Microsoft Technology Licensing, LLC

Apple Inc.

Tellme Networks, Inc.

Madhusudan Chinthakunta

Lisa Joy Stifelman

Larry Paul Heck

David Mitby

Rao Subrahmanyeswara Surapaneni

Gary Clayton

Marcel Van Os

Thomas R Gruber

Timothy S Paek

Lauren Elise Tappana

Ron C Santos

Mohammed A Tayyeb

Ping Wen Ong

Dilek Zeynep Hakkani-Tur

Julian James Odell

Daniel R Dole

Melvyn J Hunt

Tuomo J Raitio

Hywel B Richards

Systems and processes for integrating a digital assistant with telephony are provided. For example, an incoming call may be received, from a caller, at an electronic device. A communication session may be established between the caller and the digital assistant of the electronic device. In accordance with a determination that the identification of the caller is unknown, determination is made whether the caller corresponds to an automated calling system. In accordance with a determination that the identification of the caller is known, a response is provided by the digital assistant to the caller. An output including information corresponding to the communication is provided at the electronic device.

Digital assistant integration with telephony

Systems and processes for operating an intelligent automated assistant to perform intelligent list reading are provided. In accordance with one example, a method includes, at an electronic device having one or more processors, receiving a first user input of a first input type, the first user input including a plurality of words; displaying, on the touch-sensitive display, the plurality of words; receiving a second user input of a second input type indicating a selection of a word of the plurality of words, the second input type different than the first input type; receiving a third user input; modifying the selected word based on the third user input to provide a modified one or more words; and displaying, on the touch-sensitive display, the modified one or more words.

Multi-modal interfaces having selection disambiguation and text modification capability

Multi-modal interfaces

An augmented conversational understanding architecture may be provided. Upon receiving a natural language phrase from a user, the phrase may be translated into a search phrase and a search action may be performed on the search phrase.

Augmented conversational understanding architecture

Identification of user intents may be provided. A plurality of network applications may be identified, and an ontology associated with each of the plurality of applications may be defined. If a phrase received from a user is associated with at least one of the defined ontologies, an action associated with the network application may be executed.

Task driven user intents

Individuals may utilize devices to engage in conversations about topics respectively associated with a location (e.g., restaurants where the individuals may meet for dinner). Often, the individual momentarily withdraws from the conversation in order to issue commands to the device to retrieve and present such information, and may miss parts of the conversation while interacting with the device. Additionally, the individual often explores such topics individually on a device and conveys such information to the other individuals through messages, which is inefficient and error-prone. Presented herein are techniques enabling devices to facilitate conversations by monitoring the conversation for references, by one individual to another (rather than as a command to the device), to a topic associated with a location. In the absence of a command from an individual, the device may automatically present a map alongside a conversation interface showing the location(s) of the topic(s) referenced in the conversation.

Facilitating conversations with automated location mapping

An augmented conversational understanding agent may be provided. Upon receiving, by an agent, at least one natural language phrase from a user, a context associated with the at least one natural language phrase may be identified. The natural language phrase may be associated, for example, with a conversation between the user and a second user. An agent action associated with the identified context may be performed according to the at least one natural language phrase and 201 a result associated with performing the action may be displayed.

Augmented conversational understanding agent to identify conversation context between two humans and taking an agent action thereof

Systems and processes for detecting and/or providing a whispered speech response are provided. In one example process, speech is received from a user, and based on the speech input, determined that a whispered speech response is to be provided. Upon determining that a whispered speech response is to be provided, the whispered speech response is generated and provided to the user.

Digital assistant providing whispered speech

Location-based conversational understanding may be provided. Upon receiving a query from a user, an environmental context associated with the query may be generated. The query may be interpreted according to the environmental context. The interpreted query may be executed and at least one result associated with the query may be provided to the user.

Location-based conversational understanding

Personalization of user interactions may be provided. Upon receiving a phrase from a user, a plurality of semantic concepts associated with the user may be loaded. If the phrase is determined to comprise at least one of the plurality of semantic concepts associated with the user, a first action may be performed according to the phrase. If the phrase is determined not to comprise at least one of the plurality of semantic concepts associated with the user, a second action may be performed according to the phrase.

Personalization of queries, conversations, and searches

A wizard control panel may be used by a human wizard to adjust the operation of a Natural Language (NL) conversational system during a real-time dialog flow. Input to the wizard control panel is detected and used to interrupt/change an automatic operation of one or more of the NL conversational system components used during the flow. For example, the wizard control panel may be used to adjust results determined by an Automated Speech Recognition (ASR) component, a Natural Language Understanding (NLU) component, a Dialog Manager (DM) component, and a Natural Language Generation (NLG) before the results are used to perform an automatic operation within the flow. A timeout may also be set such that when the timeout expires, the conversational system performs an automated operation by using the results shown in the wizard control panel (edited/not edited).

Using human wizards in a conversational understanding system

An augmented conversational understanding agent may be provided. Upon receiving, by an agent, at least one natural language phrase from a user, a context associated with the at least one natural language phrase may be identified. The natural language phrase may be associated, for example, with a conversation between the user and a second user. An agent action associated with the identified context may be performed according to the at least one natural language phrase and a result associated with performing the action may be displayed, wherein the agent action comprises providing a list of movies, a list of night clubs, a search for restaurants, or other action suggestions.

A user interaction activation may be provided. A plurality of signals received from a user may be evaluated to determine whether the plurality of signals are associated with a visual display. If so, the plurality of signals may be translated into an agent action and a context associated with the visual display may be retrieved. The agent action may be performed according to the retrieved context and a result associated with the performed agent action may be displayed to the user.

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Saratoga, CA, United States of America

Madhusudan Chinthakunta