CN110895934A - Household appliance control method and device - Google Patents
Household appliance control method and device Download PDFInfo
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- CN110895934A CN110895934A CN201811063352.6A CN201811063352A CN110895934A CN 110895934 A CN110895934 A CN 110895934A CN 201811063352 A CN201811063352 A CN 201811063352A CN 110895934 A CN110895934 A CN 110895934A
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
- G10L15/063—Training
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/017—Gesture based interaction, e.g. based on a set of recognized hand gestures
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/26—Speech to text systems
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/2803—Home automation networks
- H04L12/2816—Controlling appliance services of a home automation network by calling their functionalities
- H04L12/282—Controlling appliance services of a home automation network by calling their functionalities based on user interaction within the home
Abstract
The invention discloses a household appliance control method and device. Wherein, the method comprises the following steps: acquiring gesture information and voice information; recognizing a gesture recognition result by using the gesture model, and recognizing a voice recognition result by using the voice model; and controlling the household appliance according to the gesture represented by the gesture information when the recognized gesture recognition result is that the gesture represented by the gesture information is a household appliance control gesture, and/or controlling the household appliance according to the voice represented by the voice information when the recognized voice recognition result is that the voice represented by the voice information is household appliance control voice. The invention solves the technical problems of low control reliability and authenticity caused by the fact that the traditional control mode in the related technology easily causes the false triggering of the household appliance.
Description
Technical Field
The invention relates to the field of electric appliance control, in particular to a household appliance control method and device.
Background
In the prior art, the household appliances are generally controlled by a remote controller or a voice control mode, but in the existing control scheme, the remote controller is adopted, so that the control precision is poor due to the influence of distance and obstacles, the control level is low, and the corresponding control can be performed only by pressing keys. The voice control mode is easily affected by external noise, and due to the complexity of the home environment, false triggering caused by other sounds is very likely to happen, and the control accuracy is poor. In conclusion, the traditional household appliance control mode is low in identification accuracy, misoperation of the household appliance is easily caused, the use experience of a user is influenced, energy is wasted when the household appliance is triggered by mistake, and the service life of the household appliance is influenced.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides a household appliance control method and a household appliance control device, which at least solve the technical problems of low control reliability and authenticity caused by the fact that the conventional control mode in the related technology easily causes the false triggering of the household appliance.
According to an aspect of an embodiment of the present invention, there is provided a home appliance control method including: acquiring gesture information and voice information; using the gesture recognition result of gesture model discernment, using the speech model discernment speech recognition result, wherein, the gesture model is for using multiunit data to obtain through machine learning training, every group data in the multiunit data all includes: gesture information and sign whether the gesture that gesture information represented is the gesture recognition result of household electrical appliances control gesture, speech model is for using multiunit data to obtain through machine learning training, every group data in the multiunit data all include: the voice information and the voice recognition result which identifies whether the voice represented by the voice information is the household appliance control voice; and controlling the household appliance according to the gesture represented by the gesture information when the recognized gesture recognition result is that the gesture represented by the gesture information is a household appliance control gesture, and/or controlling the household appliance according to the voice represented by the voice information when the recognized voice recognition result is that the voice represented by the voice information is household appliance control voice.
Optionally, the gesture information includes at least one of: gesture image information and gesture sensing information.
Optionally, the gesture information is gesture image information, the gesture model is an image gesture model, and each set of data in multiple sets of data used by the image gesture model obtained through training includes: the gesture recognition method comprises gesture image information and a gesture recognition result for identifying whether a gesture represented by the gesture image information is a household appliance control gesture.
Optionally, the gesture information is gesture sensing information, the gesture model is a sensing gesture model, and each group of data in multiple groups of data used by the sensing gesture model obtained through training includes: the gesture recognition method comprises gesture sensing information and a gesture recognition result for identifying whether a gesture represented by the gesture sensing information is a household appliance control gesture.
Optionally, in a case that the gesture information includes gesture image information, the gesture image information is obtained by at least one of the following methods: the mode of taking pictures by a camera and the mode of capturing screens after video recording by a video recorder; and/or, under the condition that the gesture information comprises gesture sensing information, acquiring the gesture sensing information by at least one of the following modes: the manner in which the sensor senses.
Optionally, before controlling the home appliance according to the gesture represented by the gesture information and/or controlling the home appliance according to the voice represented by the voice information, the method further includes: determining the priority between a first control instruction for controlling the household appliance by the voice represented by the voice information and a second control instruction for controlling the household appliance by the gesture represented by the gesture information; and under the condition that the household appliances are controlled according to the gestures represented by the gesture information and the household appliances are controlled according to the voices represented by the voice information, selecting one of the household appliances with the highest priority to control.
Optionally, when the priority of the second control instruction is higher than that of the first control instruction, before selecting to control the household appliance through the gesture information, the method includes: judging whether voice control information is received or not, wherein the voice control information is used for determining whether gesture information is effective or not; and under the condition that the voice control information shows that the gesture information is effective, controlling the household appliance through the gesture information.
According to another aspect of the embodiments of the present invention, there is also provided a home appliance control apparatus including: the acquisition module is used for acquiring gesture information; the recognition module is used for recognizing a gesture recognition result by using a gesture model, wherein the gesture model is obtained by using a plurality of groups of data through machine learning training, and each group of data in the plurality of groups of data comprises: gesture information and a gesture recognition result for identifying whether the gesture represented by the gesture information is a household appliance control gesture; and the control module is used for controlling the household appliances according to the gestures represented by the gesture information under the condition that the recognized gesture recognition result is that the gestures represented by the gesture information are household appliance control gestures.
Optionally, the home appliance control device further includes: the gesture information is gesture image information, the gesture model is an image gesture model, and each group of data in a plurality of groups of data used by the image gesture model obtained through training comprises the following steps: the gesture recognition method comprises gesture image information and a gesture recognition result for identifying whether a gesture represented by the gesture image information is a household appliance control gesture.
Optionally, the home appliance control device further includes: the gesture information is gesture sensing information, the gesture model is a sensing gesture model, and each group of data in a plurality of groups of data used by the sensing gesture model obtained through training comprises: the gesture recognition method comprises gesture sensing information and a gesture recognition result for identifying whether a gesture represented by the gesture sensing information is a household appliance control gesture.
Optionally, the home appliance control device further includes: and the confirming module is used for confirming that the gesture represented by the gesture information is an effective gesture under the condition of receiving the voice control information for controlling the household appliance.
According to another aspect of the embodiments of the present invention, there is also provided a storage medium, where the storage medium includes a stored program, and when the program runs, the apparatus on which the storage medium is located is controlled to execute any one of the above-mentioned appliance control methods.
According to another aspect of the embodiments of the present invention, there is also provided a processor, configured to execute a program, where the program executes to perform the method described in any one of the above.
In the embodiment of the present invention, a home appliance is controlled by a gesture, a gesture recognition result is recognized by using a gesture model and a voice recognition result is recognized by using a voice model by acquiring gesture information and voice information, wherein the gesture model is obtained by using a plurality of groups of data through machine learning training, and each group of data in the plurality of groups of data includes: whether the gesture that gesture information and sign gesture information represented is the gesture recognition result of household electrical appliances control gesture, speech model is for using multiunit data to reach through machine learning training, and every group data in the multiunit data all include: whether the voice represented by the voice information and the identification voice information is a voice recognition result of the household appliance control voice or not; the household appliance is controlled according to the gesture represented by the gesture information under the condition that the gesture represented by the gesture information is a household appliance control gesture in the recognized gesture recognition result, and/or the household appliance is controlled according to the voice represented by the voice information under the condition that the voice represented by the voice information is household appliance control voice in the recognized voice recognition result, so that the technical effect of improving the accuracy of gesture control on the household appliance is achieved, and the technical problem that the control reliability and the authenticity are low due to the fact that the household appliance is easily triggered by mistake in the conventional control mode in the related technology is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a flowchart of a home appliance control method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a home appliance control device according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In accordance with an embodiment of the present invention, there is provided an embodiment of a method for controlling an appliance, it should be noted that the steps illustrated in the flowchart of the accompanying drawings may be executed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowchart, in some cases, the steps illustrated or described may be executed in an order different from that herein.
Fig. 1 is a flowchart of a household appliance control method according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
step S102, acquiring gesture information and voice information;
step S104, recognizing a gesture recognition result by using a gesture model, and recognizing a voice recognition result by using a voice model, wherein the gesture model is obtained by using a plurality of groups of data through machine learning training, and each group of data in the plurality of groups of data comprises: whether the gesture that gesture information and sign gesture information represented is the gesture recognition result of household electrical appliances control gesture, speech model is for using multiunit data to reach through machine learning training, and every group data in the multiunit data all include: whether the voice represented by the voice information and the identification voice information is a voice recognition result of the household appliance control voice or not;
and S106, controlling the household appliance according to the gesture represented by the gesture information when the recognized gesture recognition result is that the gesture represented by the gesture information is a household appliance control gesture, and/or controlling the household appliance according to the voice represented by the voice information when the recognized voice recognition result is that the voice represented by the voice information is household appliance control voice.
In the embodiment of the invention, gestures are adopted to control household appliances, gesture information and voice information are obtained, gesture recognition results are recognized by using a gesture model, and voice recognition results are recognized by using a voice model, wherein the gesture model is obtained by using multiple groups of data through machine learning training, and each group of data in the multiple groups of data comprises: whether the gesture that gesture information and sign gesture information represented is the gesture recognition result of household electrical appliances control gesture, speech model is for using multiunit data to reach through machine learning training, and every group data in the multiunit data all include: whether the voice represented by the voice information and the identification voice information is a voice recognition result of the household appliance control voice or not; the household appliance is controlled according to the gesture represented by the gesture information under the condition that the gesture represented by the gesture information is a household appliance control gesture in the recognized gesture recognition result, and/or the household appliance is controlled according to the voice represented by the voice information under the condition that the voice represented by the voice information is household appliance control voice in the recognized voice recognition result, so that the technical effect of improving the accuracy of gesture control on the household appliance is achieved, and the technical problem that the control reliability and the authenticity are low due to the fact that the household appliance is easily triggered by mistake in the conventional control mode in the related technology is solved.
When the gesture information is obtained, the gesture information in the target range is obtained through information acquisition equipment such as a sensor, a camera, a video recorder and the like. Because the information acquisition equipment is easily influenced by external environmental conditions, the problems of dead angles of acquisition, repeated acquisition and the like can occur, so that the target range can be a range in a preset area, namely, a user can reasonably adjust the target range of the information acquisition equipment according to the spatial pattern, the placement position of household appliances, the installation position of the information acquisition equipment and the like. In addition, the target range also includes a range which can be detected by the information acquisition equipment and is not limited by external conditions. Acquiring gesture information in a target range at information acquisition equipment, wherein the gesture information at least comprises the following components: gesture image information, gesture sensing information, and the like. For example, the user may obtain gesture sensing information through a sensor, wherein the sensor may be a light-sensitive sensor, a pressure-sensitive sensor, or the like, and the sensor serves as a detection device capable of obtaining gesture information of the user and converting the gesture information into an electrical signal or other desired information output form. In addition, images or video information of the user gestures can be acquired through a camera, a video recorder and the like, and feature data information in the images or the video information of the user gestures can be extracted.
The above description further includes preprocessing the acquired gesture information, including denoising and filtering, and filtering out some interference signals that are useless for gesture recognition in advance.
Before a gesture recognition result is recognized by using the gesture model, the gesture model needs to be built, and then the built gesture model is trained by using multiple groups of data in a machine learning mode, wherein the multiple groups of data comprise gesture information and a gesture recognition result, and the gesture recognition result is whether a gesture represented by the gesture identification information is a household appliance control gesture. And establishing the relevance between the gesture information and the gesture recognition result through training the constructed gesture model. In addition, when a large number of groups of data are trained, wrong gesture recognition is continuously corrected, for example, an algorithm is adjusted, manual setting is carried out, and therefore the recognition accuracy of the gesture model is effectively improved.
Since the gesture information includes at least: gesture image information, gesture sensing information and the like, namely, training of different gesture information can be realized by selecting corresponding algorithms, and a gesture model corresponding to the gesture information is obtained. For example, when the gesture information is gesture image information and the gesture model is an image gesture model, each group of data in the multiple groups of data used for training the image gesture model includes: the gesture image information and the gesture represented by the identification gesture image information are the gesture recognition result of the household appliance control gesture; when gesture information is gesture response information, the gesture model is response gesture model, and the training reachs that every group data in the multiunit data that response gesture model used all includes: and whether the gesture represented by the gesture sensing information and the identification gesture sensing information is a gesture recognition result of the household appliance control gesture or not.
When a gesture recognition result is recognized by using the gesture model, the user completes the gesture action each time, the information acquisition equipment acquires gesture information related to the gesture action, and then inputs the gesture information into the corresponding gesture model to obtain a gesture recognition result, namely whether the gesture represented by the gesture information and the identification gesture information is a household appliance control gesture or not. If the gesture model identifies gesture information, namely the gesture is a household appliance control gesture, the gesture information is effective, and the household appliance is controlled according to the gesture represented by the gesture information; if the gesture model cannot recognize gesture information or the gesture represented by the gesture information is not a household appliance control gesture, the gesture information is invalid, and household appliances cannot be controlled according to the gesture information. The gestures and the gesture information are in one-to-one correspondence, and each gesture can be represented by the uniquely determined gesture information, so that the household appliance is controlled.
Optionally, the gesture information includes at least one of: gesture image information and gesture sensing information.
The gesture of the user can be acquired by the information acquisition device, and the gesture information can be gesture image information or gesture sensing information due to different acquisition modes. For example, the gesture image information may be a gesture position (a position relative to a certain reference object) in an image or picture acquired by a camera, a gesture shape and size (for example, an opening range of a finger or a change in gripping and releasing of a palm), or a pixel point displacement occurring on the acquired image due to a gesture change. The gesture sensing information can be obtained by various sensors, for example, the pressure-sensitive sensor can determine the gesture sensing information according to the pressure generated by the gesture, and the photosensitive sensor can determine the gesture sensing information according to the light signal change caused by the change generated by the gesture.
Optionally, the gesture information is gesture image information, the gesture model is an image gesture model, and each group of data in the multiple groups of data used for training the image gesture model includes: and the gesture image information and the gesture represented by the identification gesture image information are the gesture recognition result of the household appliance control gesture.
When the gesture information is gesture image information, some ornaments, artware, objects similar to gestures and the like are inevitably collected due to the complexity of a home environment, however, the objects are not real gestures, and the gesture image information can be accurately identified through the image gesture model, and whether the gesture represented by the gesture image is a household appliance control gesture or not is identified. The image gesture model is trained by machine learning through a large amount of training data to obtain a corresponding image gesture model, and the training data comprises gesture image information and a gesture recognition result corresponding to the gesture image information. The image gesture model can accurately identify gesture identification results corresponding to the input gesture image information.
Optionally, the gesture information is gesture response information, and the gesture model is response gesture model, and the training reachs that every group data in the multiunit data that response gesture model used all includes: and whether the gesture represented by the gesture sensing information and the identification gesture sensing information is a gesture recognition result of the household appliance control gesture or not.
When the gesture information is gesture sensing information, the corresponding sensing gesture model is obtained by training the sensing gesture model through a large amount of training data through machine learning, and the sensing gesture model can accurately recognize the gesture recognition result corresponding to the input gesture sensing information.
Optionally, in a case that the gesture information includes gesture image information, the gesture image information is acquired by at least one of the following manners: the mode of taking pictures by a camera and the mode of capturing screens after video recording by a video recorder; and/or, in the case that the gesture information includes gesture sensing information, acquiring the gesture sensing information by at least one of the following methods: the manner in which the sensor senses.
The above-mentioned mode of obtaining the gesture image information can adopt a mode of taking pictures by a camera, a mode of capturing a screen after video recording by a video recorder, a mode of obtaining an infrared image by an infrared camera, and can also adopt image acquisition equipment such as a miniature camera and the like to obtain the gesture image information. In the above manner of acquiring the gesture sensing information, a manner of sensing by a sensor may be adopted, wherein the sensor may include multiple types, for example, a photosensitive sensor, a pressure-sensitive sensor, a thermal-sensitive sensor, and the like. For example, a pressure-sensitive sensor is used for a home appliance, and in this case, a user may apply pressure to the home appliance by using a gesture in a target area, and the pressure-sensitive sensor of the home appliance may be operated in combination with the gesture for a predetermined time, such as the number of times the pressure is sensed, the magnitude of the pressure, and the variation range of the pressure.
Optionally, before controlling the home appliance according to the gesture represented by the gesture information and/or controlling the home appliance according to the voice represented by the voice information, the method further includes: determining the priority between a first control instruction for controlling the household appliance by voice represented by the voice information and a second control instruction for controlling the household appliance by gesture represented by the gesture information; and under the condition that the household appliances are controlled according to the gestures represented by the gesture information and the household appliances are controlled according to the voices represented by the voice information, selecting one of the household appliances with the highest priority to control.
After the gesture information is determined as the home appliance control gesture, in order to improve the accuracy of controlling the home appliance by the gesture, the recognized gesture result may be further confirmed by the voice control information controlling the home appliance. For example, when the priority of the voice information is higher than that of the gesture information, the user makes a gesture, the gesture is identified by the gesture model to be an air conditioner starting gesture, the household appliance receives the voice information sent by the user at the moment, such as a deterministic reply of yes or yes, the air conditioner can automatically identify the voice control information of the user, and the gesture represented by the gesture information is confirmed to be an effective gesture, so that the air conditioner is controlled; if the user replies a negative answer such as no or no, the household appliance at the moment can send out a warning to the user, such as 'gesture error, please re-input'. In addition, the voice control information can be voice control which is consistent with the gesture expressed by the gesture information to the control of the household appliance, and as the example, the user makes a gesture, the gesture is obtained through gesture model recognition and is an air conditioner starting gesture, the user only needs to express the control information to be expressed by the gesture of the user through voice, and the household appliance can judge whether the gesture information is consistent with the voice control information or not. If the expressions are consistent, the gesture represented by the gesture information is confirmed to be an effective gesture, and then the air conditioner is controlled; if the expressions are inconsistent, the gesture represented by the gesture information is confirmed to be an invalid gesture, and then the household appliance sends out a warning to the user to remind the user of operating again.
Optionally, when the priority of the second control instruction is higher than that of the first control instruction, before selecting to control the household appliance through the gesture information, the method includes: judging whether voice control information is received or not, wherein the voice control information is used for determining whether the gesture information is effective or not; and under the condition that the voice control information shows that the gesture information is effective, controlling the household appliance through the gesture information.
The image information, the induction information and the voice control are combined, whether the voice control information is received or not is judged under the condition that the gesture in the target area is recognized, and the gesture is confirmed to be effective under the condition that the judgment result is yes, so that the control accuracy can be effectively improved. Therefore, the technical scheme of this embodiment can utilize in household electrical appliances such as air conditioner, refrigerator, electric fan, electric oven, electric heater, can improve the gesture to the accuracy of household electrical appliance control, improves the intellectuality of household electrical appliance for the user obtains more humanized life and experiences.
In addition, the embodiment of the invention can be applied to a complex household environment, can effectively shield false gesture recognition, enables the gesture expressing the real intention of a user to be expressed, improves the accuracy of controlling the air conditioner by the gesture, and greatly avoids the problems of false triggering of gesture recognition, misoperation of household appliances and the like.
Fig. 2 is a schematic structural diagram of a home appliance control device according to an embodiment of the present invention, and as shown in fig. 2, the home appliance control device 20 includes:
an obtaining module 22, configured to obtain gesture information; the recognition module 24 is connected to the obtaining module 22, and configured to recognize a gesture recognition result by using a gesture model, where the gesture model is obtained by using multiple sets of data through machine learning training, and each set of data in the multiple sets of data includes: the gesture information and the gesture represented by the identification gesture information are the gesture recognition result of the household appliance control gesture; and a control module 26, connected to the recognition module 24, for controlling the home appliance according to the gesture indicated by the gesture information when the recognized gesture recognition result is that the gesture indicated by the gesture information is a home appliance control gesture.
The household appliance control device identifies the gesture information through the gesture model, and achieves the purpose of accurately identifying the household appliance control gesture, so that the technical effect of improving the accuracy of gesture control of household appliances is achieved, and the technical problems that the conventional control mode easily causes mistaken triggering of household appliances in the related technology, and the control reliability and the authenticity are low are solved.
Optionally, the household electrical appliance control device 20 further includes: gesture information is gesture image information, and the gesture model is image gesture model, and the training reachs every group data in the multiunit data that image gesture model used and all includes: and the gesture image information and the gesture represented by the identification gesture image information are the gesture recognition result of the household appliance control gesture.
Optionally, the household electrical appliance control device 20 further includes: gesture information is gesture response information, and the gesture model is response gesture model, and the training reachs that every group data in the multiunit data that response gesture model used all includes: and whether the gesture represented by the gesture sensing information and the identification gesture sensing information is a gesture recognition result of the household appliance control gesture or not.
Optionally, the household electrical appliance control device 20 further includes: and the confirming module is used for confirming that the gesture represented by the gesture information is an effective gesture under the condition of receiving the voice control information for controlling the household appliance.
In an embodiment of the present invention, a storage medium is provided, where the storage medium includes a stored program, and when the program runs, a device on which the storage medium is located is controlled to execute any one of the above-mentioned appliance control methods.
In an embodiment of the present invention, a processor is provided, and is configured to execute a program, where the program executes to perform the method described in any one of the above.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, a division of a unit may be a division of a logic function, and an actual implementation may have another division, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or may not be executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (13)
1. A method for controlling an appliance, comprising:
acquiring gesture information and voice information;
using the gesture recognition result of gesture model discernment, using the speech model discernment speech recognition result, wherein, the gesture model is for using multiunit data to obtain through machine learning training, every group data in the multiunit data all includes: gesture information and sign whether the gesture that gesture information represented is the gesture recognition result of household electrical appliances control gesture, speech model is for using multiunit data to obtain through machine learning training, every group data in the multiunit data all include: the voice information and the voice recognition result which identifies whether the voice represented by the voice information is the household appliance control voice;
and controlling the household appliance according to the gesture represented by the gesture information when the recognized gesture recognition result is that the gesture represented by the gesture information is a household appliance control gesture, and/or controlling the household appliance according to the voice represented by the voice information when the recognized voice recognition result is that the voice represented by the voice information is household appliance control voice.
2. The method of claim 1, wherein the gesture information comprises at least one of: gesture image information and gesture sensing information.
3. The method of claim 2, wherein the gesture information is image gesture information, the gesture model is an image gesture model, and training each of the sets of data used by the image gesture model comprises: the gesture recognition method comprises gesture image information and a gesture recognition result for identifying whether a gesture represented by the gesture image information is a household appliance control gesture.
4. The method of claim 2, wherein the gesture information is gesture sensing information, the gesture model is a sensing gesture model, and training each of the plurality of sets of data used by the sensing gesture model comprises: the gesture recognition method comprises gesture sensing information and a gesture recognition result for identifying whether a gesture represented by the gesture sensing information is a household appliance control gesture.
5. The method of claim 2,
in the case that the gesture information includes gesture image information, the gesture image information is acquired by at least one of: the mode of taking pictures by a camera and the mode of capturing screens after video recording by a video recorder;
and/or the presence of a gas in the gas,
under the condition that the gesture information comprises gesture sensing information, acquiring the gesture sensing information through at least one of the following modes: the manner in which the sensor senses.
6. The method according to any one of claims 1 to 5, before controlling the home appliance according to the gesture represented by the gesture information and/or controlling the home appliance according to the voice represented by the voice information, further comprising:
determining the priority between a first control instruction for controlling the household appliance by the voice represented by the voice information and a second control instruction for controlling the household appliance by the gesture represented by the gesture information;
and under the condition that the household appliances are controlled according to the gestures represented by the gesture information and the household appliances are controlled according to the voices represented by the voice information, selecting one of the household appliances with the highest priority to control.
7. The method according to any one of claims 6, wherein when the second control instruction has a higher priority than the first control instruction, before selecting the home appliance to be controlled by the gesture information, the method comprises:
judging whether voice control information is received or not, wherein the voice control information is used for determining whether gesture information is effective or not;
and under the condition that the voice control information shows that the gesture information is effective, controlling the household appliance through the gesture information.
8. An appliance control device, comprising:
the acquisition module is used for acquiring gesture information;
the recognition module is used for recognizing a gesture recognition result by using a gesture model, wherein the gesture model is obtained by using a plurality of groups of data through machine learning training, and each group of data in the plurality of groups of data comprises: gesture information and a gesture recognition result for identifying whether the gesture represented by the gesture information is a household appliance control gesture;
and the control module is used for controlling the household appliances according to the gestures represented by the gesture information under the condition that the recognized gesture recognition result is that the gestures represented by the gesture information are household appliance control gestures.
9. The apparatus of claim 8, wherein the gesture information is image gesture information, the gesture model is an image gesture model, and each of the sets of data used for training the image gesture model comprises: the gesture recognition method comprises gesture image information and a gesture recognition result for identifying whether a gesture represented by the gesture image information is a household appliance control gesture.
10. The apparatus of claim 9, wherein the gesture information is gesture sensing information, the gesture model is a sensing gesture model, and each of the plurality of sets of data used by the sensing gesture model is trained to include: the gesture recognition method comprises gesture sensing information and a gesture recognition result for identifying whether a gesture represented by the gesture sensing information is a household appliance control gesture.
11. The apparatus of any one of claims 8 to 10, further comprising:
and the confirming module is used for confirming that the gesture represented by the gesture information is an effective gesture under the condition of receiving the voice control information for controlling the household appliance.
12. A storage medium comprising a stored program, wherein the program, when executed, controls a device on which the storage medium is provided to perform the appliance control method according to any one of claims 1 to 7.
13. A processor, characterized in that the processor is configured to run a program, wherein the program when running performs the method of any of claims 1 to 7.
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