CN116346900A - Media recommendation method and device based on emotion of passengers in vehicle, vehicle and medium - Google Patents
Media recommendation method and device based on emotion of passengers in vehicle, vehicle and medium Download PDFInfo
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Abstract
The invention relates to the technical field of vehicles and discloses a media recommendation method, a device, a vehicle and a medium based on emotion of passengers in a vehicle, wherein the method comprises the steps of acquiring sound information of the passengers in the vehicle and acquiring position information of sound sources according to the sound information; acquiring face state information of a corresponding position according to the position information; uploading the face state information to a cloud database for identification to obtain passenger emotion information of a sound source; obtaining content to be pushed according to a pre-configured media recommendation model and the passenger emotion information; the media recommendation model comprises a mapping relation between passenger emotion information and content to be pushed; and sending the content to be pushed to media playing equipment close to the sound source passenger according to the position information so as to recommend the content. The pushing method can accurately push the passengers according to the emotion and the position of the passengers, and improves the driving experience of the passengers.
Description
Technical Field
The invention relates to the technical field of vehicles, in particular to a media recommendation method and device based on emotion of passengers in a vehicle, the vehicle and a medium.
Background
At present, a user has high requirements on the driving safety performance, and also pays attention to intelligent experience in the driving process. The existing vehicle-mounted media playing device, such as a vehicle-mounted music player, only recommends music for the user group characteristics of passengers in a vehicle, but cannot recommends music for the emotion of the passengers in the vehicle, so that the experience of the passengers in the vehicle is poor.
Disclosure of Invention
The invention provides a media recommendation method, device, vehicle and medium based on emotion of an in-vehicle passenger, and aims to solve the technical problem that the emotion of the in-vehicle passenger cannot be recommended, so that the experience of the passenger is poor.
In order to solve the above technical problems, the present invention provides a media recommendation method based on emotion of an in-vehicle passenger, including:
acquiring sound information of passengers in the vehicle, and acquiring position information of sound sources according to the sound information;
acquiring face state information of a corresponding position according to the position information;
uploading the face state information to a cloud database for identification to obtain passenger emotion information of a sound source;
obtaining content to be pushed according to a pre-configured media recommendation model and the passenger emotion information; the media recommendation model comprises a mapping relation between passenger emotion information and content to be pushed;
and sending the content to be pushed to media playing equipment close to the sound source passenger according to the position information so as to recommend the content.
Preferably, after the sending the content to be pushed to the media playing device close to the sound source passenger according to the location information for recommendation, the method further comprises:
automatically playing according to the content to be pushed, and acquiring the playing time of the content to be pushed;
scoring the media recommendation model according to the playing time to obtain a score value of the media recommendation model;
calculating average scores of all the score values according to the score times in a preset scoring period;
and when the average score is determined to be lower than a preset score threshold, optimizing the media recommendation model.
Preferably, the scoring the media recommendation model according to the playing time to obtain a score value of the media recommendation model includes:
when the passenger closes the content to be pushed in a first time range, the score value of the media recommendation model is a first score value;
when the passenger closes the content to be pushed in a second time range, the score value of the media recommendation model is a second score value;
when the passenger closes the content to be pushed in a third time range, the score value of the media recommendation model is a third score value;
when the passenger closes the content to be pushed in a fourth time range, the score value of the media recommendation model is a fourth score value;
and when the passenger closes the content to be pushed in a fifth time range, the score value of the media recommendation model is a fifth score value.
Preferably, the optimizing the media recommendation model includes:
judging whether the emotion classification in the media recommendation model is accurate, if not, updating the emotion classification; if yes, replacing the content to be recommended.
Preferably, the obtaining the location information of the sound source according to the sound information includes:
when detecting that a voice exists in the vehicle, obtaining position information according to the voice source; the position information comprises a primary driver, a secondary driver, a primary driver rear side or a secondary driver rear side.
Preferably, the obtaining the location information of the sound source according to the sound information includes:
when a plurality of voices are detected in the vehicle, the position information of the sound source is paused to be judged until only one voice exists;
after only one voice is generated, and when the distance from the last multiple voices exceeds a preset time interval, position information is obtained according to the voice source; the position information comprises a primary driver, a secondary driver, a primary driver rear side or a secondary driver rear side.
Preferably, the playing mode of the content to be pushed includes bluetooth headset playing, back-row playing only and full car playing.
In a second aspect, the present invention provides a media recommendation device based on emotion of a passenger in a vehicle, including:
the position judging module is used for acquiring sound information of passengers in the vehicle and obtaining position information of sound sources according to the sound information;
the face acquisition module is used for acquiring face state information of the corresponding position according to the position information;
the emotion recognition module is used for uploading the face state information to a cloud database for recognition to obtain passenger emotion information of a sound source;
the content matching module is used for obtaining content to be pushed according to a pre-configured media recommendation model and the passenger emotion information; the media recommendation model comprises a mapping relation between passenger emotion information and content to be pushed;
and the content recommendation module is used for sending the content to be pushed to media playing equipment close to the sound source passenger according to the position information so as to recommend the content.
In a third aspect, the present invention further provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, where the processor implements the media recommendation method based on the emotion of the passenger in the vehicle according to any one of the above when executing the computer program.
In a fourth aspect, the present invention further provides a computer readable storage medium, where the computer readable storage medium includes a stored computer program, where when the computer program runs, the computer readable storage medium is controlled to execute the media recommendation method based on the emotion of the passenger in the vehicle according to any one of the above methods.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a media recommendation method based on the emotion of an in-car passenger, which comprises the steps of obtaining sound information of the in-car passenger and obtaining the position information of a sound source according to the sound information; acquiring face state information of a corresponding position according to the position information; uploading the face state information to a cloud database for identification to obtain passenger emotion information of a sound source; obtaining content to be pushed according to a pre-configured media recommendation model and the passenger emotion information; the media recommendation model comprises a mapping relation between passenger emotion information and content to be pushed; and sending the content to be pushed to media playing equipment close to the sound source passenger according to the position information so as to recommend the content.
According to the intelligent recommendation method, behaviors of passengers in the vehicle are captured based on voice and cameras, the human expressions are identified, comprehensive analysis is carried out, then matching is carried out on a background expression library to find keywords, and further intelligent recommendation suitable for the current scene is recommended to the analyzed passengers. The recommendation method is accurate only for analyzed passengers, and if the passengers are in the rear row, the recommendation method does not influence the driver, so that the driving experience of the driver and all passengers is improved.
Drawings
Fig. 1 is a flowchart of a media recommendation method based on emotion of an in-vehicle passenger according to a first embodiment of the present invention;
fig. 2 is a schematic structural diagram of a media recommendation device based on emotion of passengers in a vehicle according to a second embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a first embodiment of the present invention provides a media recommendation method based on emotion of a passenger in a vehicle, comprising the steps of:
s11, acquiring sound information of passengers in the vehicle, and acquiring position information of sound sources according to the sound information;
s12, acquiring face state information of the corresponding position according to the position information;
s13, uploading the face state information to a cloud database for identification to obtain passenger emotion information of a sound source;
s14, obtaining content to be pushed according to a pre-configured media recommendation model and the passenger emotion information; the media recommendation model comprises a mapping relation between passenger emotion information and content to be pushed;
and S15, sending the content to be pushed to media playing equipment close to the sound source passenger according to the position information so as to recommend the content.
It should be noted that, in the embodiment of the invention, the vehicle is a 4-voice zone vehicle type, the front and rear rows are provided with screens, and the rear row vehicle machine only occupies rear row speakers. Meanwhile, the vehicle is provided with a rotatable camera. Based on judgment of human voice and the face state shot by the DMS camera, the current emotion of the passenger is obtained through comprehensive comparison, and corresponding media content recommendation is matched in a background recommendation model.
In step S11, sound information of a passenger in the vehicle is acquired, and position information of a sound source is obtained according to the sound information.
Illustratively, when a human voice is detected in the vehicle, obtaining position information according to the voice source; the position information comprises a primary driver, a secondary driver, a primary driver rear side or a secondary driver rear side.
Illustratively, when a plurality of voices are detected in the vehicle, the judgment of the position information of the sound source is suspended until only one voice exists;
after only one voice is generated, and when the distance from the last multiple voices exceeds a preset time interval, position information is obtained according to the voice source; the position information comprises a primary driver, a secondary driver, a primary driver rear side or a secondary driver rear side.
For example, after the host collects the voice, if there are a plurality of position voices, the host pauses; when only one position sound exists, whether the last non-target voice exceeds 20min is continuously judged, if not, the voice is paused, if yes, the voice parameter is transmitted to the DMS system, and the DMS rotates the camera according to the position information.
In step S12, face state information of the corresponding position is obtained according to the position information. It should be noted that, the DMS camera in the vehicle has a rotation function, when a person speaks, the DMS camera transmits a position information to the DMS through the host, and the DMS camera is aligned to the person speaking in the vehicle to shoot according to the received position information and the rotation direction.
In step S13, the face state information is uploaded to a cloud database for recognition, so as to obtain the emotion information of the passenger with the sound source. For example, after the DMS camera is aligned with the speaking direction, the facial expression is recognized, the expression and the position information are transmitted to the background, and the background is used for comparing in the expression library to locate the emotion of the passenger in the vehicle, namely the emotion information of the passenger.
In another embodiment, keywords can be extracted from the voice information, and the passenger emotion information can be obtained by matching the keywords. For example, the car machine always monitors the speaking state in the car, and when the car machine is networked, the recognition result is transmitted to the background in real time, and the background matches the keyword to recognize what emotion the customer is currently, namely passenger emotion information. When the passenger emotion information obtained by detecting the voice information extraction keywords is inconsistent with the expression recognition, the passenger voice recognition result is taken as the main basis.
In step S14, obtaining content to be pushed according to a pre-configured media recommendation model and the passenger emotion information; the media recommendation model comprises a mapping relation between passenger emotion information and content to be pushed.
The media recommendation model is a corresponding library of emotional states and contents to be pushed, such as music, videos, jokes or talk shows, and when the background is matched with the recommended contents, the background is transmitted to a corresponding module of the host together with the position information, and the corresponding module randomly recommends one content.
In step S15, the content to be pushed is sent to a media playing device close to the passenger with the sound source according to the location information, so as to make a recommendation. The playing mode of the content to be pushed comprises Bluetooth earphone playing, back-row playing only and full car playing.
Illustratively, when a passenger is detected to speak keywords such as car sickness, some hypnotic songs are played, as sleeping is a good way to avoid car sickness; playing a joke when detecting that the emotion of the passenger falls; when detecting that the passengers say that the passengers are very difficult today, playing the excitation type songs by using keywords with bad states; when detecting that the passenger says to be loved, the passenger is in a hands-free emotion, and the wounded type songs and the like are played; when the passenger is detected to be yawed, the key words which indicate fatigue, tiredness, or the passenger is detected to say tiredness are played for a talk show.
In this embodiment, the main driving and the auxiliary driving, that is, the moods of the front passengers, and the recommended content follows the speaker playing rule to determine whether to play the vehicle. The back passengers are in emotion, recommended content only responds to the back screen, and playing content only plays on the back loudspeaker, so that the driver is not disturbed, and the driving safety is improved.
The speaker playing rules are selectable in the media playing pages of the rear host, and the media playing pages comprise Bluetooth earphone playing, rear-row playing only and full car playing. When the Bluetooth earphone plays, namely the rear-row playing, the Bluetooth earphone is used for listening, and the loudspeaker does not sound; playing content only responds to the rear-row loudspeaker only when playing only at the rear-row; the whole car plays, namely, the front and rear loudspeakers play the rear host content, and the front content is paused.
For example, when the front host plays media, if the play option of the back host is bluetooth headset play, the front play should not affect the back play content, except that the front play is full car play; when the front host plays the content, the back host pauses the playing of the content; the back-row playback follows the speaker playback rule settings.
In order to facilitate an understanding of the invention, some preferred embodiments of the invention will be described further below.
In one implementation, after the sending the content to be pushed to a media playing device near the sound source passenger according to the location information to make a recommendation, the method further includes:
automatically playing according to the content to be pushed, and acquiring the playing time of the content to be pushed;
scoring the media recommendation model according to the playing time to obtain a score value of the media recommendation model;
calculating average scores of all the score values according to the score times in a preset scoring period;
and when the average score is determined to be lower than a preset score threshold, optimizing the media recommendation model.
It should be noted that, when the host computer recommends to play automatically, the passenger may not be satisfied with the push content and actively pause or close (including manual clicking and voice closing), so the accuracy of the push needs to be determined according to the time of the active pause of the passenger.
In one embodiment, the scoring the media recommendation model according to the playing time to obtain a score value of the media recommendation model includes:
when the passenger closes the content to be pushed in a first time range, the score value of the media recommendation model is a first score value;
when the passenger closes the content to be pushed in a second time range, the score value of the media recommendation model is a second score value;
when the passenger closes the content to be pushed in a third time range, the score value of the media recommendation model is a third score value;
when the passenger closes the content to be pushed in a fourth time range, the score value of the media recommendation model is a fourth score value;
and when the passenger closes the content to be pushed in a fifth time range, the score value of the media recommendation model is a fifth score value.
For example, after recommending content, the passenger is scored according to the time of active pause (including manual click and voice shutdown), the passenger is closed for 0 score in 2min, closed for 2 score in 2-5min, closed for 3 score in 5-10min, closed for 5 score in 10-20min, and closed for 10 score over 20min, and then the average score (total score/recommended number) is calculated. Then, the model is checked for the average score every month, and optimization is needed if the continuous 2 months are less than 3 minutes.
In one embodiment, the optimizing the media recommendation model includes:
judging whether the emotion classification in the media recommendation model is accurate, if not, updating the emotion classification; if yes, replacing the content to be recommended.
Illustratively, the log is checked first to see if the passenger speaks and expression, and if the classification of emotion is accurate. Then, looking at the recommended content, e.g. the passenger's emotion is sad, the passenger playing the casualty-type song may be more reputable, and the inspired-type song may be exchanged.
In summary, the invention has the following advantages:
1, the rotation function of the DMS camera can take care of all passengers in the vehicle, and compared with the traditional fixed camera which is only aligned with a main driver, the function of the DMS is upgraded once;
2. the recommended content is only recommended to the rear host computer aiming at the host computer where the analyzed passenger is located, namely when the rear passenger is detected to meet the recommended requirement, the main driving loudspeaker is not influenced, and the safety of a driver is improved;
3. compared with the traditional method for singly detecting the emotion of the passenger, the method for combining the speaking is more accurate and comprehensive, and the emotion of the passenger at the time can be more accurately positioned through the speaking.
Referring to fig. 2, a second embodiment of the present invention provides a media recommendation device based on emotion of a passenger in a vehicle, including:
the position judging module is used for acquiring sound information of passengers in the vehicle and obtaining position information of sound sources according to the sound information;
the face acquisition module is used for acquiring face state information of the corresponding position according to the position information;
the emotion recognition module is used for uploading the face state information to a cloud database for recognition to obtain passenger emotion information of a sound source;
the content matching module is used for obtaining content to be pushed according to a pre-configured media recommendation model and the passenger emotion information; the media recommendation model comprises a mapping relation between passenger emotion information and content to be pushed;
and the content recommendation module is used for sending the content to be pushed to media playing equipment close to the sound source passenger according to the position information so as to recommend the content.
It should be noted that, the media recommendation device based on the emotion of the passenger in the vehicle provided by the embodiment of the invention is used for executing all the flow steps of the media recommendation method based on the emotion of the passenger in the vehicle in the embodiment, and the working principles and beneficial effects of the two are in one-to-one correspondence, so that the description is omitted.
The embodiment of the invention also provides a vehicle, which comprises a rotatable camera, media playing equipment and a vehicle controller, wherein the vehicle controller is used for realizing the media recommendation method based on the emotion of the passengers in the vehicle according to any one of the above embodiments.
The embodiment of the invention also provides terminal equipment. The terminal device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a media recommendation program based on the mood of an in-vehicle passenger. The processor, when executing the computer program, implements the steps of the above embodiments of the media recommendation method based on the emotion of the passenger in the vehicle, for example, step S11 shown in fig. 1. Alternatively, the processor, when executing the computer program, implements the functions of the modules/units in the above-described device embodiments, such as a content matching module.
The computer program may be divided into one or more modules/units, which are stored in the memory and executed by the processor to accomplish the present invention, for example. The one or more modules/units may be a series of computer program instruction segments capable of performing the specified functions, which instruction segments are used for describing the execution of the computer program in the terminal device.
The terminal equipment can be a desktop computer, a notebook computer, a palm computer, an intelligent tablet and other computing equipment. The terminal device may include, but is not limited to, a processor, a memory. It will be appreciated by those skilled in the art that the above components are merely examples of terminal devices and do not constitute a limitation of terminal devices, and may include more or fewer components than described above, or may combine certain components, or different components, e.g., the terminal devices may also include input and output devices, network access devices, buses, etc.
The processor may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is a control center of the terminal device, and which connects various parts of the entire terminal device using various interfaces and lines.
The memory may be used to store the computer program and/or module, and the processor may implement various functions of the terminal device by running or executing the computer program and/or module stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
Wherein the terminal device integrated modules/units may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as stand alone products. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
It should be noted that the above-described apparatus embodiments are merely illustrative, and the units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the drawings of the embodiment of the device provided by the invention, the connection relation between the modules represents that the modules have communication connection, and can be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
The foregoing embodiments have been provided for the purpose of illustrating the general principles of the present invention, and are not to be construed as limiting the scope of the invention. It should be noted that any modifications, equivalent substitutions, improvements, etc. made by those skilled in the art without departing from the spirit and principles of the present invention are intended to be included in the scope of the present invention.
Claims (10)
1. A media recommendation method based on the emotion of a passenger in a vehicle, comprising:
acquiring sound information of passengers in the vehicle, and acquiring position information of sound sources according to the sound information;
acquiring face state information of a corresponding position according to the position information;
uploading the face state information to a cloud database for identification to obtain passenger emotion information of a sound source;
obtaining content to be pushed according to a pre-configured media recommendation model and the passenger emotion information; the media recommendation model comprises a mapping relation between passenger emotion information and content to be pushed;
and sending the content to be pushed to media playing equipment close to the sound source passenger according to the position information so as to recommend the content.
2. The in-car passenger emotion-based media recommendation method according to claim 1, characterized in that after said transmitting said content to be pushed to a media playback device close to a sound source passenger according to said location information for recommendation, said method further comprises:
automatically playing according to the content to be pushed, and acquiring the playing time of the content to be pushed;
scoring the media recommendation model according to the playing time to obtain a score value of the media recommendation model;
calculating average scores of all the score values according to the score times in a preset scoring period;
and when the average score is determined to be lower than a preset score threshold, optimizing the media recommendation model.
3. The method for media recommendation based on in-car passenger emotion according to claim 2, wherein scoring the media recommendation model according to the playing time to obtain a score value of the media recommendation model comprises:
when the passenger closes the content to be pushed in a first time range, the score value of the media recommendation model is a first score value;
when the passenger closes the content to be pushed in a second time range, the score value of the media recommendation model is a second score value;
when the passenger closes the content to be pushed in a third time range, the score value of the media recommendation model is a third score value;
when the passenger closes the content to be pushed in a fourth time range, the score value of the media recommendation model is a fourth score value;
and when the passenger closes the content to be pushed in a fifth time range, the score value of the media recommendation model is a fifth score value.
4. The in-vehicle passenger emotion-based media recommendation method according to claim 2, wherein optimizing the media recommendation model comprises:
judging whether the emotion classification in the media recommendation model is accurate, if not, updating the emotion classification; if yes, replacing the content to be recommended.
5. The method for media recommendation based on in-vehicle passenger emotion according to claim 1, wherein said obtaining location information of a sound source from the sound information comprises:
when detecting that a voice exists in the vehicle, obtaining position information according to the voice source; the position information comprises a primary driver, a secondary driver, a primary driver rear side or a secondary driver rear side.
6. The method for media recommendation based on in-vehicle passenger emotion according to claim 1, wherein said obtaining location information of a sound source from the sound information comprises:
when a plurality of voices are detected in the vehicle, the position information of the sound source is paused to be judged until only one voice exists;
after only one voice is generated, and when the distance from the last multiple voices exceeds a preset time interval, position information is obtained according to the voice source; the position information comprises a primary driver, a secondary driver, a primary driver rear side or a secondary driver rear side.
7. The method for media recommendation based on in-car passenger emotion according to claim 5 or 6, wherein the playing mode of the content to be pushed comprises bluetooth headset playing, back-only playing and full car playing.
8. A media recommendation device based on the emotion of a passenger in a vehicle, comprising:
the position judging module is used for acquiring sound information of passengers in the vehicle and obtaining position information of sound sources according to the sound information;
the face acquisition module is used for acquiring face state information of the corresponding position according to the position information;
the emotion recognition module is used for uploading the face state information to a cloud database for recognition to obtain passenger emotion information of a sound source;
the content matching module is used for obtaining content to be pushed according to a pre-configured media recommendation model and the passenger emotion information; the media recommendation model comprises a mapping relation between passenger emotion information and content to be pushed;
and the content recommendation module is used for sending the content to be pushed to media playing equipment close to the sound source passenger according to the position information so as to recommend the content.
9. A vehicle comprising a rotatable camera, a media playback device and a vehicle controller for implementing the in-vehicle passenger emotion-based media recommendation method according to any one of claims 1 to 7.
10. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored computer program, wherein the computer program, when run, controls a device in which the computer readable storage medium is located to perform the media recommendation method based on the emotion of an in-car passenger according to any one of claims 1 to 7.
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