US-20260128042-A1 - APPARATUS, PLATFORM, METHOD AND MEDIUM FOR INTENTION IMPORTANCE INFERENCE

US20260128042A1US 20260128042 A1US20260128042 A1US 20260128042A1US-20260128042-A1

Abstract

The application provides an apparatus, platform, method and medium for intention importance interference. The apparatus includes an interface configured to receive user-related information; and a processor coupled to the interface and configured to: extract data related to different aspects of a user from the user-related information; generate a plurality of intention probes based on the data related to different aspects of the user, each intention probe comprising an intention and associated data items; infer an importance of each intention probe by calculating a score of each associated data items of the intention probe based on the data related to different aspects of the user; and provide information associated with an intention probe with a highest importance.

Inventors

Chong Wang

Assignees

SOUNDHOUND AI IP, LLC

Dates

Publication Date: 20260507
Application Date: 20251229
Priority Date: 20220525

Claims (20)

1 . A computer-implemented method of inferring user intentions, comprising: receiving user-related information of a user from a plurality of channels; extracting, via a speech recognition system, intention data from the user-related information from the plurality of channels; generating an intention probes based on the intention data related to the user, the intention probe comprising a user task to be performed and associated data items related to the user task; receiving-changes of the associated data items related to the user task from the plurality of channels; continuously inferring a plurality of importance scores of the intention probe; determining a highest importance score of the intention probe; and generating, via an information recommender, a reminder associated with the intention probe to remind the user about the user task.
2 . The computer-implemented method of claim 1 , wherein the reminder further comprises an associated business recommendation.
3 . The computer-implemented method of claim 1 , wherein the user-related information comprises speech-based information, and the processor is configured to extract an abstract from a transcript of the speech-based information, and obtain the intention data based on the abstract.
4 . The computer-implemented method of claim 1 , further comprising: keeping the intention probe active until the user task happens or the corresponding intention probe expires.
5 . The computer-implemented method of claim 1 , further comprising: adjusting the plurality of importance scores dynamically; and inferring the importance of the intention probe based on the sum of scores of the associated data items of the intention probe.
6 . The computer-implemented method of claim 1 , wherein the user task comprises one or more activities, the associated data items comprise timing and location information as the user input data to implement the one or more activities.
7 . The computer-implemented method of claim 1 , wherein the reminder comprises an audio output associated with the intention probe to remind the user about the user task.
8 . The computer-implemented method of claim 1 , further comprising: updating the intention data over a predetermined period of time; and generating an updated intention probe based on the updated intention.
9 . A computer system, comprising: at least one processor; and memory including instructions that, when executed by the at least one processor, cause the computer system to: receive user-related information of a user from a plurality of channels; extract, via a speech recognition system, intention data from the user-related information from the plurality of channels; generate an intention probes based on the intention data related to the user, the intention probe comprising a user task to be performed and associated data items related to the user task; receive changes of the associated data items related to the user task from the plurality of channels; continuously infer a plurality of importance scores of the intention probe; determine a highest importance score of the intention probe; and generate, via an information recommender, a reminder associated with the intention probe to remind the user about the user task.
10 . The computer system of claim 9 , wherein the reminder further comprises an associated business recommendation.
11 . The computer system of claim 9 , wherein the user-related information includes speech-based information, and the method comprises extracting an abstract from a transcript of the speech-based information, and obtaining the intention data based on the abstract.
12 . The computer system of claim 9 , wherein the instructions when executed further cause the computer system to: keep the intention probe active until the user task happens or the corresponding intention probe expires.
13 . The computer system of claim 9 , wherein the instructions when executed further cause the computer system to: adjust the plurality of importance scores dynamically; and infer the importance of the intention probe based on the sum of scores of the associated data items of the intention probe.
14 . The computer system of claim 9 , wherein the user task comprises one or more activities, the associated data items comprise timing and location information as the user input data to implement the one or more activities.
15 . The computer system of claim 9 , wherein the reminder comprises an audio output associated with the intention probe to remind the user about the user task.
16 . The computer system of claim 15 , wherein the instructions when executed further cause the computer system to: provide the audio output associated with the intention probe in response to a speech-based trigger of the user.
17 . The computer system of claim 9 , wherein the instructions when executed further cause the computer system to: update the intention data over a predetermined period of time; and generate a plurality of updated intention probes based on the updated intention.
18 . A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to: receive user-related information of a user from a plurality of channels; extract, via a speech recognition system, intention data from the user-related information from the plurality of channels; generate an intention probes based on the intention data related to the user, the intention probe comprising a user task to be performed and associated data items related to the user task; receive changes of the associated data items related to the user task from the plurality of channels; continuously infer a plurality of importance scores of the intention probe; determine a highest importance score of the intention probe; and generate, via an information recommender, a reminder associated with the intention probe to remind the user about the user task.
19 . The non-transitory computer-readable storage medium of claim 18 , wherein the reminder further comprises an associated business recommendation.
20 . The non-transitory computer-readable storage medium of claim 18 , wherein the user-related information includes speech-based information, and the method comprises extracting an abstract from a transcript of the speech-based information, and obtaining the intention data based on the abstract.

Description

CROSS-REFERENCE TO RELATED APPLICATION This application is a continuation application of U.S. Non-Provisional patent application Ser. No. 17/820,660, entitled “APPARATUS, PLATFORM, METHOD AND MEDIUM FOR INTENTION IMPORTANCE INFERENCE” filed on Aug. 18, 2022, which claims priority to Chinese Patent Application Serial No. 202210572663, filed on May 25, 2022, the disclosure of all of which is hereby incorporated by reference in its entirety. BACKGROUND With the popularization of smart electronic devices, people can perform more and more activities, such as communication, conference, itinerary planning, online shopping, mobile payment and the like, with the smart electronic devices. People hope that the smart electronic devices can more and more “understand” user's mind, and “automatically” recommend information related to an activity that the user most wants to perform, so as to bring more convenience to people's daily life and work. SUMMARY An aspect of the present application provides a data processing apparatus. The apparatus includes an interface configured to receive user-related information; and a processor coupled to the interface and configured to: extract data related to different aspects of a user from the user-related information; generate a plurality of intention probes based on the data related to different aspects of the user, each intention probe comprising an intention and associated data items; infer an importance of each intention probe by calculating a score of each associated data items of the intention probe based on the data related to different aspects of the user; and provide information associated with an intention probe with a highest importance. Another aspect of the present application provides a data processing method. The method includes receiving user-related information; extracting data related to different aspects of a user from the user-related information; generating a plurality of intention probes based on the data related to different aspects of the user, each intention probe comprising an intention and associated data items; inferring an importance of each intention probe by calculating a score of each associated data items of the intention probe based on the data related to different aspects of the user; and providing information associated with an intention probe with a highest importance. Another aspect of the present application provides a computer-readable storage medium having instructions stored thereon, the instructions, when executed by a processor, implementing the above-mentioned data processing method. Another aspect of the present application provides a data management platform including the above-mentioned data processing apparatus. BRIEF DESCRIPTION OF THE DRAWINGS Particular features, aspects and advantages of the present application will be better understood with reference to the following description and accompanying drawings, wherein: FIG. 1 shows a schematic block diagram of an apparatus for intention importance interference according to some embodiments of the present disclosure. FIG. 2 shows a schematic diagram of an example of a data structure related to different aspects of a user according to some embodiments of the present disclosure. FIG. 3 shows a schematic diagram of an intention probe instance according to some embodiments of the present disclosure. FIG. 4 shows a flowchart of an example process for intention importance interference according to an embodiment of the present disclosure. FIG. 5 shows a block diagram of an example computer system including various components for implementing the example process for inferring significance of intention importance interference. DETAILED DESCRIPTION Various aspects of the illustrative embodiments will be described using terms commonly employed by those skilled in the art to convey the substance of the disclosure to others skilled in the art. However, it will be apparent to those skilled in the art that many alternate embodiments may be practiced using portions of the described aspects. For purposes of explanation, specific numbers, materials, and configurations are set forth in order to provide a thorough understanding of the illustrative embodiments. However, it will be apparent to those skilled in the art that alternate embodiments may be practiced without the specific details. In other instances, well known features may have been omitted or simplified in order to avoid obscuring the illustrative embodiments. Further, various operations will be described as multiple discrete operations, in turn, in a manner that is most helpful in understanding the illustrative embodiments; however, the order of description should not be construed as to imply that these operations are necessarily order dependent. In particular, these operations need not be performed in the order of presentation. The phrase “in some embodiments” is used repeatedly herein. The phrase generally does not refer to the same embodiments;