A system and method for providing gesture-based and video-based query feedback received from a user utilizes a system having a video display device, a microphone, a memory having instructions stored thereon, and a processor configured to execute the instructions on the memory to cause the system to perform a method. The processor executing instructions cause the system to select a first set of gestures for use when interacting with the user, determine whether the user understands the first set of gestures, and when the user understands the first set of gestures, processor executing additional instructions to further cause the system to output one or more feedback queries as query audio or video data to the user, capture one or more input gestures as video data in response to the one or more feedback queries, identify the one or more response gestures within the video data, and when the one or more gestures identified within the video data are recognized as corresponding to one or more gestures from the first set of gestures, record a query response corresponding to the recognized one or more gestures as a feedback response to the one or more feedback queries.

Examples described herein relate to music discovery. In one aspect, a method is provided that involves (a) receiving by a computing device an indication of a search tool from among a plurality of search tools, where each search tool of the plurality of search tools is associated with at least one respective media service, (b) receiving by the computing device an indication of a media characteristic, where the computing device receives the media characteristic via the indicated search tool, (c) selecting by the computing device one or more of the at least one respective media service that maintains media associate with the indicated media characteristic, and (d) sending by the computing device an indication of the selected one or more of the at least one respective media service.

Systems and methods for dynamically responding to requests for information, derived from one or more data sources, relating to at least one event participant. A notification of a scheduled event is received at a server. The notification identities a plurality of individuals invited to attend or participate in an event. Data attributes relating to the event participants are retrieved from one or more data sources and stored. The data attributes can include personal attributes, professional attributes, and social interaction attributes. Before, during or after an event, requests are received and processed to provide event participants and other interested parties access to contextual information relating event participants to one another, the identities of event participants possessing one or more attributes, and lists of attributes for one or more known event participants. The requests can include images and sound recordings captured during the event.

A process is described for a call management system to provide a call transcription supervisory monitoring interactive dashboard of incoming calls at a command center. A plurality of incoming calls are received including a first call reflecting a first incident and a second call reflecting a second incident. Audio from the first and second calls are transcribed. First and second incoming call objects are displayed in a call-by-call portion of the interactive dashboard. The transcripts are cross-referenced with a call-by-call keyword database to identify call-by-call keywords of interest, and the incoming call objects are populated with the call-by-call keywords of interest. An all-call object is displayed in an all-call portion of the interactive dashboard. The transcripts are cross-referenced with an all-call keyword database to identify all-call keywords of interest, and the all-call object is populated with the all-call keywords of interest.

A process is described for a call management system to provide a call transcription supervisory monitoring interactive dashboard of incoming calls at a command center. A plurality of incoming calls are received including a first call reflecting a first incident and a second call reflecting a second incident. Audio from the first and second calls are transcribed. First and second incoming call objects are displayed in a call-by-call portion of the interactive dashboard. The transcripts are cross-referenced with a call-by-call keyword database to identify call-by-call keywords of interest, and the incoming call objects are populated with the call-by-call keywords of interest. An all-call object is displayed in an all-call portion of the interactive dashboard. The transcripts are cross-referenced with an all-call keyword database to identify all-call keywords of interest, and the all-call object is populated with the all-call keywords of interest.

In some examples, with respect to intent and context-aware dialogue based virtual assistance, an intent of an inquiry may be determined using an intent classification model. A determination may be made as to whether the determined intent matches a pre-specified intent of a plurality of pre-specified intents. Based on a determination that the determined intent does not match the pre-specified intent, a question related to the inquiry may be generated. Another intent of the inquiry may be determined by analyzing a response to the question using the intent classification model. A determination may be made as to whether the determined other intent matches another pre-specified intent of the plurality of pre-specified intents. Based on a determination that the determined other intent does not match the other pre-specified intent, a deep learning model may be utilized to predict a response to the inquiry.

Systems and methods of transferring data from memory to manage graphical output latency are provided. A device having a display receives an acoustic signal that carries a query. The device determines that a wireless controller is in a first state. The device establishes, based on receipt of the acoustic signal and the determination that the wireless controller device is in the first state, a first interaction mode for a graphical user interface rendered by the computing device for display via the display device. The device sets a prefetch parameter to a first value and prefetches the corresponding amount of electronic content items. The device establishes a second interaction mode and overrides the first value of the prefetch parameter to a second value, and prefetches a second amount of electronic content items corresponding to the second value.

Systems and methods of transferring data from memory to manage graphical output latency are provided. A device having a display receives an acoustic signal that carries a query. The device determines that a wireless controller is in a first state. The device establishes, based on receipt of the acoustic signal and the determination that the wireless controller device is in the first state, a first interaction mode for a graphical user interface rendered by the computing device for display via the display device. The device sets a prefetch parameter to a first value and prefetches the corresponding amount of electronic content items. The device establishes a second interaction mode and overrides the first value of the prefetch parameter to a second value, and prefetches a second amount of electronic content items corresponding to the second value.

An apparatus includes a memory and processor. The memory stores previous requests and corresponding previous responses. The processor determines that a user device transmitted a new voice request, converts the voice request into a first set of text, and transmits the text to an agent device. The processor applies the machine learning algorithm to the first set of text to generate suggested responses, by identifying patterns shared by the first set of text and a subset of the previous requests that are associated with the suggested responses. The processor transmits the suggested responses to the agent device. The processor then determines that the agent device transmitted voice signals responding to the new request. The processor converts these voice signals into a second set of text. The processor stores the first set of text as a previous request, and the second set of text as a corresponding previous response.

An apparatus includes a memory and processor. The memory stores previous requests and corresponding previous responses. The processor determines that a user device transmitted a new voice request, converts the voice request into a first set of text, and transmits the text to an agent device. The processor applies the machine learning algorithm to the first set of text to generate suggested responses, by identifying patterns shared by the first set of text and a subset of the previous requests that are associated with the suggested responses. The processor transmits the suggested responses to the agent device. The processor then determines that the agent device transmitted voice signals responding to the new request. The processor converts these voice signals into a second set of text. The processor stores the first set of text as a previous request, and the second set of text as a corresponding previous response.