# US 10,872,115 B2 · Automatically associating an image with an audio track > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,872,115 B2 - Document ID: US10872115B2 - Status: Granted - Kind: B2 - Application number: 15/925,695 - Filed: 2018-03-19 - Published: 2019-09-19 - Granted: 2020-12-22 - Earliest claimed: 2018-03-19 - Assignees: Motorola Mobility LLC - Applicants: Motorola Mobility LLC - Inventors: Amit Kumar Agrawal; Vishnu Kumar Shivaji Rao - Web page: https://patentgrep.com/patent/US10872115B2 ## CPC - G06F 16/5866: {using information manually generated, e.g. tags, keywords, comments, manually generated location and time information} - G06F 16/433: {using audio data} - G06F 16/635: Filtering based on additional data, e.g. user or group profiles - G06F 16/686: {using information manually generated, e.g. tags, keywords, comments, title or artist information, time, location or usage information, user ratings} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Techniques described herein automatically associate an image with an audio track. At least some implementations identify an audio track of interest, and automate associating an image with the audio track. Some implementations gather context information during playback of an audio track, and use the context information to automatically identify an image to associate with the audio track. Upon associating the image with the audio track, various implementations render the image during subsequent playback of the audio track. ## Claims ### Claim 1 A computer-implemented method comprising: automatically identifying an audio track of interest by monitoring user interactions with a computing device; gathering context information during playback of the audio track, the context information including information describing an environment in which playback of the audio track occurs, wherein the context information comprises a particular date on which playback of the audio track occurred; automatically identifying an image to associate with the audio track of interest based, at least in part, on the context information, the automatically identifying the image including searching for an event that occurred on the particular date and identifying an image corresponding to the event; associating the image with the audio track of interest; and rendering the image during subsequent playback of the audio track of interest. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein said associating the image with the audio track of interest further comprises: generating association information that links the image with the audio track; and causing the association information to be stored at a remote server. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, wherein said gathering the context information further comprises generating a keyword or tag for the context information, and wherein said automatically identifying the image further comprises searching an image database using the keyword or tag. ### Claim 4 (depends on 1) The computer-implemented method of claim 1, wherein said gathering context information during playback of the audio track further comprises: gathering the context information during multiple playback events of the audio track; and generating cumulative context information with the context information gathered during the multiple playback events. ### Claim 5 (depends on 1) The computer-implemented method of claim 1, wherein the context information further comprises a physical location of the computing device during playback of the audio track. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, wherein said automatically identifying the audio track of interest by monitoring the user interactions further comprises: monitoring how often the audio track is played by generating a playback count number; and determining the audio track is of interest when the playback count number reaches a predetermined threshold. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein said automatically identifying the image further comprises identifying an image that is captured during playback of the audio track. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, wherein said automatically identifying the image to associate with the audio track of interest further comprises: automatically rendering a user interface that includes an automatically identified image; and displaying a prompt to confirm selection of the automatically identified image as the image to associate with the audio track. ### Claim 9 (depends on 1) The computer-implemented method of claim 1, wherein said gathering context information further comprises identifying an individual within a threshold proximity of the computing device and the context information comprises an indication of the identified individual. ### Claim 10 (depends on 1) The computer-implemented method of claim 1, wherein said gathering context information further comprises identifying an image repeatedly viewed by the user during playback of the audio track, and said automatically identifying the image further comprises automatically identifying the repeatedly viewed image as the image to associate with the audio track. ### Claim 11 (depends on 1) The computer-implemented method of claim 1, wherein said automatically identifying the audio track of interest comprises determining, as the audio track of interest, one of multiple audio tracks that has been played back repeatedly. ### Claim 12 (depends on 1) The computer-implemented method of claim 1, wherein said automatically identifying the audio track of interest comprises determining, as the audio track of interest, one of multiple audio tracks that has been shared via social media. ### Claim 13 A computing device comprising: one or more processors; and one or more computer-readable storage memories comprising processor-executable instructions that, responsive to execution by the one or more processors, cause the computing device to perform operations comprising: automatically identifying an audio track of interest by monitoring user interactions with the computing device; gathering context information during playback of the audio track of interest by the computing device, the context information including information describing an environment in which playback of the audio track by the computing device occurs, wherein the context information comprises a particular date on which playback of the audio track of interest occurred; automatically identifying an image to associate with the audio track of interest based, at least in part, on the context information, wherein said automatically identifying the image comprises searching for an event that occurred on the particular date and identifying an image corresponding to the event; associating the image with the audio track of interest; and rendering the image during subsequent playback of the audio track of interest. ### Claim 14 (depends on 13) The computing device method of claim 13, wherein said gathering context information further comprises identifying an individual within a threshold proximity of the computing device and the context information comprises an indication of the identified individual. ### Claim 15 (depends on 13) The computing device method of claim 13, wherein said gathering context information further comprises identifying an image repeatedly viewed by the user during playback of the audio track of interest, and said automatically identifying the image further comprises automatically identifying the repeatedly viewed image as the image to associate with the audio track of interest. ### Claim 16 A computing device comprising: a playback control module, implemented at least in part in hardware, to provide a user interface with one or more selectable controls; and a context engine module, implemented at least in part in hardware, to automatically identify an audio track of interest by monitoring user interactions with a computing device, gather context information during playback of the audio track, the context information including information describing an environment in which playback of the audio track occurs, wherein the context information comprises a particular date on which playback of the audio track of interest occurred, automatically identify an image to associate with the audio track of interest based, at least in part, on the context information, wherein said automatically identifying the image comprises searching for an event that occurred on the particular date and identifying an image corresponding to the event, associate the image with the audio track of interest, and render the image during subsequent playback of the audio track of interest. ### Claim 17 (depends on 16) The computing device of claim 16, wherein to automatically identify an audio track of interest is to determine, as the audio track of interest, one of multiple audio tracks that has been played back repeatedly. ### Claim 18 (depends on 16) The computing device of claim 16, wherein to automatically identify an audio track of interest is to determine, as the audio track of interest, one of multiple audio tracks that has been shared via social media. ### Claim 19 (depends on 16) The computing device of claim 16, wherein said gathering context information further comprises identifying an image repeatedly viewed by the user during playback of the audio track of interest, and said automatically identifying the image further comprises automatically identifying the repeatedly viewed image as the image to associate with the audio track of interest. ### Claim 20 (depends on 13) The computing device method of claim 13, wherein said automatically identifying the image to associate with the audio track of interest further comprises: automatically rendering a user interface that includes an automatically identified image; and displaying a prompt to confirm selection of the automatically identified image as the image to associate with the audio track.