient light sensor, proximity sensor, temperature sensor, accelerometer, gyroscope, motion detector, GPS sensor, location sensor, microphone, or touch sensor. The transducer <NUM> can include a speaker or a microphone. The audio driver <NUM> can provide a software interface to the hardware transducer <NUM>. The audio driver <NUM> can execute an audio file or other instructions provided by the data processing system <NUM> to control the transducer <NUM> to generate a corresponding acoustic wave or sound wave. The pre-processor <NUM> can be configured to detect a keyword and perform an action based on the keyword. The pre-processor <NUM> can filter out one or more terms or modify the terms prior to transmitting the terms to the data processing system <NUM> for further processing. The pre-processor <NUM> can convert the analog audio signals detected by the microphone into a digital audio signal, and transmit one or more data packets carrying the digital audio signal to the data processing system <NUM> via the network <NUM>. In some cases, the pre-processor <NUM> can transmit data packets (or other protocol based transmission) carrying some or all of the input audio signal responsive to detecting an instruction to perform such transmission, such as "OK," "start," or another wake word. The instruction can include, for example, a trigger keyword or other keyword or approval to transmit data packets comprising the input audio signal to the data processing system <NUM>. In some cases, the primary user interface of the computing device <NUM> may be a microphone and speaker.

Types of actions can include, for example, services, products, reservations, or tickets. Types of actions can further include types of services or products. For example, types of services can include car share service, food delivery service, laundry service, maid service, repair services, or household services. Types of products can include, for example, clothes, shoes, toys, electronics, computers, books, or jewelry. Types of reservations can include, for example, dinner reservations or hair salon appointments. Types of tickets can include, for example, movie tickets, sports venue tickets, or flight tickets. In some cases, the types of services, products, reservations or tickets can be categorized based on price, location, type of shipping, availability, or other attributes.

The client computing device <NUM> can be associated with an end user that enters voice queries as audio input into the client computing device <NUM> (via the sensor <NUM>) and receives audio output in the form of a computer generated voice that can be provided from the data processing system <NUM> (or the content provider computing device <NUM>) to the client computing device <NUM>, output from the transducer <NUM> (e.g., a speaker). The computer generated voice can include recordings from a real person or computer generated language. Rather than voice queries, the input can also include one or more images or video segments generated or obtained (e.g., via the network <NUM>) from the client computing device <NUM> and parsed by the data processing system <NUM> to obtain the same type of information obtained by parsing of the voice queries. For example, the user can take a picture of item they wish to purchase. The data processing system <NUM> can perform machine vision on the image to identify the contents of the image and generate a text string that identifies the contents of the image. The text string can be used as the input query.

The data processing system <NUM> can include, interface, or otherwise communicate with at least one interface <NUM> that enables the data processing system <NUM> to communicate with other devices, such as via the network <NUM>. The data processing system <NUM> can include, interface, or otherwise communicate with at least one natural language processor component <NUM>. The data processing system <NUM> can include, interface, or otherwise communicate with at least one direct action application programming interface ("API") <NUM>. The data processing system <NUM> can include, interface, or otherwise communicate with at least one session handler <NUM>. The data processing system <NUM> can include, interface, or otherwise communicate with at least navigation component <NUM>. The data processing system <NUM> can include, interface, or otherwise communicate with at least one audio signal generator <NUM>. The data processing system <NUM> can include, interface, or otherwise communicate with at least one data repository <NUM>.

The data processing system <NUM> can include, interface, or otherwise communicate with a navigation component <NUM>. The navigation component <NUM> can enable a voice-based interaction between a computing device <NUM> and a digital component, such as a website, provided by a content provider <NUM>. The digital component provided by the content provider <NUM> may not be configured to accommodate a voice-based interaction. For example, the digital component can be a webpage that includes text, images, video, input elements, and other non-audio elements. Additionally, there may be no previously established integration between the digital component (or provider thereof) and the data processing system <NUM>. The navigation component <NUM> can render the digital component, using for example, a headless browser or headless webkit renderer, and identify input elements, text, and other data in the digital component. When rendered with a headless renderer, the rendered digital component does not require a graphical user interface to function. The navigation component <NUM> can interact with those elements using an interaction model. For example, the navigation component <NUM> can input data arrays into the input fields, select and activate input elements (e.g., navigation or submission buttons), and retrieve data based on the interaction model to complete an action as identified in an input audio signal received from the computing device <NUM>. As one example, for the input audio signal "buy two shirts," the navigation component <NUM> can generate a data array of "text = <NUM>. " The navigation component <NUM> can also identify the input field and the "buy" button in the headlessly rendered webpage. The navigation component <NUM> can enter the text "<NUM>" into the input field and then select the "buy" button to complete the transaction.

The data repository <NUM> can include one or more local or distributed databases, and can include a database management system. The data repository <NUM> can include computer data storage or memory and can store one or more parameters <NUM>, one or more policies <NUM>, interaction models <NUM>, and templates <NUM> among other data. The parameters <NUM>, policies <NUM>, and templates <NUM> can include information such as rules about a voice based session between the client computing device <NUM> and the data processing system <NUM>. The data repository <NUM> can also store content data that can include content items for audio output or associated metadata, as well as input audio messages that can be part of one or more communication sessions with the client computing device <NUM>. The parameters <NUM> can include, for example, thresholds, distances, time intervals, durations, scores, or weights.

The interaction models <NUM> can be generated and updated by the navigation component <NUM>. The data repository <NUM> can include multiple interaction models. The interaction models <NUM> can be categorized into generic models and content provider specific models. The generic models can be further subdivided into different interaction or action categories. For example, the interaction models <NUM> can include a generic model for different types of commercial website, such as a shopping website, a weather provider website, and a reservation booking website.

The interaction models <NUM> can also include specific models. The specific interaction models can be specific to a content provider <NUM> or a specific digital component provided by a specific content provider <NUM>. For example, for a specific website Y, the specific interaction model can know the placement of links, menus, how to navigate the website, and how particular products and data is stored and classified within the website. The navigation component <NUM> can use this information to navigate through the website and to provide data arrays to the website when interacting with the website to complete an action or other transaction with the website.

The generic interaction models can be used when the navigation component <NUM> has not had a predetermined number of interactions with the digital component or content provider <NUM> to generate a specific interaction model. The navigation component <NUM> can train the models (both the generic and the specific interaction models), by initially collecting data from specific sessions (e.g., user sessions upon obtaining their permission or specific training sessions where a user interacts with the digital component). For example, given an input audio signal, a user can complete the task of the input audio signal (e.g., "Ok, buy a shirt. ") The navigation component <NUM> can receive the inputs made by the user in completing the action and build a model that enables the navigation component <NUM> to identify the input elements, such as text fields and buttons, that are used in completing the action. The specific models can be trained on specific digital components and the generic models can be trained using a plurality of digital component within a given category. The training can enable the model to determine interaction data such as the steps involved in purchasing a particular product, categories of products, sorting of products, and how ordering is carried out on the digital component. The models can enable the navigation component <NUM> to correctly identify and interact with the products or services that are identified in the input audio signal.

Both types of interaction models <NUM> can be trained and updated during and after sessions between the data processing system <NUM> and the content provider <NUM>. For example, while using a generic model for a digital component, the navigation component <NUM> can build a specific model for the digital component. Once the specific interaction model for the specific navigation component <NUM> is deemed to be reliable, for example by being built with the data from a predetermined number of sessions, the navigation component <NUM> can begin to use the specific interaction model for the digital component rather than the generic model. The navigation component <NUM> can use the data from additional (or new sessions) to updated the interaction models <NUM>.

The interface <NUM>, the natural language processor component <NUM>, the session handler <NUM>, the direct action API <NUM>, the navigation component <NUM>, or the audio signal generator component <NUM> can each include at least one processing unit or other logic device such as programmable logic array engine, or module configured to communicate with the database repository or database <NUM>. The interface <NUM>, the natural language processor component <NUM>, the session handler <NUM>, the direct action API <NUM>, the navigation component <NUM>, the audio signal generator component <NUM>, and the data repository <NUM> can be separate components, a single component, or part of the data processing system <NUM>. The system <NUM> and its components, such as a data processing system <NUM>, can include hardware elements, such as one or more processors, logic devices, or circuits.

The data processing system <NUM> can obtain anonymous computer network activity information associated with a plurality of computing devices <NUM>. A user of a computing device <NUM> can affirmatively authorize the data processing system <NUM> to obtain network activity information corresponding to the user's computing device <NUM>. For example, the data processing system <NUM> can prompt the user of the computing device <NUM> for consent to obtain one or more types of network activity information. The identity of the user of the computing device <NUM> can remain anonymous and the computing device <NUM> can be associated with a unique identifier (e.g., a unique identifier for the user or the computing device <NUM> provided by the data processing system <NUM> or a user of the computing device). The data processing system <NUM> can associate each observation with a corresponding unique identifier.

The data processing system <NUM> can include an interface component <NUM> designed, configured, constructed, or operational to receive and transmit information using, for example, data packets. The interface <NUM> can receive and transmit information using one or more protocols, such as a network protocol. The interface <NUM> can include a hardware interface, software interface, wired interface, or wireless interface. The interface <NUM> can facilitate translating or formatting data from one format to another format. For example, the interface <NUM> can include an application programming interface that includes definitions for communicating between various components, such as software components.

The data processing system <NUM> can receive data packets or other signal that includes or identifies an audio input signal. For example, the data processing system <NUM> can execute or run the NLP component <NUM> to receive or obtain the audio signal and parse the audio signal. For example, the NLP component <NUM> can provide for interactions between a human and a computer. The NLP component <NUM> can be configured with techniques for understanding natural language and allowing the data processing system <NUM> to derive meaning from human or natural language input. The NLP component <NUM> can include or be configured with technique based on machine learning, such as statistical machine learning. The NLP component <NUM> can utilize decision trees, statistical models, or probabilistic models to parse the input audio signal. The NLP component <NUM> can perform, for example, functions such as named entity recognition (e.g., given a stream of text, determine which items in the text map to proper names, such as people or places, and what the type of each such name is, such as person, location, or organization), natural language generation (e.g., convert information from computer databases or semantic intents into understandable human language), natural language understanding (e.g., convert text into more formal representations such as first-order logic structures that a computer module can manipulate), machine translation (e.g., automatically translate text from one human language to another), morphological segmentation (e.g., separating words into individual morphemes and identify the class of the morphemes, which can be challenging based on the complexity of the morphology or structure of the words of the language being considered), question answering (e.g., determining an answer to a human-language question, which can be specific or openended), semantic processing (e.g., processing that can occur after identifying a word and encoding its meaning in order to relate the identified word to other words with similar meanings).

The NLP component <NUM> converts the audio input signal into recognized text by comparing the input signal against a stored, representative set of audio waveforms (e.g., in the data repository <NUM>) and choosing the closest matches. The set of audio waveforms can be stored in data repository <NUM> or other database accessible to the data processing system <NUM>. The representative waveforms are generated across a large set of users, and then may be augmented with speech samples from the user. After the audio signal is converted into recognized text, the NLP component <NUM> matches the text to words that are associated, for example via training across users or through manual specification, with actions that the data processing system <NUM> can serve.

The audio input signal can be detected by the sensor <NUM> or transducer <NUM> (e.g., a microphone) of the client computing device <NUM>. Via the transducer <NUM>, the audio driver <NUM>, or other components the client computing device <NUM> can provide the audio input signal to the data processing system <NUM> (e.g., via the network <NUM>) where it can be received (e.g., by the interface <NUM>) and provided to the NLP component <NUM> or stored in the data repository <NUM>.

The NLP component <NUM> can obtain the input audio signal. From the input audio signal, the NLP component <NUM> can identify at least one request or at least one trigger keyword corresponding to the request. The request can indicate intent or subject matter of the input audio signal. The trigger keyword can indicate a type of action likely to be taken. For example, the NLP component <NUM> can parse the input audio signal to identify at least one request to leave home for the evening to attend dinner and a movie. The trigger keyword can include at least one word, phrase, root or partial word, or derivative indicating an action to be taken. For example, the trigger keyword "go" or "to go to" from the input audio signal can indicate a need for transport. In this example, the input audio signal (or the identified request) does not directly express an intent for transport, however the trigger keyword indicates that transport is an ancillary action to at least one other action that is indicated by the request.

The NLP component <NUM> can parse the input audio signal to identify, determine, retrieve, or otherwise obtain the request and the trigger keyword. For instance, the NLP component <NUM> can apply a semantic processing technique to the input audio signal to identify the trigger keyword or the request. The NLP component <NUM> can apply the semantic processing technique to the input audio signal to identify a trigger phrase that includes one or more trigger keywords, such as a first trigger keyword and a second trigger keyword. For example, the input audio signal can include the sentence "I need someone to do my laundry and my dry cleaning. " The NLP component <NUM> can apply a semantic processing technique, or other natural language processing technique, to the data packets comprising the sentence to identify trigger phrases "do my laundry" and "do my dry cleaning". The NLP component <NUM> can further identify multiple trigger keywords, such as laundry, and dry cleaning. For example, the NLP component <NUM> can determine that the trigger phrase includes the trigger keyword and a second trigger keyword.

The NLP component <NUM> can parse the input audio signal to identify, determine, retrieve, or otherwise obtain an identification of a remote content provider <NUM> or remote data processing system <NUM> in a method similar to the method the NLP component <NUM> uses to obtain the request and trigger keyword. For example, the input audio signal including the phrase "ok, buy a red shirt from ABC" can be parsed to identify ABC as a seller of shirts. The data processing system <NUM> can then determine a content provider <NUM> associated with ABC. The content provider <NUM> can be a server that hosts ABC's website. The data processing system <NUM> can identify a web address of ABC, such as "www. " The data processing system <NUM> can transmit a confirmation audio signal to the computing device <NUM>, such as "Are you referring to ABC of www. com?" Responsive to receiving a confirmation message from the computing device <NUM>, the data processing system <NUM> can initiate a session with the content provider <NUM> located at www.

The NLP component <NUM> can filter the input audio signal to identify the trigger keyword. For example, the data packets carrying the input audio signal can include "It would be great if I could get someone that could help me go to the airport", in which case the NLP component <NUM> can filter out one or more terms as follows: "it", "would", "be", "great", "if", "I", "could", "get", "someone", "that", "could", or "help". By filtering out these terms, the NLP component <NUM> may more accurately and reliably identify the trigger keywords, such as "go to the airport" and determine that this is a request for a taxi or a ride sharing service.

The data processing system <NUM> can include a direct action API <NUM> designed and constructed to generate, based on the trigger keyword, an action data structure responsive to the request and the identified remote content provider <NUM>. Processors of the data processing system <NUM> can invoke the direct action API <NUM> to execute scripts that generate a data structure to the content provider <NUM> request or order a service or product, such as a car from a car share service. The direct action API <NUM> can obtain data from the data repository <NUM>, as well as data received with end user consent from the client computing device <NUM> to determine location, time, user accounts, logistical or other information to allow the data processing system <NUM> to perform an operation, such as reserve a car from the car share service.

The direct action API <NUM> can execute a specified action to satisfy the end user's intention when the data processing system <NUM> interacts with the digital component from the content provider device <NUM>. Depending on the action specified in its inputs, the direct action API <NUM> can execute code or a dialog script that identifies the parameters required to fulfill a user request, which can be included into an action data structure. Such code can look-up additional information or it can provide audio output for rendering at the client computing device <NUM> to ask the end user questions such as the user's preferred shirt size, to continue the above example where the input audio signal is "ok, by a red shirt. " The direct action API <NUM> can determine necessary parameters and can package the information into an action data structure. For example, when the input audio signal is "ok, buy a red shirt," that action data structure can include the user's preferred shirt size.

The direct action API <NUM>, upon identifying the type of request, can access the corresponding template from a template repository stored in the data repository <NUM>. The templates <NUM> can include fields in a structured data set that can be populated by the direct action API <NUM> to further the operation of fulfilling or interacting with the digital component provided by the content provider <NUM>. The direct action API <NUM> can perform a lookup in the template repository to select the template that matches one or more characteristic of the trigger keyword and request. For example, if the request corresponds to a request for a car or ride to a destination, the data processing system <NUM> can select a car sharing service template. The car sharing service template can include one or more of the following fields: device identifier, pick up location, destination location, number of passengers, or type of service. The direct action API <NUM> can populate the fields with values. To populate the fields with values, the direct action API <NUM> can ping, poll or otherwise obtain information from one or more sensors <NUM> of the computing device <NUM> or a user interface of the computing device <NUM>. For example, the direct action API <NUM> can detect the source location using a location sensor, such as a GPS sensor. The direct action API <NUM> can obtain further information by submitting a survey, prompt, or query to the end of user of the computing device <NUM>. The direct action api <NUM> can submit the survey, prompt, or query via interface <NUM> of the data processing system <NUM> and a user interface of the computing device <NUM> (e.g., audio interface, voice-based user interface, display, or touch screen). Thus, the direct action API <NUM> can select a template for the action data structure based on the trigger keyword or the request, populate one or more fields in the template with information detected by one or more sensors <NUM> or obtained via a user interface, and generate, create or otherwise construct the action data structure to facilitate performance of an operation by the content provider <NUM>.

The data processing system <NUM> can select the template based from the template data structure based on various factors including, for example, one or more of the trigger keyword, request, type of content provider <NUM>, a category that the content provider <NUM> (e.g., taxi service, laundry service, flower service, retail service, or food delivery), location, or other sensor information.

To select the template based on the trigger keyword, the data processing system <NUM> (e.g., via direct action API <NUM>) can perform a look-up or other query operation on the template database using the trigger keyword to identify a template data structure that maps or otherwise corresponds to the trigger keyword. For example, each template in the template database can be associated with one or more trigger keywords to indicate that the template is configured to generate an action data structure responsive to the trigger keyword that the data processing system <NUM> can process to establish a communication session between the data processing system <NUM> and the content provider <NUM>.

To construct or generate the action data structure, the data processing system <NUM> can identify one or more fields in the selected template to populate with values. The fields can be populated with numerical values, character strings, Unicode values, Boolean logic, binary values, hexadecimal values, identifiers, location coordinates, geographic areas, timestamps, or other values. The fields or the data structure itself can be encrypted or masked to maintain data security.

Upon determining the fields in the template, the data processing system <NUM> can identify the values for the fields to populate the fields of the template to create the action data structure. The data processing system <NUM> can obtain, retrieve, determine or otherwise identify the values for the fields by performing a look-up or other query operation on the data repository <NUM>.

In some cases, the data processing system <NUM> can determine that the information or values for the fields are absent from the data repository <NUM>. The data processing system <NUM> can determine that the information or values stored in the data repository <NUM> are out-of-date, stale, or otherwise not suitable for the purpose of constructing the action data structure responsive to the trigger keyword and request identified by the NLP component <NUM> (e.g., the location of the client computing device <NUM> may be the old location and not be the current location; an account can be expired; the destination restaurant may have moved to a new location; physical activity information; or mode of transportation).

If the data processing system <NUM> determines that it does not currently have access, in memory of the data processing system <NUM>, to the values or information for the field of the template, the data processing system <NUM> can acquire the values or information. The data processing system <NUM> can acquire or obtain the information by querying or polling one or more available sensors of the client computing device <NUM>, prompting the end user of the client computing device <NUM> for the information, or accessing an online web-based resource using an HTTP protocol. For example, the data processing system <NUM> can determine that it does not have the current location of the client computing device <NUM>, which may be a needed field of the template. The data processing system <NUM> can query the client computing device <NUM> for the location information. The data processing system <NUM> can request the client computing device <NUM> to provide the location information using one or more location sensors <NUM>, such as a Global Positioning System sensor, WIFI triangulation, cell tower triangulation, Bluetooth beacons, IP address, or other location sensing technique.

In some cases, the data processing system <NUM> can identify a remote content provider <NUM> with which to establish a session based on the trigger keyword or request. To identify the content provider <NUM> based on the trigger keyword, the data processing system <NUM> can perform a lookup in the data repository <NUM> to identify a content provider <NUM> that maps to the trigger keyword. For example, if the trigger keyword includes "ride" or "to go to", then the data processing system <NUM> (e.g., via direct action API <NUM>) can identify a content provider <NUM> (or web address thereof) corresponding to Taxi Service Company A. The data processing system <NUM> can select the template from the template database based on the identified content provider <NUM>. The data processing system <NUM> can identify the content provider <NUM> by conducting an internet based search.

The data processing system <NUM> can include, execute, access, or otherwise communicate with a session handler component <NUM> to establish a communication session between with the computing device <NUM> and the data processing system <NUM>. The communication session can also refer to one or more data transmissions between the data processing system <NUM> and the content provider <NUM>. The communication session between the computing device <NUM> and the data processing system <NUM> can include the transmission of the input audio signal that is detected by a sensor <NUM> of the computing device <NUM>, and the output signal transmitted by the data processing system <NUM> to the computing device <NUM>. The data processing system <NUM> (e.g., via the session handler component <NUM>) can establish the communication session responsive to receiving the input audio signal. The data processing system <NUM> can set a duration for the communication session. The data processing system <NUM> can set a timer or a counter for the duration set for the communication session. Responsive to expiration of the timer, the data processing system <NUM> can terminate the communication session. The communication session between the data processing system <NUM> and the content provider <NUM> can include the transmission of the digital component from the content provider <NUM> to the data processing system <NUM>. The communication session between the data processing system <NUM> and the content provider <NUM> can also include the transmission of data arrays to the content provider <NUM>. The communication session can refer to a network-based communication session in which data (e.g., digital components, authenticating information, credentials, etc.) is transmitted between the data processing system <NUM> and the content provider <NUM> and the data processing system <NUM> and the computing device <NUM>.

The data processing system <NUM> can include, execute, or communicate with an audio signal generator component <NUM> to generate an output signal. The output signal can include one or more portions. The output signal can include content identified from the digital component received from the content provider <NUM>.

The audio signal generator component <NUM> can generate the output signal with a first portion having sound corresponding to the first data structure. For example, the audio signal generator component <NUM> can generate the first portion of the output signal based on one or more values populated into the fields of the action data structure by the direct action API <NUM>. In a taxi service example, the values for the fields can include, for example, <NUM> Main Street for pick-up location, <NUM> Main Street for destination location, <NUM> for number of passengers, and economy for the level of service.

The data processing system <NUM> (e.g., via interface <NUM> and network <NUM>) can transmit data packets comprising the output signal generated by the audio signal generator component <NUM>. The output signal can cause the audio driver component <NUM> of or executed by the computing device <NUM> to drive a speaker (e.g., transducer <NUM>) of the computing device <NUM> to generate an acoustic wave corresponding to the output.

The content provider <NUM> can provide websites, goods, or services (all generally referred to as digital components) to the computing devices <NUM> and the data processing system <NUM>. The services and goods can be services and goods that are provided physically (e.g., clothing, car services, other consumables, etc.) and are associated with a digital component. For example, the digital component for a car service can be a website through which the user schedules the car service. The digital component associated with the service or goods can be digital components that are used in the purchase, initiation, setup of the good or services, or other transactions related to the goods and services.

The content provider <NUM> can include one or more keywords in the digital components. The keywords can be in meta tags, header strings, the body of the digital component, and links. After receiving the digital component, the navigation component <NUM> can analyze the keywords to categorize the digital component (or content provider <NUM> associated with the digital component) into different categories. For example, the digital component can be categorized into a news, retail, etc. category that identifies the general subject matter of the digital component. The navigation component <NUM> can select an interaction model from the interaction models <NUM> at least partially based on the category of the digital component.

The digital component can be rendered via a display device of the computing device <NUM> or can be rendered on the data processing system <NUM>. Rendering can include displaying the content item on a display device. In some implementations, the computing device <NUM> does not include a display device for rendering the digital component. For example, the computing device <NUM> can only render digital components by playing the digital component via a speaker of the computing device <NUM>. The data processing system <NUM> can act as an intermediary and enable the computing device <NUM> to interact with the digital component in an audio based fashion. The computing device <NUM> can include an application, script or program, installed at the client computing device <NUM>, such as an app to communicate input audio signals to the interface <NUM> of the data processing system <NUM>. The application can also drive components of the computing device <NUM> to render output audio signals.

<FIG> illustrates a block diagram of an example method <NUM> to retrieve and interact with digital components in a voice activated, data packet (or other protocol) based computer network. <FIG> illustrates a block diagram of an example data flow through the system illustrated in <FIG> during the course of the method <NUM> illustrated in <FIG>. The method <NUM> includes receiving an input audio signal (ACT <NUM>). The method <NUM> includes parsing the input audio signal to identify a request, a content provider, and a trigger keyword (ACT <NUM>). The method <NUM> includes generating an action data structure (ACT <NUM>). The method <NUM> includes establishing a session with the content provider (ACT <NUM>). The method <NUM> includes rendering a received digital component (ACT <NUM>). The method <NUM> includes selecting an interaction model (ACT <NUM>). The method <NUM> includes generating a data array based on the interaction model (ACT <NUM>). The method <NUM> includes transmitting the data array to the content provider (ACT <NUM>).

As set forth above, and referring to <FIG>, the method <NUM> includes receiving an input audio signal (ACT <NUM>). The data processing system <NUM> can receive the input audio signal <NUM> from the computing device <NUM>. The input audio signal <NUM> can be received by the data processing system <NUM> via a nlp component <NUM> over a network. The NLP can be executed by the data processing system <NUM>. The data processing system <NUM> can receive the input audio signal <NUM> as data packets that include the input audio signal. The input audio signal can be detected by a sensor, such as a microphone, of the computing device <NUM>.

The method <NUM> includes parsing the input audio signal to identify a request, a content provider, and a trigger keyword (ACT <NUM>). The input audio signal can be parsed by the natural language processor component <NUM>. For example, the audio signal detected by the computing device <NUM> can include "Okay device, I want a shirt from ABC Co. " In this input audio signal, the initial trigger keyword can include "okay device", which can indicate to the computing device <NUM> to transmit an input audio signal to the data processing system <NUM>. A pre-processor of the computing device <NUM> can filter out the terms "okay device" prior to sending the remaining audio signal to the data processing system <NUM>. In some cases, the computing device <NUM> can filter out additional terms or generate keywords to transmit to the data processing system <NUM> for further processing.

The data processing system <NUM> identifies a trigger keyword in the input audio signal <NUM>. The trigger keyword, which can be a phrase, can include, in the above example, "I want a shirt. " The trigger keyword can indicate a type of service or product (e.g., the shirt) and an action to take. The data processing system <NUM> can identify a request in the input audio signal. The request can be determined based on the terms "I want". The trigger keyword and request can be determined using a semantic processing technique or other natural language processing technique. The data processing system <NUM> can identify the content provider <NUM> as ABC Co. The data processing system <NUM> can identify a website, IP address, or other network location of the content provider <NUM> associated with the content provider <NUM>, ABC Co.

The method <NUM> includes generating an action data structure (ACT <NUM>). The direct action application programming interface can generate the action data structure based on the trigger keyword. The action data structure can also be generated responsive to the request and the identified content provider <NUM>. The action data structure can be generated from or based on a template. The template can be selected based on the trigger keywords and the identified content provider <NUM>. The generated action data structure can include information and data related to completing the action associated with the trigger keyword. For example, for "I want a shirt from ABC Co. " the template may indicate the needed information related to the purchase of shirt can include size, preferred color, preferred style, and preferred price range. The data processing system <NUM> can populate the fields in the action data structure with values retrieved from the memory or based on responses by the user to output signals transmitted from the data processing system <NUM> to the computing device <NUM>. The data processing system <NUM> can populate the secure fields such as user credentials from a secure wallet that can be stored on the data processing system <NUM> or the computing device <NUM>. The data processing system <NUM> can request permission from the user to access the secure wallet before obtaining information from the secure wallet.

The method <NUM> includes establishing a session with the content provider (ACT <NUM>). The data processing system <NUM> can establish a communication session <NUM> with the content provider <NUM> responsive to identifying the content provider <NUM> in the input audio signal. The communication session <NUM> can be established to receive a digital component from the content provider <NUM>. The session can be established using the hypertext transfer protocol. The session can be established with a request <NUM> from the data processing system <NUM> to the content provider <NUM>. The request <NUM> can be for a webpage transmitted in the response <NUM> to the request <NUM>.

The method <NUM> includes rendering a received digital component (ACT <NUM>). The received digital component can be rendered by the navigation component <NUM> of the data processing system <NUM>. <FIG> illustrates a partial rendering <NUM> of the digital component. Continuing the above example, the digital component can be received in response to the input audio signal "I want a shirt from ABC Co. " The rendered digital component <NUM> can include input fields <NUM>, buttons <NUM>, menus, image fields <NUM>, images <NUM>, and text <NUM> (generally referred to as the components or elements of the digital component). Buttons, links, input fields, and radio buttons can generally be referred to as input elements. The digital component is rendered without a graphical user interface. For example, the digital component <NUM> can be an HTML document that is rendered by a headless browser. The headless browser of the navigation component <NUM> can include a layout engine that can render the code of a digital component <NUM>, such as the HTML and JavaScript within the digital component. The navigation component <NUM>, when rendering the digital component in a headless fashion, renders the digital component <NUM> to an image file that is analyzed with a machine vision component of the navigation component <NUM>.

The method <NUM> includes selecting an interaction model (ACT <NUM>). The navigation component <NUM> selects an interaction model that is associated with the content provider <NUM>. The navigation component <NUM> can select between two general types of interaction models. The first model can be a generic model that may be the same for each content provider <NUM> associated with a particular category. For example, the data processing system <NUM> may include a generic model for shopping websites; a generic model for insurance websites; a generic model for hotel booking websites; and a generic model for food delivery websites. The second type of model can be specific to the content provider <NUM> (or the digital component received from the content provider <NUM>).

In addition, a second model that is a specific data model may also be used. For example, the model can be specific to ABC Co. Specific or special features such as placement of links to access products, specific menus and how to navigate through them, how particular products are stored and classified within a website may be information that is include in the specific model. The navigation component <NUM> can use the model to interpret the digital component <NUM>. The navigation component <NUM> can generate the specific interaction model after a predetermined number of sessions are established between the data processing system <NUM> and the content provider <NUM>. For example, initially the data processing system <NUM> can use a generic model when interacting with a given content provider <NUM>. Data from the interactions can be used to build the specific interaction model. Once the data processing system <NUM> has initiated a predetermined number of sessions and added the session data to the specific model for the content provider <NUM>, the data processing system <NUM> can begin using the specific interaction model for the content provider <NUM>. While the number of previously established sessions is below the predetermined number, the data processing system <NUM> can continue to use the generic interaction model when interacting with the content provider <NUM>.

Using the selected model, the navigation component <NUM> identifies the input fields <NUM>, buttons <NUM>, menus, image fields <NUM>, images <NUM>, and text <NUM> of the digital component <NUM> by performing a machine vision analysis of the saved image file of the digital component <NUM>. The navigation component <NUM> can also identify the components of the digital component <NUM> by parsing the code of the digital component <NUM>. For example, navigation component <NUM> can identify HTML tags within the digital component <NUM>. As one example, the navigation component <NUM> can search for the HTML tags <input> or <form> to identify the input field <NUM>.

When the navigation component <NUM> identifies an image or button, the navigation component <NUM> can perform machine vision analysis on the image or butter to determine one or more characteristics of the image or button. The characteristics can include a determination of colors within the image (e.g., that the shirt illustrated in image <NUM> is a red shirt), identification of objects in the image (e.g., that image <NUM> illustrates a shirt), or text or icons within the image or button (e.g., that button <NUM> includes an arrow indicating "next" or if the button <NUM> included the text "next").

The method <NUM> includes generating a data array based on the interaction model (ACT <NUM>). The data array is generated by the navigation component <NUM> based on information identified in the digital component <NUM> using the interaction model. The data array can be generated using information from the action data structure. For example, using the interaction model, the navigation component <NUM> can determine the text <NUM> states "size" and is associated with the input field <NUM>. The action data structure can include an entry of "medium" in the field "size. " The navigation component <NUM> can include "medium" in the data array and input the data array into the input field <NUM> to indicate that a shirt of medium size should be selected.

The method <NUM> includes transmitting the data array to the content provider (ACT <NUM>). The data array <NUM> can be input into the input field <NUM>. The data array <NUM> can be transmitted to the content provider <NUM> responsive to the navigation component <NUM> selecting another input field, such as the button <NUM>. The data array <NUM> can be transmitted to the content provider <NUM> responsive to a HTTP POST or GET method. The data processing system <NUM> continues to interact with the digital component to complete the action identified in the input audio signal. For example, in the example illustrated in <FIG>, the data processing system <NUM> can repeat ACTs of method <NUM> to select the shirt, checkout or purchase the shirt, and then send a confirmation to the client computing device <NUM>.

The data processing system <NUM> establishes a communication session <NUM> between the data processing system <NUM> and the computing device <NUM>. The communication session <NUM> can be established by a conversational application programming interface. The communication session <NUM> can be a real-time, back-and-forth voice or audio based conversation session. The data processing system <NUM> can establish the communication session <NUM> with the computing device <NUM> to retrieve additional information for the action data structure or the data array. For example, the data processing system <NUM> can transmit an output audio signal <NUM> with instructions that cause the transducer of the computing device <NUM> to generate a sound wave of "What is your preferred color. " The user can provide a second input audio signal <NUM> in response to the output audio signal <NUM>. The natural language processor component <NUM> can process the second input audio signal <NUM> to identify the user's response, which in this example can be "red. " The navigation component <NUM> can generate a second data array <NUM> based on the interaction model and the response identified in the second input audio signal <NUM>. The second data array <NUM> can be transmitted to the content provider <NUM>.

The data processing system <NUM> can establish a communication session with a second computing device <NUM> that is associated with the user of the first computing device <NUM> that originally transmitted the input audio signal. For example, the first computing device <NUM> can be a voice-based digital assistant speaker system and the second computing device <NUM> can be the user's smart phone. The data processing system <NUM> can request additional information or confirmation from the user via the second computing device <NUM>. For example, in the example illustrated in <FIG>, the data processing system <NUM> can provide two images of selected shirts to the user's smart phone and request that the user select one of the two shirts. Prior to completing a purchase or making a reservation the data processing system <NUM> can request a verbal confirmation via the first computing device <NUM> or a confirmation via the second computing device <NUM> (e.g., the selection of a "buy" button).

The computer system or computing device <NUM> can include or be used to implement the system <NUM>, or its components such as the data processing system <NUM>. The data processing system <NUM> can include an intelligent personal assistant or voice-based digital assistant. The computing system <NUM> includes a bus <NUM> or other communication component for communicating information and a processor <NUM> or processing circuit coupled to the bus <NUM> for processing information. The computing system <NUM> can also include one or more processors <NUM> or processing circuits coupled to the bus for processing information. The computing system <NUM> also includes main memory <NUM>, such as a random access memory (RAM) or other dynamic storage device, coupled to the bus <NUM> for storing information, and instructions to be executed by the processor <NUM>. The main memory <NUM> can be or include the data repository <NUM>. The main memory <NUM> can also be used for storing position information, temporary variables, or other intermediate information during execution of instructions by the processor <NUM>. The computing system <NUM> may further include a read only memory (ROM) <NUM> or other static storage device coupled to the bus <NUM> for storing static information and instructions for the processor <NUM>. A storage device <NUM>, such as a solid state device, magnetic disk or optical disk, can be coupled to the bus <NUM> to persistently store information and instructions. The storage device <NUM> can include or be part of the data repository <NUM>.

The computing system <NUM> may be coupled via the bus <NUM> to a display <NUM>, such as a liquid crystal display, or active matrix display, for displaying information to a user. An input device <NUM>, such as a keyboard including alphanumeric and other keys, may be coupled to the bus <NUM> for communicating information and command selections to the processor <NUM>. The input device <NUM> can include a touch screen display <NUM>. The input device <NUM> can also include a cursor control, such as a mouse, a trackball, or cursor direction keys, for communicating direction information and command selections to the processor <NUM> and for controlling cursor movement on the display <NUM>. The display <NUM> can be part of the data processing system <NUM>, the client computing device <NUM> or other component of <FIG>, for example.

One or more processors in a multi-processing arrangement may also be employed to execute the instructions contained in main memory <NUM>.

For situations in which the systems discussed herein collect personal information about users, or may make use of personal information, the users may be provided with an opportunity to control whether programs or features that may collect personal information (e.g., information about a user's social network, social actions or activities, a user's preferences, or a user's location), or to control whether or how to receive content from a content server or other data processing system that may be more relevant to the user. In addition, certain data may be anonymized in one or more ways before it is stored or used, so that personally identifiable information is removed when generating parameters. For example, a user's identity may be anonymized so that no personally identifiable information can be determined for the user, or a user's geographic location may be generalized where location information is obtained (such as to a city, postal code, or state level), so that a particular location of a user cannot be determined. Thus, the user may have control over how information is collected about him or her and used by the content server.

The subject matter and the operations described in this specification can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them. The subject matter described in this specification can be implemented as one or more computer programs, e.g., one or more circuits of computer program instructions, encoded on one or more computer storage media for execution by, or to control the operation of, data processing apparatuses. Alternatively or in addition, the program instructions can be encoded on an artificially generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information for transmission to suitable receiver apparatus for execution by a data processing apparatus. While a computer storage medium is not a propagated signal, a computer storage medium can be a source or destination of computer program instructions encoded in an artificially generated propagated signal. The computer storage medium can also be, or be included in, one or more separate components or media (e.g., multiple CDs, disks, or other storage devices).

The terms "data processing system," "computing device <NUM>," "component," or "data processing apparatus" encompass various apparatuses, devices, and machines for processing data, including by way of example a programmable processor, a computer, a system on a chip, or multiple ones, or combinations of the foregoing. For example, the direct action API <NUM>, the NLP component <NUM>, and other data processing system <NUM> components can include or share one or more data processing apparatuses, systems, computing devices, or processors.

A computer program (also known as a program, software, software application, app, script, or code) can be written in any form of programming language, including compiled or interpreted languages, declarative or procedural languages, and can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program can correspond to a file in a file system. A computer program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub programs, or portions of code).

The processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs (e.g., components of the data processing system <NUM>) to perform actions by operating on input data and generating output. The processes and logic flows can also be performed by, and apparatuses can also be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit). Devices suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto optical disks; and CD ROM and DVD-ROM disks.

The subject matter described herein can be implemented in a computing system that includes a back end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front end component, e.g., a client computer having a graphical user interface or a web browser through which a user can interact with the computer system <NUM> or other elements described herein, or a combination of one or more such back end, middleware, or front end components.

The computing system such as system <NUM> can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network (e.g., the network <NUM>). A server can transmit data (e.g., data packets representing a content item) to a computing device <NUM> (e.g., for purposes of displaying data to and receiving user input from a user interacting with the computing device <NUM>). Data generated at the computing device <NUM> (e.g., a result of the user interaction) can be received from the computing device <NUM> at the server (e.g., received by the data processing system <NUM> from the computing device <NUM> or content provider <NUM>).

The separation of various system components does not require separation in all implementations, and the described program components can be included in a single hardware or software product. For example, the NLP component <NUM> can be a single component, app, or program, or a logic device having one or more processing circuits, or part of one or more servers of the data processing system <NUM>.

Having now described some illustrative implementations, it is apparent that the foregoing is illustrative and not limiting, having been presented by way of example. In particular, although many of the examples presented herein involve specific combinations of method acts or system elements, those acts and those elements may be combined in other ways to accomplish the same objectives. Acts, elements and features discussed in connection with one implementation are not intended to be excluded from a similar role in other implementations or implementations.

Any implementation disclosed herein may be combined with any other implementation or embodiment, and references to "an implementation," "some implementations," "one implementation" or the like are not necessarily mutually exclusive and are intended to indicate that a particular feature, structure, or characteristic described in connection with the implementation may be included in at least one implementation or embodiment. Such terms as used herein are not necessarily all referring to the same implementation. Any implementation may be combined with any other implementation, inclusively or exclusively, in any manner consistent with the aspects and implementations disclosed herein.

References to "or" may be construed as inclusive so that any terms described using "or" may indicate any of a single, more than one, and all of the described terms. For example, a reference to "at least one of 'A' and 'B'" can include only 'A', only 'B', as well as both 'A' and 'B'. Such references used in conjunction with "comprising" or other open terminology can include additional items.

Claim 1:
A system (<NUM>) to retrieve digital components in a voice activated data packet based computer network environment, comprising:
a natural language processor component (<NUM>) executed by a data processing system (<NUM>) to receive, via an interface (<NUM>) of the data processing system, data packets comprising an input audio signal (<NUM>) detected by a sensor (<NUM>) of a computing device (<NUM>);
the natural language processor component to parse the input audio signal to identify a request, a content provider (<NUM>), and a trigger keyword corresponding to the request;
a direct action application programming interface (<NUM>) of the data processing system to generate, based on the trigger keyword, an action data structure responsive to the request and the content provider;
a navigation component (<NUM>) of the data processing system to:
establish a session with the content provider;
render, without a graphical user interface, a digital component received, via the session, from the content provider, to an image file for analysis with a machine vision component of the navigation component;
select an interaction model (<NUM>) associated with the content provider;
identify using the selected interaction model one or more of input fields (<NUM>), buttons (<NUM>), menus, image fields (<NUM>), images (<NUM>), or text (<NUM>) of the digital component by performing a machine vision analysis of the image file;
and
generate a data array (<NUM>) based on the information identified in the digital component using the interaction model and the action data structure; and
the data processing system to transmit, via the interface of the data processing system, the data array to the content provider to interact with the digital component to complete the request.