CN111023470A - Air conditioner temperature adjusting method, medium, equipment and device - Google Patents
Air conditioner temperature adjusting method, medium, equipment and device Download PDFInfo
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- CN111023470A CN111023470A CN201911240597.6A CN201911240597A CN111023470A CN 111023470 A CN111023470 A CN 111023470A CN 201911240597 A CN201911240597 A CN 201911240597A CN 111023470 A CN111023470 A CN 111023470A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/52—Indication arrangements, e.g. displays
- F24F11/526—Indication arrangements, e.g. displays giving audible indications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2120/00—Control inputs relating to users or occupants
- F24F2120/10—Occupancy
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Abstract
The invention discloses an air conditioner temperature adjusting method, medium, equipment and device, wherein the method comprises the following steps: acquiring first audio data, and classifying the first audio data to generate a training set; extracting acoustic features corresponding to each audio data in the training set, and combining the acoustic features to generate corresponding combined features; inputting each combined feature in the training set into a long-term and short-term memory model for training an audio recognition model to obtain the audio recognition model; acquiring second audio data of an air conditioner user, and extracting combination characteristics corresponding to the second audio data; inputting the combination characteristics corresponding to the second audio data into the audio recognition model, judging the age group of the air conditioner user according to the output result of the audio recognition model, and adjusting the temperature of the air conditioner according to the age group of the air conditioner user; can adjust the temperature according to air conditioner user's age to prevent that special crowd from leading to the malaise because air conditioner temperature is low, improve user experience.
Description
Technical Field
The invention relates to the technical field of household appliance control, in particular to an air conditioner temperature adjusting method, a computer readable storage medium, computer equipment and an air conditioner temperature adjusting device.
Background
The temperature is controlled by an air conditioner, which is a common means for improving the living environment of modern people. In many situations (e.g., malls, meeting rooms, auditoriums, buses, etc.), the temperature is regulated by air conditioning.
However, in these situations, there are often elderly and children; because the immunity of the people is generally low, when the power of the air conditioner is too high and the temperature in the occasions is too low, diseases such as cold and the like are easily caused to the bodies of the special people.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the art described above. Therefore, an object of the present invention is to provide an air conditioner temperature adjusting method, which can adjust the temperature according to the age of the user of the air conditioner, so as to prevent the special people from being uncomfortable due to the low temperature of the air conditioner, and improve the user experience.
A second object of the invention is to propose a computer-readable storage medium.
A third object of the invention is to propose a computer device.
The fourth purpose of the invention is to provide an air conditioner temperature adjusting device.
In order to achieve the above object, an embodiment of a first aspect of the present invention provides an air conditioner temperature adjustment method, including the following steps: acquiring first audio data, and classifying the first audio data to generate a training set of a plurality of categories; extracting acoustic features corresponding to each audio data in the training set, and combining the acoustic features to generate corresponding combined features; inputting each combined feature in the training set into a long-term and short-term memory model for training an audio recognition model to obtain the audio recognition model; acquiring second audio data of an air conditioner user, and extracting combination characteristics corresponding to the second audio data; and inputting the combination characteristics corresponding to the second audio data into the audio recognition model, judging the age group of the air conditioner user according to the output result of the audio recognition model, and adjusting the temperature of the air conditioner according to the age group of the air conditioner user.
According to the air conditioner temperature adjusting method, first audio data are obtained and classified to generate a training set with a plurality of categories; secondly, extracting acoustic features corresponding to each audio data in the training set, and combining the acoustic features to generate combined features corresponding to each audio data; then, inputting each combined feature in the training set into a long-term and short-term memory model for training an audio recognition model to obtain the audio recognition model; then, second audio data of the air conditioner user are obtained, and combination features corresponding to the second audio data are extracted; then, the combined features corresponding to the second audio data are input into the audio recognition model, the age of the air conditioner user is judged according to the output result of the audio recognition model, and the temperature of the air conditioner is adjusted according to the age of the air conditioner user, so that the temperature is adjusted according to the age of the air conditioner user, discomfort caused by the fact that the temperature of the air conditioner is too low of a special crowd is prevented, and user experience is improved.
In addition, the air conditioner temperature adjusting method provided by the above embodiment of the invention may further have the following additional technical features:
optionally, the multi-dimensional MFCC features, the first derivatives corresponding to each-dimensional MFCC features, the second derivatives corresponding to each-dimensional MFCC features, the one-dimensional fundamental frequency estimate, and the one-dimensional energy features.
Optionally, the audio recognition model comprises two lstm layers and two fully connected layers.
To achieve the above object, a second embodiment of the present invention provides a computer-readable storage medium on which an air conditioner temperature adjustment program is stored, the air conditioner temperature adjustment program implementing the air conditioner temperature adjustment method as described above when executed by a processor.
According to the computer-readable storage medium of the embodiment of the invention, the air-conditioning temperature adjusting program is stored through the memory, so that the processor realizes the air-conditioning temperature adjusting method when executing the air-conditioning temperature adjusting program, the temperature is adjusted according to the age of an air-conditioning user, the discomfort of special people due to the fact that the air-conditioning temperature is too low is prevented, and the user experience is improved.
In order to achieve the above object, a third embodiment of the present invention provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the air conditioner temperature adjusting method as described above.
According to the computer equipment provided by the embodiment of the invention, the air-conditioning temperature adjusting program is stored through the memory, so that the processor realizes the air-conditioning temperature adjusting method when executing the computer program stored in the memory, and the temperature is adjusted according to the age of an air-conditioning user, so that the special people are prevented from causing discomfort due to the fact that the air-conditioning temperature is too low, and the user experience is improved.
In order to achieve the above object, a fourth aspect of the present invention provides an air conditioner temperature adjustment apparatus, including: the first acquisition module is used for extracting acoustic features corresponding to each piece of audio data in the training set and combining the acoustic features to generate corresponding combined features; the training module is used for inputting each combined feature in the training set into a long-short term memory model to train an audio recognition model so as to obtain the audio recognition model; the second acquisition module is used for acquiring second audio data of an air conditioner user and extracting combination characteristics corresponding to the second audio data; the identification module is used for inputting the combination characteristics corresponding to the second audio data into the audio identification model and judging the age bracket of the air conditioner user according to the output result of the audio identification model; and the adjusting module is used for adjusting the temperature of the air conditioner according to the age group of the air conditioner user.
According to the air conditioner temperature adjusting device provided by the embodiment of the invention, the first acquisition module is arranged for extracting the acoustic characteristics corresponding to each audio data in the training set and combining the acoustic characteristics to generate corresponding combined characteristics; the training module is used for inputting each combined feature in the training set into the long-term and short-term memory model to train the audio recognition model so as to obtain the audio recognition model; the second acquisition module is used for acquiring second audio data of the air conditioner user and extracting combination characteristics corresponding to the second audio data; the identification module is used for inputting the combination characteristics corresponding to the second audio data into the audio identification model and judging the age bracket of the air conditioner user according to the output result of the audio identification model; the adjusting module is used for adjusting the temperature of the air conditioner according to the age group of the user of the air conditioner; thereby realize adjusting the temperature according to air conditioner user's age to prevent that special crowd from leading to the malaise because the air conditioner temperature is low, improve user experience.
In addition, the air conditioner temperature adjusting device provided according to the above embodiment of the present invention may further have the following additional technical features:
optionally, the combined features comprise: the method comprises the steps of multi-dimensional MFCC features, first derivatives corresponding to the MFCC features in each dimension, second derivatives corresponding to the MFCC features in each dimension, one-dimensional fundamental frequency estimation and one-dimensional energy features.
Optionally, the audio recognition model comprises two lstm layers and two fully connected layers.
Drawings
Fig. 1 is a schematic flow chart of an air conditioner temperature adjusting method according to an embodiment of the present invention;
fig. 2 is a block diagram schematically illustrating an air conditioner temperature adjusting apparatus according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
In many occasions, if the temperature of the air conditioner is too low, the body of a special crowd is easy to be diseased; according to the air conditioner temperature adjusting method, first audio data are obtained and classified to generate a training set with a plurality of categories; secondly, extracting acoustic features corresponding to each audio data in the training set, and combining the acoustic features to generate combined features corresponding to each audio data; then, inputting each combined feature in the training set into a long-term and short-term memory model for training an audio recognition model to obtain the audio recognition model; then, second audio data of the air conditioner user are obtained, and combination features corresponding to the second audio data are extracted; then, the combined features corresponding to the second audio data are input into the audio recognition model, the age of the air conditioner user is judged according to the output result of the audio recognition model, and the temperature of the air conditioner is adjusted according to the age of the air conditioner user, so that the temperature is adjusted according to the age of the air conditioner user, discomfort caused by the fact that the temperature of the air conditioner is too low of a special crowd is prevented, and user experience is improved.
In order to better understand the above technical solutions, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
Referring to fig. 1, fig. 1 is a schematic flow chart of an air conditioner temperature adjusting method according to an embodiment of the present invention, as shown in fig. 1, the air conditioner temperature adjusting method includes the following steps:
s101, acquiring first audio data, and classifying the first audio data to generate a training set of multiple categories.
That is, audio data for training a model is acquired, and the acquired data is classified to generate a training set of a plurality of classes, so that the model is subsequently trained by the training set of the plurality of classes.
As an example, first, audio data of a large number of people of different ages are collected to obtain audio data corresponding to people of different ages, and then after the audio data are obtained, the audio data are classified according to different ages, and preferably, the audio data can be divided according to the ages into: class A (1-15 years old), class B (16-65 years old), and class C (66 years old and older).
S102, extracting acoustic features corresponding to each audio data in the training set, and combining the acoustic features to generate corresponding combined features.
That is to say, the acoustic features corresponding to each audio data in a plurality of classification training sets are extracted, it can be understood that when a person is in different age groups, the features of the sound of the person are different (for example, the energy and fundamental frequency of the sound in a specific frequency band), and therefore, the features with the differences can be extracted to complete the extraction of the acoustic features; and then, combining according to the extracted acoustic features to generate combined features of corresponding audio data so as to improve the recognition effect of a subsequent audio recognition model.
Wherein, the combination mode of the combination characteristics can be various.
As an example, the combined features include multi-dimensional MFCC features, first derivatives corresponding to each-dimensional MFCC features, second derivatives corresponding to each-dimensional MFCC features, one-dimensional fundamental frequency estimates, and one-dimensional energy features.
S103, inputting each combined feature in the training set into the long-term and short-term memory model to train the audio recognition model so as to obtain the audio recognition model.
That is, after the combined features are obtained, each combined feature in the training set is input into the long-short term memory model, so that the long-short term memory model is used for training the audio recognition model, and finally the audio recognition model is obtained through training.
As an example, the combined features corresponding to each audio data are input into an lstm network (long-short term memory model) for training of the audio recognition model to obtain the audio recognition model.
The audio recognition model can be set in various ways.
As an example, the audio recognition model includes two lstm layers and two fully connected layers.
It should be noted that, in some embodiments, in order to prevent the audio recognition model from being over-fitted, a drop operation is further added to the audio recognition model to prevent the audio recognition model from being over-fitted.
In some embodiments, in the training process of the audio recognition model, the loss function adopts cross entropy loss, and meanwhile, parameters of the audio recognition model are updated by adopting an Adam algorithm, and iterative training is performed on the basis of the parameters to obtain a final audio recognition model.
And S104, acquiring second audio data of the air conditioner user, and extracting combination characteristics corresponding to the second audio data.
That is to say, after the audio recognition model is trained, in a specific using process, first, second audio data of the air conditioner user is acquired, and corresponding combination features of the second audio data are extracted according to the second audio data.
As an example, first, a sound receiver and an adjusting device are installed in an air conditioner; then, second audio data of the user are obtained through the sound receiver, and the second audio data are sent to the controller, so that the controller extracts corresponding acoustic features according to the second audio data, and combines the acoustic features to complete extraction of combined features.
And S105, inputting the combination characteristics corresponding to the second audio data into the audio recognition model, judging the age group of the air conditioner user according to the output result of the audio recognition model, and adjusting the temperature of the air conditioner according to the age group of the air conditioner user.
That is to say, after the combination feature corresponding to the second audio data is extracted, the combination feature is input into the audio recognition model, so that the audio recognition model outputs a result according to the combination feature, then, the age group of the current air-conditioning user can be judged according to the result output by the audio recognition model, and the temperature of the air conditioner is adjusted according to the age group of the air-conditioning user, so as to prevent discomfort of people of a special age caused by the fact that the temperature of the air conditioner is too low.
As an example, first, after second audio data of a user is acquired, a sound receiver installed inside an air conditioner sends the second audio data to a controller, and the controller extracts acoustic features corresponding to the second audio data and then combines the second audio data to obtain combined features; then, inputting the combined features into a trained audio recognition model, and outputting a result according to the combined features through the audio recognition model; the controller judges the age of the current user according to the output result (for example, judges whether the current user includes people at the age of 1-15 years or 66 years or more), and then adjusts the air-conditioning temperature to 26-28 ℃ through the temperature adjusting device when the judgment result of the controller is that the current user includes the characteristic people group, so as to prevent the special people group from generating physical discomfort in the environment with too low air-conditioning temperature.
In summary, according to the air conditioner temperature adjustment method of the embodiment of the present invention, first audio data is obtained, and the first audio data is classified to generate a training set of multiple categories; secondly, extracting acoustic features corresponding to each audio data in the training set, and combining the acoustic features to generate combined features corresponding to each audio data; then, inputting each combined feature in the training set into a long-term and short-term memory model for training an audio recognition model to obtain the audio recognition model; then, second audio data of the air conditioner user are obtained, and combination features corresponding to the second audio data are extracted; then, the combined features corresponding to the second audio data are input into the audio recognition model, the age of the air conditioner user is judged according to the output result of the audio recognition model, and the temperature of the air conditioner is adjusted according to the age of the air conditioner user, so that the temperature is adjusted according to the age of the air conditioner user, discomfort caused by the fact that the temperature of the air conditioner is too low of a special crowd is prevented, and user experience is improved.
In order to achieve the above embodiments, a second aspect embodiment of the present invention proposes a computer-readable storage medium on which an air conditioner temperature adjustment program is stored, the air conditioner temperature adjustment program implementing the air conditioner temperature adjustment method as described above when executed by a processor.
According to the computer-readable storage medium of the embodiment of the invention, the air-conditioning temperature adjusting program is stored through the memory, so that the processor realizes the air-conditioning temperature adjusting method when executing the air-conditioning temperature adjusting program, the temperature is adjusted according to the age of an air-conditioning user, the discomfort of special people due to the fact that the air-conditioning temperature is too low is prevented, and the user experience is improved.
In order to achieve the above embodiments, a third aspect of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the air conditioner temperature adjusting method as described above.
According to the computer equipment provided by the embodiment of the invention, the air-conditioning temperature adjusting program is stored through the memory, so that the processor realizes the air-conditioning temperature adjusting method when executing the computer program stored in the memory, and the temperature is adjusted according to the age of an air-conditioning user, so that the special people are prevented from causing discomfort due to the fact that the air-conditioning temperature is too low, and the user experience is improved.
In order to implement the above embodiments, an embodiment of the present invention provides an air conditioner temperature adjustment device, and fig. 2 is a block diagram of the air conditioner temperature adjustment device according to the embodiment of the present invention, as shown in fig. 2, the air conditioner temperature adjustment device includes:
a first acquisition module 10, a training module 20, a second acquisition module 30, a recognition module 40, and an adjustment module 50.
The first obtaining module 10 is configured to extract an acoustic feature corresponding to each piece of audio data in a training set, and combine the acoustic features to generate a corresponding combined feature;
the training module 20 is configured to input each combined feature in the training set into the long-term and short-term memory model for training the audio recognition model to obtain the audio recognition model;
the second obtaining module 30 is configured to obtain second audio data of the air conditioner user, and extract a combination feature corresponding to the second audio data;
the recognition module 40 is configured to input the combination feature corresponding to the second audio data into the audio recognition model, and determine the age bracket of the air conditioner user according to an output result of the audio recognition model;
the adjusting module 50 is used for adjusting the temperature of the air conditioner according to the age group of the user of the air conditioner.
In some embodiments, the combined features include: the method comprises the steps of multi-dimensional MFCC features, first derivatives corresponding to the MFCC features in each dimension, second derivatives corresponding to the MFCC features in each dimension, one-dimensional fundamental frequency estimation and one-dimensional energy features.
In some embodiments, the audio recognition model includes two lstm layers and two fully connected layers.
It should be noted that the above description about the air conditioning temperature adjusting method in fig. 1 is also applicable to the air conditioning temperature adjusting device, and is not repeated herein.
In summary, according to the air conditioner temperature adjustment apparatus in the embodiment of the present invention, the first obtaining module is configured to extract the acoustic features corresponding to each audio data in the training set, and combine the acoustic features to generate corresponding combined features; the training module is used for inputting each combined feature in the training set into the long-term and short-term memory model to train the audio recognition model so as to obtain the audio recognition model; the second acquisition module is used for acquiring second audio data of the air conditioner user and extracting combination characteristics corresponding to the second audio data; the identification module is used for inputting the combination characteristics corresponding to the second audio data into the audio identification model and judging the age bracket of the air conditioner user according to the output result of the audio identification model; the adjusting module is used for adjusting the temperature of the air conditioner according to the age group of the user of the air conditioner; thereby realize adjusting the temperature according to air conditioner user's age to prevent that special crowd from leading to the malaise because the air conditioner temperature is low, improve user experience.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
In the description of the present invention, it is to be understood that the terms "first", "second" and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the present invention, unless otherwise expressly stated or limited, the first feature "on" or "under" the second feature may be directly contacting the first and second features or indirectly contacting the first and second features through an intermediate. Also, a first feature "on," "over," and "above" a second feature may be directly or diagonally above the second feature, or may simply indicate that the first feature is at a higher level than the second feature. A first feature being "under," "below," and "beneath" a second feature may be directly under or obliquely under the first feature, or may simply mean that the first feature is at a lesser elevation than the second feature.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above should not be understood to necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (8)
1. The air conditioner temperature adjusting method is characterized by comprising the following steps:
acquiring first audio data, and classifying the first audio data to generate a training set of a plurality of categories;
extracting acoustic features corresponding to each audio data in the training set, and combining the acoustic features to generate corresponding combined features;
inputting each combined feature in the training set into a long-term and short-term memory model for training an audio recognition model to obtain the audio recognition model;
acquiring second audio data of an air conditioner user, and extracting combination characteristics corresponding to the second audio data;
and inputting the combination characteristics corresponding to the second audio data into the audio recognition model, judging the age group of the air conditioner user according to the output result of the audio recognition model, and adjusting the temperature of the air conditioner according to the age group of the air conditioner user.
2. The air conditioner temperature adjusting method as claimed in claim 1, wherein the combination of features includes: the method comprises the steps of multi-dimensional MFCC features, first derivatives corresponding to the MFCC features in each dimension, second derivatives corresponding to the MFCC features in each dimension, one-dimensional fundamental frequency estimation and one-dimensional energy features.
3. The air conditioner temperature adjusting method of claim 1, wherein the audio recognition model includes two lstm layers and two full connection layers.
4. A computer-readable storage medium, on which an air conditioner temperature adjustment program is stored, the air conditioner temperature adjustment program, when executed by a processor, implementing the air conditioner temperature adjustment method according to any one of claims 1 to 3.
5. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor, when executing the program, implements the air conditioner temperature adjustment method according to any one of claims 1-3.
6. An air conditioner temperature adjusting device, comprising:
the first acquisition module is used for extracting acoustic features corresponding to each piece of audio data in the training set and combining the acoustic features to generate corresponding combined features;
the training module is used for inputting each combined feature in the training set into a long-short term memory model to train an audio recognition model so as to obtain the audio recognition model;
the second acquisition module is used for acquiring second audio data of an air conditioner user and extracting combination characteristics corresponding to the second audio data;
the identification module is used for inputting the combination characteristics corresponding to the second audio data into the audio identification model and judging the age bracket of the air conditioner user according to the output result of the audio identification model;
and the adjusting module is used for adjusting the temperature of the air conditioner according to the age group of the air conditioner user.
7. The air conditioner temperature adjusting apparatus as claimed in claim 6, wherein the combination of features includes: the method comprises the steps of multi-dimensional MFCC features, first derivatives corresponding to the MFCC features in each dimension, second derivatives corresponding to the MFCC features in each dimension, one-dimensional fundamental frequency estimation and one-dimensional energy features.
8. The air conditioner thermostat of claim 6 wherein said audio recognition model includes two lstm layers and two fully connected layers.
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