Voice bird repelling method, device and equipment and storage medium
By finding awakening words based on bird habit characteristics and determining bird types, timely monitoring and accurate bird repelling of bird sounds is achieved, and the existing bird repelling technology is solved.
Patent Information
- Application Number
- CN202411823663.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-10
- Publication Date
- 2025-03-21
AI Technical Summary
The existing bird repelling technology is inefficient and the equipment operation life is affected by noise and continuous playback. How to monitor bird sounds in a timely and effective manner to accurately repel birds has become a challenge.
By finding the target awakening words based on the current habit characteristics of the bird, determining whether to turn on monitoring, and determining the type of bird corresponding to the bird sound clip after turning on monitoring, so as to accurately play the bird's feared sound to drive away birds.
It realizes timely and effectively monitoring bird sounds, accurately playing the sounds of birds fear, improving the efficiency and accuracy of bird repelling, and reducing the noise and burden of equipment operation.
Smart Images
Figure CN119673177A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of bird-repelling technology, and in particular to a method, device, equipment and storage medium for repelling birds by voice. Background Art
[0002] At present, bird repellents usually adopt simple and crude methods, such as using laser patrols to stimulate the eyes of birds to repel birds. This method requires birds to face the bird repellent and the bird repellent can identify the location of the birds. In fact, most laser bird repellents do not have the ability to accurately locate birds, and the efficiency of bird repellent is low. By using intelligent pan-tilts to identify birds and then drive them away, the price is relatively expensive. At the same time, using windmills to repel birds or raptor models to repel birds, the sound and reflection caused by the rotation or the visual effect of the raptor model are used to repel birds. After the birds adapt, the repelling effect gradually weakens, and the range of action is also limited by the installation location of the equipment. In addition, some products record the sounds that different birds are afraid of and play them in a loop to repel birds. This solution needs to be played continuously regardless of whether there are birds or not. On the one hand, there is noise for people, and on the other hand, continuous playback has posed a great challenge to the operating life of the equipment. Therefore, how to monitor the sounds of birds in a timely and effective manner, so as to accurately play the sounds that birds are afraid of to repel birds, has become an urgent problem to be solved. Summary of the invention
[0003] The main purpose of this application is to provide a voice bird-repelling method, device, equipment and storage medium, aiming to solve the technical problem of how to monitor bird sounds in a timely and effective manner, so as to accurately play the sounds that birds are afraid of to repel birds.
[0004] To achieve the above purpose, the present application provides a method for driving away birds by voice, which comprises the following steps:
[0005] Searching for a target wake-up word from a preset wake-up word library according to the current habits and characteristics of various birds, and determining whether to start monitoring based on the current bird sound and the target wake-up word;
[0006] After monitoring is turned on, the bird type corresponding to the recorded bird sound clip is determined, and the target bird-repelling voice is determined according to the bird type.
[0007] Optionally, before the step of searching for a target wake-up word from a preset wake-up word library according to the current habit characteristics of various birds, and determining whether to start monitoring according to the current bird sound and the target wake-up word, the method further includes:
[0008] Collecting bird sounds and habit characteristics of various birds, and constructing a full bird sound information vector library based on the bird sounds and habit characteristics;
[0009] Clustering the full bird sound information vector library to obtain a bird sound set of various birds with different habit characteristics;
[0010] A preset wake-up word library for various birds with different habit characteristics is determined according to the bird sound collection.
[0011] Optionally, the step of collecting bird sounds and habit characteristics of various birds, and constructing a full bird sound information vector library according to the bird sounds and habit characteristics, specifically includes:
[0012] Collecting bird sounds and habit characteristics of various birds, and cutting and segmenting the bird sounds to obtain a collection of sounds of various birds;
[0013] Extracting vector features from the sound set using the Mel-frequency cepstral coefficient method to obtain sound feature vectors of various birds;
[0014] Quantifying the habit characteristics to obtain a habit characteristic vector;
[0015] A complete bird sound information vector library is constructed based on the sound feature vector and the habit feature vector.
[0016] Optionally, the step of determining, according to the bird sound set, a preset wake-up word library for various birds with different habit characteristics specifically includes:
[0017] Determine the bird sound frequency corresponding to the bird sound set of the various birds under each habit characteristic;
[0018] Sorting the frequencies of the bird sounds to obtain sorting results under different habit characteristics;
[0019] Selecting wake-up words of various birds with different habit characteristics from the bird sound collection according to the sorting result;
[0020] A preset wake-up word library for various birds with different habit characteristics is constructed according to the wake-up word.
[0021] Optionally, the step of constructing a preset wake-up word library for various birds with different habit characteristics according to the wake-up word specifically includes:
[0022] The initial neural network model is trained according to the bird sounds, habit characteristics, the wake-up words and the wake-up word sound samples of the various birds to obtain a target neural network model;
[0023] The preset wake-up word library of various birds under different habit characteristics is determined according to the target neural network model.
[0024] Optionally, after starting monitoring, the step of determining the bird type corresponding to the recorded bird sound clip, and determining the target bird-repelling voice according to the bird type specifically includes:
[0025] After turning on monitoring, determine the type of bird that the recorded bird sound clip corresponds to;
[0026] Collecting initial bird-repelling voices corresponding to various bird species, and classifying the initial bird-repelling voices to obtain classified bird-repelling voices corresponding to various bird species;
[0027] A target bird-repelling voice is selected from the classified bird-repelling voices according to the bird type.
[0028] Optionally, after starting monitoring, the step of determining the bird type corresponding to the recorded bird sound clip specifically includes:
[0029] Training an initial bird sound classification model according to the full bird sound information vector library to obtain a target bird sound classification model;
[0030] After monitoring is turned on, the current habit characteristics and the recorded bird sound clips are input into the target bird sound classification model to obtain the corresponding bird type.
[0031] In addition, to achieve the above purpose, the present application also provides a voice bird-repelling device, the voice bird-repelling device comprising:
[0032] A monitoring judgment module is used to search for a target wake-up word from a preset wake-up word library according to the current habit characteristics of various birds, and to judge whether to start monitoring according to the current bird sound and the target wake-up word;
[0033] The voice bird-repelling module is used to determine the bird type corresponding to the recorded bird sound clip after monitoring is turned on, and determine the target bird-repelling voice according to the bird type.
[0034] In addition, to achieve the above-mentioned purpose, the present application also proposes a voice bird-repelling device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the voice bird-repelling method described above.
[0035] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the voice bird-repelling method described above are implemented.
[0036] This application searches for the target wake-up word from the preset wake-up word library according to the current habit characteristics of various birds, and determines whether to turn on monitoring based on the current bird sound and the target wake-up word. After turning on monitoring, the bird type corresponding to the recorded bird sound clip is determined, and the target bird-repelling voice is determined according to the bird type. This application searches for the target wake-up word from the preset wake-up word library according to the current habit characteristics, and can obtain the target wake-up word for various birds under the current habit characteristics, and determines whether to turn on monitoring based on the current bird sound and the target wake-up word. It can turn on monitoring in a timely and effective manner. After turning on monitoring, the bird type corresponding to the recorded bird sound clip is determined. Compared with the existing looping playback of bird fear sounds, the above method of this application can monitor bird sounds in a timely and effective manner, so as to accurately play the target bird-repelling voice that birds fear according to the corresponding bird type to drive away birds. BRIEF DESCRIPTION OF THE DRAWINGS
[0037] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.
[0038] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.
[0039] Figure 1 This is a flow chart of the first embodiment of the voice bird-repelling method of the present application;
[0040] Figure 2 A schematic diagram of a flow chart of determining whether to start monitoring in an embodiment of a method for driving away birds with voice according to the present application;
[0041] Figure 3 This is a flow chart of the second embodiment of the voice bird-repelling method of the present application;
[0042] Figure 4 A schematic diagram of the process of constructing a preset wake-up word library in an embodiment of the voice bird-repelling method of the present application;
[0043] Figure 5 This is a flow chart of the third embodiment of the method for driving away birds with voice;
[0044] Figure 6 This is a structural block diagram of the first embodiment of the voice bird-repelling device of the present application;
[0045] Figure 7 It is a structural diagram of a voice bird-repelling device in a hardware operating environment involved in an embodiment of the present application.
[0046] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION
[0047] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.
[0048] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.
[0049] The main solution of the embodiment of the present application is: to search for the target wake-up word from the preset wake-up word library according to the current habit characteristics of various birds, and to determine whether to turn on monitoring according to the current bird sound and the target wake-up word; after turning on monitoring, determine the bird type corresponding to the recorded bird sound clip, and determine the target bird-repelling voice according to the bird type.
[0050] At present, bird repellents usually adopt simple and crude methods, such as using laser patrols to stimulate the eyes of birds to repel birds. This bird repellent method requires the birds to face the bird repellent and the bird repellent to identify the position of the birds. In fact, most laser bird repellents do not have the ability to accurately locate birds, and the bird repellent efficiency is low. By using an intelligent gimbal to identify birds and then repel them, the price is relatively expensive. At the same time, windmills or raptor models are used to repel birds. The sound and reflection caused by the rotation or the visual effects of the raptor model are used to repel birds. After the birds adapt, the repelling effect gradually weakens, and the range of action is also limited by the installation location of the equipment. In addition, some products record the sounds that different birds are afraid of and play them in a loop to repel birds. This solution needs to be played continuously regardless of whether there are birds or not. On the one hand, there is noise for people, and on the other hand, continuous playback has posed a great challenge to the operating life of the equipment.
[0051] This application searches for the target wake-up word from the preset wake-up word library according to the current habit characteristics of various birds, and determines whether to turn on monitoring based on the current bird sound and the target wake-up word. After turning on monitoring, the bird type corresponding to the recorded bird sound clip is determined, and the target bird-repelling voice is determined according to the bird type. This application searches for the target wake-up word from the preset wake-up word library according to the current habit characteristics, and can obtain the target wake-up word for various birds under the current habit characteristics, and determines whether to turn on monitoring based on the current bird sound and the target wake-up word. It can turn on monitoring in a timely and effective manner. After turning on monitoring, the bird type corresponding to the recorded bird sound clip is determined. Compared with the existing looping playback of bird fear sounds, the above method of this application can monitor bird sounds in a timely and effective manner, so as to accurately play the target bird-repelling voice that birds fear according to the corresponding bird type to drive away birds.
[0052] It should be noted that the execution subject of this application can be a computing service device with data processing, network communication and program running functions, such as a computer, or an electronic device capable of realizing the above functions, a voice bird-repelling device, etc. The following takes the voice bird-repelling device as an example to illustrate this embodiment and the following embodiments.
[0053] Based on this, the present application embodiment provides a method for driving away birds with voice, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the voice bird-repelling method of the present application.
[0054] In this embodiment, the voice bird-repelling method comprises the following steps:
[0055] Step S10: searching for a target wake-up word from a preset wake-up word library according to the current habit characteristics of various birds, and determining whether to start monitoring according to the current bird sound and the target wake-up word.
[0056] It is understandable that the current habit characteristics are the habit characteristics of various species of birds corresponding to the time and geographical location of the microphone. The types of birds may include sparrows, parrots, thrushes, larks, etc. The habit characteristics may include seasons, surrounding environment, climate, geographical location, etc.
[0057] It should be understood that the preset wake-up word library may contain pre-built wake-up words for various birds under different habit characteristics. Taking sparrows as an example, the wake-up word library contains the wake-up words for sparrows under all possible seasons, environments, climates, and geographical locations. The wake-up word refers to the word that wakes up the microphone in the bird activity area for monitoring. After determining the current habit characteristics, the target wake-up words for various birds under the current habit characteristics can be found from the preset wake-up word library.
[0058] In a specific implementation, it can be determined whether to turn on monitoring based on the current bird sound and the target wake-up word, that is, whether to monitor and record through the microphone set in the bird activity area.
[0059] Furthermore, in order to effectively determine whether to turn on monitoring, in this embodiment, the step S20 includes: searching for target wake-up words corresponding to various birds from a preset wake-up word library according to current habit characteristics; matching the current bird sound with the target wake-up word to obtain a matching result; when the matching result is a match passed, determining to turn on monitoring.
[0060] It is understandable that after determining the target wake-up words corresponding to various birds, the current bird sound and the target wake-up word can be matched, that is, to determine whether the current bird sound has the target wake-up word. The current bird sound refers to the bird sound in the bird activity area at the current moment. When the matching result is a pass, that is, when the current bird sound has the target wake-up word, it is determined that the microphone is turned on for monitoring; when the current bird sound does not have the target wake-up word, the microphone is in a dormant state.
[0061] In the specific implementation, refer to Figure 2 , Figure 2 This is a flow chart of determining whether to start monitoring in an embodiment of the voice bird-repelling method of the present application. Figure 2 As shown, the habit characteristics of the surrounding environment, climate, geographical location, etc. of the bird activity area can be obtained first, and the habit characteristic of date information can also be obtained. Then, based on this information, the device selects the target wake-up words corresponding to various birds from the preset wake-up word library, and then enters the standby wake-up collection state, and then matches the current bird sound with the target wake-up word to determine whether it is awakened. If so, the monitoring is started, if not, it ends and the microphone is in sleep mode.
[0062] Step S30: After monitoring is started, the bird type corresponding to the recorded bird sound clip is determined, and the target bird-repelling voice is determined according to the bird type.
[0063] It should be understood that after monitoring is turned on, the bird sound clip recorded by the microphone can be obtained, and the bird type corresponding to the bird sound clip can be determined, and the target bird-repelling voice corresponding to the bird type can be determined, and the target bird-repelling voice can be played through the speakers in the bird activity area, so that the target driving voice that birds are afraid of can be played to repel birds.
[0064] This embodiment searches for the target wake-up word from the preset wake-up word library according to the current habit characteristics of various birds, and determines whether to turn on monitoring based on the current bird sound and the target wake-up word. After turning on monitoring, the bird type corresponding to the recorded bird sound clip is determined, and the target bird-repelling voice is determined according to the bird type. This embodiment searches for the target wake-up word from the preset wake-up word library according to the current habit characteristics, and can obtain the target wake-up word for various birds under the current habit characteristics, and determines whether to turn on monitoring based on the current bird sound and the target wake-up word. It can turn on monitoring in a timely and effective manner. After turning on monitoring, the bird type corresponding to the recorded bird sound clip is determined. Compared with the existing loop playback of bird fear sounds, the above method of this application can monitor bird sounds in a timely and effective manner, so as to accurately play the target bird-repelling voice that birds fear according to the corresponding bird type to drive away birds.
[0065] refer to Figure 3 , Figure 3This is a flow chart of the second embodiment of the voice bird-repelling method of the present application.
[0066] Based on the first embodiment above, in this embodiment, before step S10, the following steps are further included:
[0067] Step S01: collecting bird sounds and habit characteristics of various birds, and constructing a full bird sound information vector library based on the bird sounds and habit characteristics.
[0068] It is understandable that the bird sounds of various birds may include chirping sounds, movement sounds, etc., and a full bird sound information vector library is constructed based on the bird sounds and habit characteristics.
[0069] Furthermore, in this embodiment, the step S101 includes: collecting bird sounds and habit characteristics of various birds, and cutting and segmenting the bird sounds to obtain a sound set of various birds; extracting vector features of the sound set by the Mel-cephalogram coefficient method to obtain sound feature vectors of various birds; quantizing the habit characteristics to obtain habit feature vectors; and constructing a full bird sound information vector library based on the sound feature vectors and the habit feature vectors.
[0070] It should be understood that the bird sounds of various birds can be cut and segmented. Specifically, the chirping sounds, movement sounds, etc. can be cut and segmented according to the pause time to obtain a sound set of various birds, which can be expressed as Si(x) (i=1,2,3...m, m is the number of segments of each type of bird sound; x=1,2,3...n, n is the bird type). The above sound set Si(x) is vector feature extracted by the Mel cepstral coefficient method to obtain the sound feature vectors Ci(x) of various birds.
[0071] It is understandable that the habit characteristics can also be quantified, that is, the bird type, season, surrounding environment, climate, geographical location, etc. are quantified to obtain a habit feature vector, which can be expressed as numbers, letters, etc. Then the habit feature vector is added to the sound feature vector to construct the full bird sound information vector library CiF(x).
[0072] Step S02: clustering the entire bird sound information vector library to obtain a bird sound set of various birds with different habit characteristics.
[0073] It should be understood that, in this embodiment, the entire bird sound information vector library CiF(x) can be clustered according to clustering methods such as k-means to obtain a set of bird sounds of various birds with different habit characteristics.
[0074] Step S03: determining preset wake-up word libraries for various birds with different habit characteristics according to the bird sound set.
[0075] Furthermore, in order to effectively determine the preset wake-up word library for various birds under different habit characteristics, in this embodiment, the step S03 includes: determining the bird sound frequency corresponding to the bird sound set of the various birds under each habit characteristic; sorting the bird sound frequencies to obtain sorting results under different habit characteristics; selecting the wake-up words for various birds under different habit characteristics from the bird sound set according to the sorting results; and constructing the preset wake-up word library for various birds under different habit characteristics according to the wake-up words.
[0076] It is understandable that the bird sound frequencies corresponding to the bird sound sets of various birds under each habit characteristic can be counted. The bird sound frequency can be the number of data contained in each bird sound set under each habit characteristic, and the bird sound frequencies are sorted according to size to obtain the sorting results under different habit characteristics.
[0077] It should be understood that, according to the sorting results, wake-up words for various birds under different habit characteristics can be selected from the bird sound sets. Specifically, one or more bird sound sets with larger frequencies can be selected as the wake-up words, and all the wake-up words can be combined into a preset wake-up word library for various birds under different habit characteristics. For example, sparrows include X bird sound sets under habit characteristic A, and X bird sound frequencies corresponding to the X bird sound sets can be determined. Then, the bird sound sets corresponding to one or more larger frequencies among the X bird sound frequencies are selected as the wake-up words. The wake-up words for the remaining birds can also be obtained in the above manner to jointly construct a preset wake-up word library.
[0078] Furthermore, in order to accurately construct a preset wake-up word library, in this embodiment, the step of constructing a preset wake-up word library for various birds under different habit characteristics based on the wake-up word specifically includes: training an initial neural network model according to the bird sounds, habit characteristics, the wake-up words and wake-up word sound samples of the various birds to obtain a target neural network model; determining the preset wake-up word library for various birds under different habit characteristics according to the target neural network model.
[0079] It is understandable that the input of the initial neural network model can be the bird sounds and habit characteristics of various birds, and the output can be the wake-up word. Therefore, the bird sounds, habit characteristics, and wake-up words of various birds can be used as training sets. In addition, more simulated wake-up word sound samples can be constructed, and these sound data can be used to train the initial neural network model to obtain the target neural network model. In this way, the preset wake-up word library of various birds under different habit characteristics can be determined according to the target neural network model.
[0080] In the specific implementation, refer to Figure 4 , Figure 4 This is a flow chart of building a preset wake-up word library in an embodiment of the voice bird-repelling method of the present application. Figure 4As shown in the figure, we first collect bird sounds (including chirping and movement sounds) and habit characteristics (including season, surrounding environment, climate, geographical location, etc.) of different birds, cut and segment the chirping or movement sounds according to the pause time to obtain the sound set Si(x) of x types of birds (i=1,2,3...m, m is the number of segments of each type of bird sound; x=1,2,3...n, n is the bird category), and use the Mel-frequency cepstral coefficient (MFCC) method to extract the feature vector Ci(x) of the Si(x) set, quantify the information of bird type, season, surrounding environment, climate, geographical location, etc., and add the vector Ci (x), construct a full-scale bird sound information feature vector library CiF(x), cluster CiF(x) according to the bird sounds of the same bird with different habit characteristics according to clustering methods such as k-means, obtain L types of bird sounds for each bird under a certain habit characteristic, count the frequency of each bird in the L type sounds, and sort them by size, select high-frequency wake-up words as the wake-up words for different bird species based on the ranking of the sorting results, construct more simulated wake-up word sound samples, train the model on the high-frequency wake-up words for each type of bird, and achieve a high accuracy rate, and finally construct a preset wake-up word library for each bird species under different habit characteristics.
[0081] This embodiment collects the bird sounds and habit characteristics of various birds, and constructs a full bird sound information vector library based on the bird sounds and habit characteristics, and then clusters the full bird sound information vector library to obtain a bird sound set of various birds with different habit characteristics, and then determines the preset wake-up word library of various birds with different habit characteristics based on the bird sound set. This embodiment constructs a full bird sound information vector library based on bird sounds and habit characteristics, and then clusters the full bird sound information vector library to obtain a bird sound set of various birds with different habit characteristics, and then determines the high-frequency wake-up words of various birds with different habit characteristics based on the bird sound set, and constitutes a preset wake-up word library.
[0082] refer to Figure 5 , Figure 5 This is a flow chart of the third embodiment of the voice bird-repelling method of the present application.
[0083] Based on the above embodiments, in this embodiment, step S20 includes:
[0084] Step S201: after monitoring is started, the bird type corresponding to the recorded bird sound clip is determined.
[0085] It is understandable that after monitoring is turned on, a bird sound clip recorded by a microphone can be obtained, and the bird type corresponding to the bird sound clip can be determined.
[0086] Furthermore, in order to accurately determine the bird type corresponding to the recorded bird sound clip, in the present embodiment, the step S201 includes: training the initial bird sound classification model according to the full bird sound information vector library to obtain the target bird sound classification model; after turning on the monitoring, inputting the current habit characteristics and the recorded bird sound clip into the target bird sound classification model to obtain the corresponding bird type.
[0087] It should be understood that the initial bird sound classification model can be a classification model such as a random forest model, and the initial bird sound classification model can be trained according to the above-mentioned full bird sound information vector library CiF(x) to obtain a target bird sound classification model. After starting monitoring, the current habit characteristics and recorded bird sound clips can be input into the target bird sound classification model to obtain the corresponding bird type. The current habit characteristics may include the date, surrounding environment, climate, geographical location, etc. at the current moment.
[0088] Step S202: collecting initial bird-repelling voices corresponding to various bird species, and classifying the initial bird-repelling voices to obtain classified bird-repelling voices corresponding to various bird species.
[0089] It is understandable that the initial bird-repelling voices corresponding to various birds can be collected. The initial bird-repelling voices refer to the sounds that various birds are afraid of. Since the initial bird-repelling voices may contain multiple types, the initial bird-repelling voices can be classified to obtain the classified bird-repelling voices corresponding to various birds.
[0090] Step S203: selecting a target bird-repelling voice from the classified bird-repelling voices according to the bird type.
[0091] It should be understood that the target bird-repelling voice can be selected from the classified bird-repelling voices according to the bird type corresponding to the recorded bird sound clip, and the target bird-repelling voice refers to the bird-repelling voice corresponding to the bird type. After obtaining the target bird-repelling voice, monitoring can be stopped, and the target bird-repelling voice can be played for a certain length of time through the speakers in the bird activity area in turn. After the playback is completed, the playback can be stopped, and it can be re-determined whether to start monitoring.
[0092] After monitoring is turned on, this embodiment determines the type of bird corresponding to the recorded bird sound clip, then collects the initial bird-repelling voices corresponding to various birds, and classifies the initial bird-repelling voices to obtain the classified bird-repelling voices corresponding to various birds, and then selects the target bird-repelling voice from the classified bird-repelling voices according to the bird type. After monitoring is turned on, this embodiment determines the type of bird corresponding to the recorded bird sound clip, and then selects the target bird-repelling voice from the classified bird-repelling voices according to the bird type, and can accurately play the target bird-repelling voice that the bird is afraid of according to the corresponding bird type to drive away the bird.
[0093] Reference Figure 6 , Figure 6 This is a structural block diagram of the first embodiment of the voice bird-repelling device of the present application.
[0094] like Figure 6 As shown, the voice bird-repelling device proposed in the embodiment of the present application includes:
[0095] A monitoring judgment module 10 is used to search for a target wake-up word from a preset wake-up word library according to the current habit characteristics of various birds, and to judge whether to start monitoring according to the current bird sound and the target wake-up word;
[0096] The voice bird-repelling module 20 is used to determine the bird type corresponding to the recorded bird sound clip after the monitoring is turned on, and determine the target bird-repelling voice according to the bird type.
[0097] This embodiment searches for the target wake-up word from the wake-up word library according to the current habit characteristics of various birds, and determines whether to turn on monitoring based on the current bird sound and the target wake-up word. After turning on monitoring, the bird type corresponding to the recorded bird sound clip is determined, and the target bird-repelling voice is determined according to the bird type. This embodiment searches for the target wake-up word from the wake-up word library according to the current habit characteristics, and can obtain the target wake-up word for various birds under the current habit characteristics, and determines whether to turn on monitoring based on the current bird sound and the target wake-up word. It can turn on monitoring in a timely and effective manner. After turning on monitoring, the bird type corresponding to the recorded bird sound clip is determined. Compared with the existing loop playback of bird fear sounds, the above method of this application can monitor bird sounds in a timely and effective manner, so as to accurately play the target bird-repelling voice that birds fear according to the corresponding bird type to drive away birds.
[0098] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present application. In practical applications, technicians in this field can select part or all of it according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.
[0099] In addition, for technical details not fully described in this embodiment, please refer to the voice bird-repelling method provided in any embodiment of the present application, and will not be repeated here.
[0100] Based on the above-mentioned first embodiment of the voice bird-repellent device of the present application, a second embodiment of the voice bird-repellent device of the present application is proposed.
[0101] In this embodiment, the voice bird-repellent device also includes a wake-up word library construction module, which is also used to collect bird sounds and habit characteristics of various birds, and construct a full bird sound information vector library based on the bird sounds and the habit characteristics; cluster the full bird sound information vector library to obtain a set of bird sounds of various birds under different habit characteristics; and determine a preset wake-up word library for various birds under different habit characteristics based on the bird sound set.
[0102] Furthermore, the wake-up word library construction module is also used to collect bird sounds and habit characteristics of various birds, and cut and segment the bird sounds to obtain a sound set of various birds; extract vector features of the sound set through the Mel-cephalogram coefficient method to obtain sound feature vectors of various birds; quantize the habit characteristics to obtain habit feature vectors; and construct a full bird sound information vector library based on the sound feature vectors and the habit feature vectors.
[0103] Furthermore, the wake-up word library construction module is also used to determine the bird sound frequency corresponding to the bird sound set of the various birds under each habit characteristic; sort the bird sound frequencies to obtain sorting results under different habit characteristics; select wake-up words for various birds under different habit characteristics from the bird sound set according to the sorting results; and construct a preset wake-up word library for various birds under different habit characteristics according to the wake-up words.
[0104] Furthermore, the wake-up word library construction module is also used to train the initial neural network model according to the bird sounds, habit characteristics, the wake-up words and wake-up word sound samples of the various birds to obtain a target neural network model; and determine the preset wake-up word library for various birds under different habit characteristics according to the target neural network model.
[0105] Furthermore, the voice bird-repelling module 20 is also used to determine the bird type corresponding to the recorded bird sound clip after monitoring is turned on; collect initial bird-repelling voices corresponding to various birds, and classify the initial bird-repelling voices to obtain classified bird-repelling voices corresponding to various birds; and select target bird-repelling voices from the classified bird-repelling voices according to the bird type.
[0106] Furthermore, the voice bird-repelling module 20 is also used to train an initial bird sound classification model based on the full bird sound information vector library to obtain a target bird sound classification model; after monitoring is turned on, the current habit characteristics and recorded bird sound clips are input into the target bird sound classification model to obtain the corresponding bird type.
[0107] Other embodiments or specific implementations of the voice bird-repelling device of the present application can refer to the above-mentioned method embodiments, which will not be repeated here.
[0108] The present application provides a voice bird-repelling device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the voice bird-repelling method in the above-mentioned embodiment 1.
[0109] Reference below Figure 7 , which shows a schematic diagram of the structure of a voice bird-repelling device suitable for implementing the embodiment of the present application. The voice bird-repelling device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 7 The voice bird-repelling device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.
[0110] like Figure 7 As shown, the voice bird-repelling device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the voice bird-repelling device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the voice bird repellent device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a voice bird repellent device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or provided alternatively.
[0111] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.
[0112] The voice bird-repelling device provided by the present application adopts the voice bird-repelling method in the above embodiment, which can solve the technical problem of how to monitor the bird sounds in a timely and effective manner, thereby accurately playing the sounds that birds are afraid of to repel birds. Compared with the prior art, the beneficial effects of the voice bird-repelling device provided by the present application are the same as the beneficial effects of the voice bird-repelling method provided by the above embodiment, and the other technical features of the voice bird-repelling device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.
[0113] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.
[0114] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.
[0115] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the voice bird-repelling method in the above-mentioned embodiment.
[0116] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.
[0117] The computer-readable storage medium may be included in the voice bird-repelling device; or may exist independently without being assembled into the voice bird-repelling device.
[0118] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the voice bird-repellent device, the voice bird-repellent device: searches for the target wake-up word from the preset wake-up word library according to the current habit characteristics of various birds, and determines whether to turn on monitoring according to the current bird sound and the target wake-up word; after turning on monitoring, determines the bird type corresponding to the recorded bird sound clip, and determines the target bird-repellent voice according to the bird type.
[0119] Computer program code for performing the operations of the present application may be written in one or more programming languages or a combination thereof, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).
[0120] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.
[0121] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.
[0122] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned voice bird-repelling method, and can solve the technical problem of how to monitor the bird sounds in a timely and effective manner, thereby accurately playing the sounds that birds are afraid of to repel birds. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the voice bird-repelling method provided by the above-mentioned embodiment, and will not be repeated here.
[0123] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.
Claims
1. A method for driving away birds by voice, characterized in that: The voice bird-repelling method comprises the following steps: Searching for a target wake-up word from a preset wake-up word library according to the current habits and characteristics of various birds, and determining whether to start monitoring based on the current bird sound and the target wake-up word; After monitoring is turned on, the bird type corresponding to the recorded bird sound clip is determined, and the target bird-repelling voice is determined according to the bird type.
2. The method for driving away birds by voice according to claim 1, characterized in that: Before the step of searching for a target wake-up word from a preset wake-up word library according to the current habit characteristics of various birds, and determining whether to start monitoring according to the current bird sound and the target wake-up word, the method further includes: Collecting bird sounds and habit characteristics of various birds, and constructing a full bird sound information vector library based on the bird sounds and habit characteristics; Clustering the full bird sound information vector library to obtain a bird sound set of various birds with different habit characteristics; A preset wake-up word library for various birds with different habit characteristics is determined according to the bird sound collection.
3. The method for driving away birds by voice according to claim 2, characterized in that: The step of collecting bird sounds and habit characteristics of various birds and constructing a full bird sound information vector library according to the bird sounds and habit characteristics specifically includes: Collecting bird sounds and habit characteristics of various birds, and cutting and segmenting the bird sounds to obtain a collection of sounds of various birds; Extracting vector features from the sound set using the Mel-frequency cepstral coefficient method to obtain sound feature vectors of various birds; Quantifying the habit characteristics to obtain a habit characteristic vector; A complete bird sound information vector library is constructed based on the sound feature vector and the habit feature vector.
4. The method for driving away birds by voice according to claim 2, characterized in that: The step of determining the preset wake-up word library of various birds under different habit characteristics according to the bird sound set specifically includes: Determine the bird sound frequency corresponding to the bird sound set of the various birds under each habit characteristic; Sorting the frequencies of the bird sounds to obtain sorting results under different habit characteristics; Selecting wake-up words of various birds with different habit characteristics from the bird sound collection according to the sorting result; A preset wake-up word library for various birds with different habit characteristics is constructed according to the wake-up word.
5. The method for driving away birds by voice according to claim 4, characterized in that: The step of constructing a preset wake-up word library for various birds with different habit characteristics according to the wake-up word specifically includes: The initial neural network model is trained according to the bird sounds, habit characteristics, the wake-up words and the wake-up word sound samples of the various birds to obtain a target neural network model; The preset wake-up word library of various birds under different habit characteristics is determined according to the target neural network model.
6. The method for driving away birds with voice according to any one of claims 2 to 5, characterized in that: After the monitoring is started, the step of determining the bird type corresponding to the recorded bird sound clip, and determining the target bird-repelling voice according to the bird type specifically includes: After turning on monitoring, determine the type of bird that the recorded bird sound clip corresponds to; Collecting initial bird-repelling voices corresponding to various bird species, and classifying the initial bird-repelling voices to obtain classified bird-repelling voices corresponding to various bird species; A target bird-repelling voice is selected from the classified bird-repelling voices according to the bird type.
7. The method for driving away birds by voice according to claim 6, characterized in that: After the monitoring is started, the step of determining the bird type corresponding to the recorded bird sound clip specifically includes: Training an initial bird sound classification model according to the full bird sound information vector library to obtain a target bird sound classification model; After monitoring is turned on, the current habit characteristics and the recorded bird sound clips are input into the target bird sound classification model to obtain the corresponding bird type.
8. A voice bird-repelling device, characterized in that: The voice bird-repelling device comprises: A monitoring judgment module, used to search for a target wake-up word from the preset wake-up word library according to the current habit characteristics of various birds, and judge whether to start monitoring according to the current bird sound and the target wake-up word; The voice bird-repelling module is used to determine the bird type corresponding to the recorded bird sound clip after monitoring is turned on, and determine the target bird-repelling voice according to the bird type.
9. A voice bird-repelling device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the voice bird-repelling method according to any one of claims 1 to 7.
10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the voice bird-repelling method according to any one of claims 1 to 7 are implemented.