# US 2019/0378535 A1 · Apparatus That Identifies A Scene Type and Method for Identifying a Scene Type > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0378535 A1 - Document ID: US20190378535A1 - Status: Published application - Kind: A1 - Application number: 16/550,833 - Filed: 2019-08-26 - Published: 2019-12-12 - Earliest claimed: 2017-02-27 - Assignees: Yamaha Corporation - Applicants: Yamaha Corporation - Inventors: Yuta YUYAMA - Web page: https://patentgrep.com/patent/US20190378535A1 ## CPC - G10L 25/57: for processing of video signals - G11B 27/28: by using information signals recorded by the same method as the main recording {(G11B27/22 takes precedence)} - H04S 7/00: Indicating arrangements; Control arrangements, e.g. balance control - G10L 25/72: for transmitting results of analysis - G10L: SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING - G11B: INFORMATION STORAGE BASED ON RELATIVE MOVEMENT BETWEEN RECORD CARRIER AND TRANSDUCER (recording measured values in a way that does not require playback through a transducer G01D9/00; recording or playback apparatus using mechanically marked tape, e.g. punched paper tape, or using unit records, e.g. punched or magnetically marked cards G06K; transferring data from one type of record carrier to another G06K1/18; circuits for coupling output of reproducer to radio receiver H04B1/20; gramophone pick-ups or like acoustic electromechanical transducers or circuits therefor H04R) - H04S: STEREOPHONIC SYSTEMS ## Abstract An apparatus that identifies a scene type includes at least one processor and a memory. The memory is operatively coupled to the at least one processor and is configured to store instructions executable by the processor. Upon execution of the instructions, the processor is caused to identify a scene type of content that includes video and audio based on a feature amount of the audio in the content. ## Claims ### Claim 1 An apparatus that identifies a scene type, comprising: at least one processor; and a memory that is operatively coupled to the at least one processor and that is configured to store instructions executable by the processor, wherein upon execution of the instructions the processor is caused to: prepare, for content that includes video and audio, a feature amount of the audio in the content; and identify the scene type of the content based on the feature amount of the audio. ### Claim 2 (depends on 1) The apparatus according to claim 1, wherein the processor is further caused to: set playback control data for controlling playback of the content based on the identified scene type. ### Claim 3 (depends on 2) The apparatus according to claim 2, wherein the playback control data includes audio control data for controlling a sound field formed by the audio in the content. ### Claim 4 (depends on 1) The apparatus according to claim 1, wherein in identifying the scene type, the scene type of the content is identified from the feature amount of the audio in the content by use of an identification model representative of relations between feature amounts of audio and scene types. ### Claim 5 (depends on 4) The apparatus according to claim 4, wherein the identification model is a statistical model that identifies a single scene type from the feature amount of the audio in the content. ### Claim 6 (depends on 1) The apparatus according to claim 1, wherein the processor is further caused to: notify a terminal apparatus of the identified scene type. ### Claim 7 (depends on 1) The apparatus according to claim 1, wherein the feature amount is a vector including elements corresponding to respective channels representative of the audio in the content, and each of the elements is a numerical value depending on frequency characteristics of a channel that corresponds to the element from among the channels. ### Claim 8 (depends on 1) The apparatus according to claim 1, wherein the scene type is a classification of a scene represented by the content. ### Claim 9 A method for identifying a scene type, comprising: preparing, for content that includes video and audio, a feature amount of the audio in the content; and identifying the scene type of the content based on the feature amount of the audio. ### Claim 10 (depends on 9) The method according to claim 9, wherein identifying a scene type includes identifying the scene type of the content from the feature amount of the audio in the content by use of an identification model representative of relations between feature amounts of audio and scene types. ### Claim 11 (depends on 10) The method according to claim 10, wherein the identification model is a statistical model that identifies a single scene type from the feature amount of the audio in the content. ### Claim 12 (depends on 9) The method according to claim 9, further comprising setting playback control data for controlling playback of the content based on the identified scene type. ### Claim 13 (depends on 12) The method according to claim 12, wherein the playback control data includes audio control data for controlling a sound field formed by the audio in the content. ### Claim 14 (depends on 9) The method according to claim 9, further comprising notifying a terminal apparatus of the identified scene type. ### Claim 15 (depends on 9) The method according to claim 9, wherein the feature amount of the audio in the content is a vector including elements corresponding to respective channels representative of the audio in the content, and each of the elements is a numerical value depending on frequency characteristics of a channel that corresponds to the element from among the channels. ### Claim 16 (depends on 9) The method according to claim 9, wherein the scene type is a classification of a scene represented by the content. ### Claim 17 A method for identifying a plurality of scene types, comprising: preparing, for content that includes video and audio, a feature amount of the audio in the content; and identifying, using a statistical model, a likelihood that the content corresponds to each of the plurality of scene types from the feature amount of the audio. ### Claim 18 (depends on 17) The method according to claim 17, wherein the feature amount is a vector including elements corresponding to respective channels representative of the audio in the content, and each of the elements is a numerical value depending on frequency characteristics of a channel that corresponds to the element from among the channels. ### Claim 19 (depends on 17) The method according to claim 17, wherein the scene type is a classification of a scene represented by the content.