Door lock control method based on call, electronic device and computer readable medium

Abstract

The embodiments of the present disclosure disclose a call-based door lock control method, an electronic device, and a computer-readable medium. A specific implementation of the method includes: in response to receiving a call request, parsing the call request to obtain the opposite user information corresponding to the call request; obtaining the call recording information of the opposite user end; generating the archived person information according to the call recording information; displaying the storage pop-up window corresponding to the archived person information; storing the archived person information according to the storage time information of the configured corresponding storage time configuration control; in response to obtaining the information of the person to be identified through the smart door lock device, matching the information of the person to be identified according to the stored archived person information to obtain a matching result; in response to determining that the matching result indicates a successful match, controlling the door lock component of the smart door lock device to perform an unlocking operation. This implementation allows a visitor user to use the smart door lock normally when visiting for the first time, thereby improving the security of the smart door lock.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular to a call-based door lock control method, an electronic device, and a computer-readable medium. Background Art

[0002] Smart door locks are improved upon traditional mechanical locks and are more intelligent and simple in terms of user security, identification, and management. At present, when using smart door locks, the usual method is: frequent users enter fingerprints, face photos, door unlocking commands in advance, or memorize passwords in advance for subsequent normal use of smart door locks.

[0003] However, the inventors have found that when the above method is adopted, the following technical problems often occur:

[0004] First, the method of pre-entering fingerprints, face photos, and door opening commands requires users to enter their body features in advance at the smart door lock, and visitors cannot use the smart door lock normally when they visit for the first time; the method of memorizing passwords in advance requires sending the passwords to others, which has a high risk of password leakage and poor security of smart door locks.

[0005] Second, the method of pre-entering the door opening password is adopted. When the door opening password spoken by the user is intercepted by the recording, the smart door lock can be opened by playing the recording, resulting in poor security of the smart door lock.

[0006] The above information disclosed in this Background section is only for enhancement of understanding of the background of the inventive concept and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art. Summary of the invention

[0007] The content of this disclosure is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this disclosure is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0008] Some embodiments of the present disclosure propose a call-based door lock control method, an electronic device, and a computer-readable medium to solve one or more of the technical problems mentioned in the above background technology section.

[0009] In a first aspect, some embodiments of the present disclosure provide a call-based door lock control method, the method comprising: in response to receiving a call request through a target application associated with a smart door lock device, parsing the call request to obtain peer user information corresponding to the call request; obtaining call recording information of the peer user; generating archived person information based on the call recording information; displaying a storage pop-up window corresponding to the archived person information, wherein the archived person information and a storage time configuration control are displayed in the storage pop-up window; storing the archived person information according to the configured storage time information corresponding to the storage time configuration control; in response to obtaining the person information to be identified through the smart door lock device, matching the person information to be identified according to each stored archived person information to obtain a matching result; in response to determining that the matching result indicates a successful match, controlling the door lock component of the smart door lock device to perform an unlocking operation.

[0010] In a second aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation manner of the above-mentioned first aspect.

[0011] In a third aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner of the first aspect is implemented.

[0012] The above-mentioned embodiments of the present disclosure have the following beneficial effects: through the call-based door lock control method of some embodiments of the present disclosure, the visitor user can use the smart door lock normally when visiting for the first time, and the security of the smart door lock is improved. Specifically, the reason why the visitor user cannot use the smart door lock normally when visiting for the first time and the security of the smart door lock is poor is that: the method of pre-entering fingerprints, face photos, and door opening commands requires the user to enter the human body characteristics in advance at the smart door lock, and the visitor user cannot use the smart door lock normally when visiting for the first time; the method of memorizing the password in advance requires the password to be sent to others, and the risk of password leakage is high, and the security of the smart door lock is poor. Based on this, the call-based door lock control method of some embodiments of the present disclosure, first, in response to receiving a call request through a target application associated with the smart door lock device, the call request is parsed to obtain the opposite user information corresponding to the call request. Thus, when receiving the request of the opposite user, the opposite user information can be parsed. Then, the call recording information of the above-mentioned opposite user end is obtained. Thus, the call of the opposite user end can be automatically recorded. Then, according to the call recording information, the archived person information is generated. Thus, the human feature-related information to be archived can be extracted from the call recording information. After that, a storage pop-up window corresponding to the archived person information is displayed, wherein the archived person information and the storage time configuration control are displayed in the storage pop-up window. Thus, the user can set the storage-related configuration of the archived person information by himself. Secondly, according to the storage time information corresponding to the configured storage time configuration control, the archived person information is stored. Thus, the archived person information can be automatically stored according to the configured information. Next, in response to obtaining the person information to be identified through the smart door lock device, the person information to be identified is matched according to the stored archived person information to obtain a matching result. Thus, it can be automatically determined whether the acquired person information to be identified matches the stored archived person information. Finally, in response to determining that the matching result indicates a successful match, the door lock component of the smart door lock device is controlled to perform an unlocking operation. Thus, when the match is successful, the door lock component of the automatic smart door lock device performs an unlocking operation, so that the guest user can enter the door. Also, because the peer user's archived information can be automatically stored through the recorded conversation content when the peer user talks with the current user, it can be used for identity verification at the smart door lock device when the peer user visits for the first time, and thus the visiting user does not need to arrive at the smart door lock in advance to enter the information, so that the guest user can use the smart door lock normally when visiting for the first time. In addition, because the password unlocking method is not adopted, the security of the smart door lock is improved. As a result, the guest user can use the smart door lock normally when visiting for the first time, and the security of the smart door lock is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0014] Figure 1 is a flow chart of some embodiments of the call-based door lock control method according to the present disclosure;

[0015] Figure 2 It is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0016] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0017] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0018] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0019] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0020] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0021] With regard to the collection, storage, and use of user personal information (such as call recording information, archived person information, and information of persons to be identified) involved in this disclosure, before performing the corresponding operations, the relevant organizations or individuals shall fulfill their obligations, including conducting personal information security impact assessments, fulfilling the obligation to inform the personal information subject, and obtaining the authorization and consent of the personal information subject in advance.

[0022] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0023] Figure 1 The process 100 of some embodiments of the door lock control method based on conversation according to the present disclosure is shown. The door lock control method based on conversation includes the following steps:

[0024] Step 101, in response to receiving a call request through a target application associated with a smart door lock device, parsing the call request to obtain peer user information corresponding to the call request.

[0025] In some embodiments, the execution subject (e.g., a computing device) of the call-based door lock control method may respond to receiving a call request through a target application associated with the smart door lock device, parse the call request, and obtain the opposite user information corresponding to the call request. Among them, the smart door lock device may be a device that can automatically identify human body features for unlocking. The target application may be an application that can be used in conjunction with the smart door lock device. For example, the user can connect the smart door lock device through the target application, and can configure various related configuration items in the target application. The target application may be an independent application or a mini-program application. The call request may be a request to apply for a call with the current user. Here, the call may be a video call or a voice call. The current user may be a user who logs in to the execution subject with an account. The execution subject may be, but is not limited to, a mobile phone, a tablet computer, a home smart screen, and a phone watch. The opposite user information may be information related to the opposite user and the opposite user end obtained by parsing. In practice, the execution subject may parse the opposite user information from the call request through a pre-packaged request parsing interface.

[0026] Optionally, the above-mentioned peer user information may include the peer user terminal address and user information. The peer user terminal address may be the IP address of the terminal of the peer user's login account. The user information may be user attribute related information of the peer user. The user information may include but is not limited to at least one of the following: user name, user avatar.

[0027] Optionally, before step 102, the execution entity may perform the following steps:

[0028] The first step is to obtain the location address of the opposite user terminal corresponding to the call request according to the address of the opposite user terminal in response to detecting the selection operation of the connection control acting on the call request page. In practice, the execution subject can obtain the location address of the opposite user terminal corresponding to the call request through a wireless connection method according to the address of the opposite user terminal in response to detecting the selection operation of the connection control acting on the call request page. Among them, the call request page can be a page for connecting or rejecting a call displayed on the display screen of the execution subject. The connection control can be used to connect a call. The selection operation can include but is not limited to at least one of the following: click, slide, drag. The location address can be a real-time location address of the opposite user terminal. The location address can be expressed as a geographic coordinate or as a text address. The call request page corresponds to the call request. The call request page displays the user name included in the opposite user information. The call request page can also display the user avatar included in the opposite user information. It should be noted that the above-mentioned wireless connection methods may include but are not limited to 3G / 4G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods currently known or to be developed in the future.

[0029] The second step is to determine whether the positioning address meets the preset distance condition corresponding to the target address. The target address may be the positioning address of the execution subject. The preset distance condition may be that the distance between the positioning address and the target address is less than the preset distance. Here, the distance may be a straight-line distance. For example, the preset distance may be 1 kilometer. The specific setting of the preset distance needs to meet the condition that the distance between the opposite user and the target address is relatively close.

[0030] In the third step, in response to determining that the positioning address meets the preset distance condition, a call recording request corresponding to the call request is sent to the opposite user terminal. The call recording request may be a request for applying to record the call content.

[0031] Step 102, obtaining call recording information of the opposite user end.

[0032] In some embodiments, the execution subject may obtain the call recording information of the peer user. The call recording information may be call data of a preset duration that is recorded after the peer user clicks the consent recording control. The call recording information may be a call recording video or a call recording voice.

[0033] In some optional implementations of some embodiments, the execution subject may obtain the call recording information of the peer user terminal in response to receiving feedback information indicating consent to recording corresponding to the call recording request. The feedback information indicating consent to recording may be determined by the peer user after clicking a consent recording control on the peer user terminal.

[0034] Step 103: Generate archiver information based on the call recording information.

[0035] In some embodiments, the execution entity may generate archiver information based on the call recording information.

[0036] In some optional implementations of some embodiments, the execution subject may generate archiver information according to the call recording information through the following steps:

[0037] The first step is to perform non-empty detection processing on the call recording information to obtain a non-empty detection result.

[0038] In a second step, in response to determining that the non-empty detection result indicates the existence of a recording target object, archiver information is generated according to the call recording information.

[0039] Optionally, the call request is a video call request, and the call recording information is a call recording video.

[0040] In some optional implementations of some embodiments, the execution subject may perform liveness detection on the call recording information, and obtain a liveness detection result as a non-empty detection result. In practice, the execution subject may perform liveness detection on the call recording information through a lip movement detection algorithm, and obtain a liveness detection result indicating whether a recording target object exists as a non-empty detection result. Here, the recording target object may be a real human face. Thus, whether the call recording information is non-empty can be determined through liveness detection.

[0041] Optionally, the call request is a voice call request, and the call recording information is call recording voice.

[0042] In some optional implementations of some embodiments, the execution subject may perform voiceprint identification processing on the call recording information to obtain a voiceprint identification result as a non-empty detection result. The voiceprint identification processing may be a process of identifying whether there is a human voice. In practice, the execution subject may perform voiceprint identification processing on the call recording information by using a voiceprint recognition technology based on sound type to obtain a voiceprint identification result indicating whether there is a recording target object as a non-empty detection result. Here, the recording target object may be a human voice. Thus, whether the call recording information is non-empty can be determined by voiceprint identification.

[0043] In some optional implementations of some embodiments, the execution subject may generate archiver information according to the call recording information through the following steps:

[0044] The first step is to perform frame processing on the call recording information to obtain a call image sequence. In practice, the execution subject can take a frame of image from the call recording information as a call image at every preset time interval to obtain a call image sequence.

[0045] In the second step, for each call image in the call image sequence, perform the following steps:

[0046] The first sub-step is to determine whether there is a complete face region in the call image. The face region may be a region representing a face displayed in the image. The complete face region may be an image region with a complete face outline. In practice, the execution subject may determine whether there is a complete face region in the call image by using a target detection algorithm in image detection technology.

[0047] The second sub-step is, in response to determining that there is a complete face region in the call image, capturing the face region in the call image to obtain a face image. In practice, the execution subject may capture the face region as the face image.

[0048] The third sub-step is to perform clarity detection on the above-mentioned face image to obtain the clarity information of the face image.

[0049] The fourth sub-step is to perform brightness detection on the face image to obtain brightness information of the face image. In practice, the execution subject may perform brightness detection on the face image using a brightness detection algorithm to obtain brightness parameters of the face image as the brightness information of the face image.

[0050] The fifth sub-step is to perform color deviation detection on the face image to obtain color deviation information of the face image. In practice, the execution subject may perform brightness detection on the face image using a color deviation detection algorithm to obtain color deviation parameters of the face image as the color deviation information of the face image.

[0051] The sixth sub-step is to generate facial image parameters according to the facial image clarity information, the facial image brightness information and the facial image color cast information. In practice, the execution subject may combine the facial image clarity information, the facial image brightness information and the facial image color cast information into facial image parameters.

[0052] In the third step, according to the obtained facial image parameters, a facial image that meets the preset image parameter conditions is selected from the obtained facial images as the target facial image. The preset image parameter conditions may be that the facial image is a facial image with the largest facial image clarity information among the facial images whose corresponding facial image brightness information is less than the preset brightness parameter and whose facial image color deviation information is less than the preset color deviation parameter. Here, the preset brightness parameter and the preset color deviation parameter may be 1.

[0053] In the fourth step, according to the facial image clarity information, facial image brightness information and facial image color cast information corresponding to the target facial image, image adjustment processing is performed on the target facial image to obtain an adjusted facial image.

[0054] The fifth step is to perform feature extraction processing on the adjusted face image to obtain face image feature information. In practice, the execution subject can perform feature extraction processing on the adjusted face image using a face image feature extraction algorithm to obtain face image feature information.

[0055] Step 6: Generate archived person information based on the facial image feature information and the user information. In practice, the execution subject may combine the facial image feature information and the user information into archived person information. Thus, call images with higher image quality can be selected from the call images to store the facial feature information of the peer user.

[0056] In some optional implementations of some embodiments, the execution subject may perform definition detection on the facial image to obtain the facial image definition information by the following steps:

[0057] The first step is to perform grayscale processing on the above-mentioned face image to obtain a face grayscale image. In practice, the above-mentioned execution subject can convert the above-mentioned face image into a grayscale image to obtain a face grayscale image.

[0058] The second step is to remove each pixel point that meets the preset edge condition in the above face image to obtain a face image after removal. The above preset edge condition can be that the pixel point is located at the upper edge or right edge of the image.

[0059] Step 3: For each pixel in the above face grayscale image, perform the following steps:

[0060] In the first sub-step, a pixel point that is right adjacent to the above pixel point in the above face grayscale image is determined as a right adjacent pixel point.

[0061] The second sub-step is to determine the pixel point in the above-mentioned face grayscale image that is adjacent to the above-mentioned pixel point as the upper adjacent pixel point.

[0062] The third sub-step is to generate a first pixel value and a second pixel value according to the pixel value of the right adjacent pixel point and the pixel value of the pixel point. In practice, the execution subject may determine the square of the difference between the pixel value of the right adjacent pixel point and the pixel value of the pixel point as the first pixel value. The execution subject may determine the absolute value of the difference between the pixel value of the right adjacent pixel point and the pixel value of the pixel point as the second pixel value.

[0063] The fourth sub-step is to generate a third pixel value and a fourth pixel value according to the pixel value of the upper adjacent pixel point and the pixel value of the pixel point. In practice, the execution subject may determine the square of the difference between the pixel value of the upper adjacent pixel point and the pixel value of the pixel point as the third pixel value. The execution subject may determine the absolute value of the difference between the pixel value of the upper adjacent pixel point and the pixel value of the pixel point as the fourth pixel value.

[0064] In the fourth step, the sum of the obtained first pixel values, the obtained second pixel values, the obtained third pixel values ​​and the obtained fourth pixel values ​​is determined as the fifth pixel value.

[0065] The fifth step is to determine the number of each pixel point included in the above-mentioned face grayscale image as the total number of pixel points.

[0066] In step 6, the ratio of the fifth pixel value to the total number of pixels is determined as the face image definition information corresponding to the face image. Thus, the definition of the image can be comprehensively determined from the left-right and top-bottom dimensions, thereby improving the accuracy of the determined definition.

[0067] In some optional implementations of some embodiments, the execution subject may perform image adjustment processing on the target facial image according to facial image clarity information, facial image brightness information, and facial image color cast information corresponding to the target facial image through the following steps to obtain an adjusted facial image:

[0068] The first step is to perform a clarity adjustment process on the target facial image in response to determining that the facial image clarity information corresponding to the target facial image satisfies a preset clarity adjustment condition, so as to update the target facial image. The preset clarity adjustment condition may be that the facial image clarity information is less than a preset clarity. In practice, the execution subject may use an image clarity adjustment algorithm to improve the clarity of the target facial image, so as to update the target facial image.

[0069] The second step is to perform brightness adjustment processing on the target facial image in response to determining that the facial image brightness information corresponding to the target facial image satisfies a preset brightness adjustment condition, so as to update the target facial image. The preset brightness adjustment condition may be that the facial image brightness information is not equal to a preset facial brightness parameter. In practice, the execution subject may perform brightness adjustment processing on the target facial image so that the facial image brightness information is equal to the preset facial brightness parameter, so as to update the target facial image.

[0070] The third step is to perform color deviation adjustment processing on the target facial image in response to determining that the facial image color deviation information corresponding to the target facial image satisfies a preset color deviation adjustment condition, so as to update the target facial image. The preset color deviation adjustment condition may be that the facial image color deviation information is not equal to a preset facial color deviation parameter. In practice, the execution subject may perform color deviation adjustment processing on the target facial image so that the facial image color deviation information is equal to the preset facial color deviation parameter, so as to update the target facial image.

[0071] The fourth step is to resize the updated target facial image to update the target facial image. In practice, the execution subject may resize the target facial image to a preset size to update the target facial image.

[0072] In the fifth step, the updated target face image is determined as the adjusted face image. Thus, the face image can be adjusted from four dimensions: clarity, brightness, color deviation and size.

[0073] In some optional implementations of some embodiments, the execution subject may generate archiver information according to the call recording information through the following steps:

[0074] The first step is to perform silence elimination and non-human voice elimination processing on the call recording information to obtain the eliminated audio. In practice, the execution subject can perform silence elimination and non-human voice elimination processing on the call recording information by using silence elimination and sound source separation technology in the field of audio processing technology to obtain the eliminated audio.

[0075] The second step is to perform denoising on the audio after elimination to obtain denoised audio. In practice, the execution subject may perform denoising on the audio after elimination through a linear filter to obtain denoised audio.

[0076] The third step is to perform frame processing on the denoised audio to obtain an audio sequence. In practice, the execution subject may equally divide the denoised audio into a preset number of audios to obtain an audio sequence.

[0077] Step 4: For each audio in the above audio sequence, perform the following steps:

[0078] The first sub-step is to determine the signal-to-noise ratio corresponding to the audio.

[0079] The second sub-step is to determine the volume corresponding to the above audio.

[0080] In a third sub-step, in response to determining that the signal-to-noise ratio and the volume meet a preset elimination condition, the audio is eliminated from the audio sequence to update the audio sequence. The preset elimination condition may be that the signal-to-noise ratio is less than a preset ratio, or the volume is less than a preset volume.

[0081] Step 5: Perform feature extraction on each audio in the updated audio sequence to obtain audio feature information. In practice, the above execution subject may use an audio feature extraction algorithm to perform feature extraction on each audio in the updated audio sequence to obtain audio feature information.

[0082] Step 6: For any two audio feature information obtained, determine the distance information between the two audio feature information. Here, the distance information may be a Euclidean distance.

[0083] Step 7: Select distance information that meets a preset distance condition from the determined distance information as target distance information. The preset distance condition may be that the distance information is the maximum value among the distance information.

[0084] In the eighth step, the two audio feature information corresponding to the target distance information and the user information are determined as the archiver information. Thus, the two most dissimilar audio feature information can be used as the audio features of the peer user, thereby improving the diversity of audio features and further improving the fault tolerance of audio feature matching.

[0085] Step 104, display a pop-up window for storing the corresponding archiver information.

[0086] In some embodiments, the execution subject may display a storage pop-up window corresponding to the archiver information. The storage pop-up window may be a window for the current user to set configuration items related to the storage of the archiver information. The storage pop-up window displays the archiver information and storage time configuration controls. The storage time configuration controls may be used for the current user to configure the storage period of the archiver information.

[0087] Step 105: store the archiver information according to the storage time information of the configured corresponding storage time configuration control.

[0088] In some embodiments, the execution subject may store the archiver information according to the storage time information configured corresponding to the storage time configuration control. In practice, the execution subject may store the archiver information, and at the same time, may generate an archiver information deletion task corresponding to the storage time information and the archiver information, and add the archiver information deletion task to the archiver information deletion task queue. Thus, when the storage period of the archiver information expires, the archiver information deletion task may be automatically taken out from the archiver information deletion task queue to execute the archiver information deletion task.

[0089] Step 106, in response to obtaining the information of the person to be identified through the smart door lock device, matching processing is performed on the information of the person to be identified according to the stored archived person information to obtain a matching result.

[0090] In some embodiments, the execution subject may obtain the information of the person to be identified through the smart door lock device, and perform matching processing on the information of the person to be identified according to the stored archived person information to obtain a matching result.

[0091] Optionally, before step 110, the execution subject may further perform the following steps:

[0092] The first step is to generate a voiceprint verification text according to a preset word library in response to a visitor request detected by the above-mentioned smart door lock device. The above-mentioned visitor request can be information representing that a visitor has requested to open the door. For example, after a visitor presses the doorbell button in the smart door lock device, the smart door lock device can send a visitor request to the above-mentioned execution subject. The above-mentioned preset word library can be a pre-set word library text for combining into sentences. The above-mentioned preset word library can contain words or characters of various parts of speech. Various parts of speech may include but are not limited to: articles, nouns, verbs, and prepositions. In practice, the above-mentioned execution subject can use a sentence generation model to select characters and / or words from the above-mentioned preset word library to form a sentence as a voiceprint verification text.

[0093] The second step is to send the voiceprint verification text to the smart door lock device, so that the smart door lock device displays the voiceprint verification text through an external display. The external display can be a display set outside the door. The external display can be set outside the smart door lock device.

[0094] The third step is to receive the audio to be verified corresponding to the voiceprint verification text sent by the smart door lock device as the person to be identified information. The audio to be verified can be the audio of the guest user reading the voiceprint verification text.

[0095] In some optional implementations of some embodiments, the execution subject may perform matching processing on the to-be-identified person information according to each stored archived person information through the following steps to obtain a matching result:

[0096] In the first step, the audio to be verified is subjected to silence elimination and non-human voice elimination processing to obtain the eliminated audio to be verified.

[0097] In the second step, the audio to be verified after the elimination is denoised to obtain the denoised audio to be verified.

[0098] The third step is to perform feature extraction processing on the above-mentioned denoised audio to be verified to obtain feature information of the audio to be verified.

[0099] The fourth step is to generate the audio similarity between the audio feature information to be verified and each audio feature information included in the above archiver information to obtain an audio similarity set. Here, the audio similarity can be cosine similarity.

[0100] In step 5, the audio similarity in the audio similarity set that satisfies the first preset similarity condition is determined as the target audio similarity. The first preset similarity condition may be that the audio similarity is the maximum value in the audio similarity set.

[0101] Step 6: In response to determining that the target audio similarity satisfies a second preset similarity condition, the audio feature information corresponding to the target audio similarity is determined as matching audio feature information. The second preset similarity condition may be that the target audio similarity is greater than a preset similarity.

[0102] Step 7: Generate a matching result based on the user information corresponding to the matching audio feature information. In practice, the execution entity may determine the preset matching success flag and the user name included in the user information as the matching result.

[0103] The above-mentioned first step-third step and first step-seventh step are an inventive point of an embodiment of the present disclosure, which solves the technical problem 2 mentioned in the background technology, "adopting the method of pre-entering the door opening command, when the door opening command spoken by the user is intercepted by the recording, the smart door lock can be opened by the played recording, resulting in poor security of the smart door lock". The factors that lead to poor security of the smart door lock are often as follows: adopting the method of pre-entering the door opening command, when the door opening command spoken by the user is intercepted by the recording, the smart door lock can be opened by the played recording. If the above factors are solved, the effect of improving the security of the smart door lock can be achieved. In order to achieve this effect, the present disclosure first generates a voiceprint verification text for the visitor user to read, so as to obtain the audio of the above-mentioned voiceprint verification text being read on site. Then, the audio feature information of the obtained audio is extracted as the audio feature information to be verified, so as to be used for audio feature matching, so as to obtain a matching result. Also because the obtained audio is temporarily generated and needs to be read by the visitor on site, the applicability of the door opening command intercepted by the recording is reduced, thereby improving the security of the smart door lock.

[0104] Step 107 , in response to determining that the matching result indicates a successful match, controlling the door lock component of the smart door lock device to perform an unlocking operation.

[0105] In some embodiments, the execution subject may control the door lock assembly of the smart door lock device to perform an unlocking operation in response to determining that the matching result indicates a successful match. The door lock assembly may be an assembly including a lock core.

[0106] The above-mentioned embodiments of the present disclosure have the following beneficial effects: through the call-based door lock control method of some embodiments of the present disclosure, the visitor user can use the smart door lock normally when visiting for the first time, and the security of the smart door lock is improved. Specifically, the reason why the visitor user cannot use the smart door lock normally when visiting for the first time and the security of the smart door lock is poor is that: the method of pre-entering fingerprints, face photos, and door opening commands requires the user to enter the human body characteristics in advance at the smart door lock, and the visitor user cannot use the smart door lock normally when visiting for the first time; the method of memorizing the password in advance requires the password to be sent to others, and the risk of password leakage is high, and the security of the smart door lock is poor. Based on this, the call-based door lock control method of some embodiments of the present disclosure, first, in response to receiving a call request through a target application associated with the smart door lock device, the call request is parsed to obtain the opposite user information corresponding to the call request. Thus, when receiving the request of the opposite user, the opposite user information can be parsed. Then, the call recording information of the above-mentioned opposite user end is obtained. Thus, the call of the opposite user end can be automatically recorded. Then, according to the call recording information, the archived person information is generated. Thus, the human feature-related information to be archived can be extracted from the call recording information. After that, a storage pop-up window corresponding to the archived person information is displayed, wherein the archived person information and the storage time configuration control are displayed in the storage pop-up window. Thus, the user can set the storage-related configuration of the archived person information by himself. Secondly, according to the storage time information corresponding to the configured storage time configuration control, the archived person information is stored. Thus, the archived person information can be automatically stored according to the configured information. Next, in response to obtaining the person information to be identified through the smart door lock device, the person information to be identified is matched according to the stored archived person information to obtain a matching result. Thus, it can be automatically determined whether the acquired person information to be identified matches the stored archived person information. Finally, in response to determining that the matching result indicates a successful match, the door lock component of the smart door lock device is controlled to perform an unlocking operation. Thus, when the match is successful, the door lock component of the automatic smart door lock device performs an unlocking operation, so that the guest user can enter the door. Also, because the peer user's archived information can be automatically stored through the recorded conversation content when the peer user talks with the current user, it can be used for identity verification at the smart door lock device when the peer user visits for the first time, and thus the visiting user does not need to arrive at the smart door lock in advance to enter the information, so that the guest user can use the smart door lock normally when visiting for the first time. In addition, because the password unlocking method is not adopted, the security of the smart door lock is improved. As a result, the guest user can use the smart door lock normally when visiting for the first time, and the security of the smart door lock is improved.

[0107] Reference below Figure 2, which shows a schematic diagram of the structure of an electronic device 200 (e.g., a computing device) suitable for implementing some embodiments of the present disclosure. The electronic devices in some embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 2 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0108] like Figure 2 As shown, the electronic device 200 may include a processing device 201 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 202 or a program loaded from a storage device 208 to a random access memory (RAM) 203. In the RAM 203, various programs and data required for the operation of the electronic device 200 are also stored. The processing device 201, the ROM 202, and the RAM 203 are connected to each other via a bus 204. An input / output (I / O) interface 205 is also connected to the bus 204.

[0109] Typically, the following devices may be connected to the I / O interface 205: an input device 206 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 207 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; and a communication device 209. The communication device 209 may allow the electronic device 200 to communicate with other devices wirelessly or by wire to exchange data. Figure 2 The electronic device 200 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 2 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0110] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 209, or installed from the storage device 208, or installed from the ROM 202. When the computer program is executed by the processing device 201, the above-mentioned functions defined in the method of some embodiments of the present disclosure are executed.

[0111] It should be noted that the computer-readable medium recorded in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, 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 some embodiments of the present disclosure, a 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, device or device. In some embodiments of the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0112] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0113] The computer-readable medium may be included in the electronic device; or it may exist independently without being installed in the electronic device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: in response to receiving a call request through a target application associated with the smart door lock device, parse the call request to obtain the opposite user information corresponding to the call request; obtain the call recording information of the opposite user end; generate the archived person information according to the call recording information; display a storage pop-up window corresponding to the archived person information, wherein the archived person information and the storage time configuration control are displayed in the storage pop-up window; store the archived person information according to the storage time information configured corresponding to the storage time configuration control; in response to obtaining the person information to be identified through the smart door lock device, match the person information to be identified according to the stored archived person information to obtain a matching result; in response to determining that the matching result indicates a successful match, control the door lock component of the smart door lock device to perform an unlocking operation.

[0114] Computer program code for performing the operations of some embodiments of the present disclosure 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 cases involving a remote computer, the remote computer may be connected to the user's computer via 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).

[0115] 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 disclosure. 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 implementations as replacements, 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.

[0116] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0117] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with the technical features with similar functions disclosed in the embodiments of the present disclosure (but not limited to) and the technical solutions formed.

Claims

1. A door lock control method based on call, comprising: In response to receiving a call request through a target application associated with the smart door lock device, parsing the call request to obtain peer user information corresponding to the call request, wherein the call request is a request for applying for a call with a current user, and the call includes a voice call; Obtaining call recording information of the opposite user terminal; Generate archiver information based on the call recording information; Displaying a storage pop-up window corresponding to the archiver information, wherein the archiver information and a storage time configuration control are displayed in the storage pop-up window; Storing the archiver information according to the storage time information configured corresponding to the storage time configuration control; In response to detecting a visitor request through the smart door lock device, generating a voiceprint verification text according to a preset word library; Sending the voiceprint verification text to the smart door lock device, so that the smart door lock device displays the voiceprint verification text through an external display; Receiving the audio to be verified corresponding to the voiceprint verification text sent by the smart door lock device as the person to be identified information, wherein the audio to be verified is the audio of the visitor user reading the voiceprint verification text; In response to obtaining the information of the person to be identified through the smart door lock device, matching the information of the person to be identified according to the stored archived information to obtain a matching result, wherein the matching process of the information of the person to be identified according to the stored archived information to obtain a matching result includes: Perform silence elimination and non-human voice elimination processing on the audio to be verified to obtain the eliminated audio to be verified; Performing denoising on the eliminated audio to be verified to obtain denoised audio to be verified; Performing feature extraction processing on the denoised audio to be verified to obtain feature information of the audio to be verified; Generating audio similarities between the audio feature information to be verified and each audio feature information included in each archiver information, to obtain an audio similarity set; Determine the audio similarity in the audio similarity set that satisfies a first preset similarity condition as the target audio similarity, wherein the first preset similarity condition is that the audio similarity is a maximum value in the audio similarity set; In response to determining that the target audio similarity satisfies a second preset similarity condition, determining the audio feature information corresponding to the target audio similarity as matching audio feature information, wherein the second preset similarity condition is that the target audio similarity is greater than a preset similarity; Generate a matching result according to the user information corresponding to the matching audio feature information; In response to determining that the matching result indicates a successful match, the door lock assembly of the smart door lock device is controlled to perform an unlocking operation.

2. The method according to claim 1, wherein: The peer user information includes the peer user terminal address and user information; as well as Before acquiring the call recording information of the opposite user terminal, the method further includes: In response to detecting a selection operation of a connect control on a call request page, acquiring a location address of a peer user terminal corresponding to the call request according to the address of the peer user terminal, wherein the call request page corresponds to the call request and the user name included in the peer user information is displayed on the call request page; Determining whether the positioning address meets a preset distance condition corresponding to the target address; In response to determining that the positioning address satisfies the preset distance condition, sending a call recording request corresponding to the call request to the opposite user terminal; and The acquiring of the call recording information of the opposite user terminal includes: In response to receiving feedback information indicating consent to recording corresponding to the call recording request, the call recording information of the opposite user end is acquired.

3. The method according to claim 2, wherein: The generating the archiver information according to the call recording information includes: Performing non-empty detection processing on the call recording information to obtain a non-empty detection result; In response to determining that the non-empty detection result indicates that a recording target object exists, archiver information is generated according to the call recording information.

4. The method according to claim 3, wherein: The call request is a video call request, and the call recording information is a call recording video; as well as The performing non-empty detection processing on the call recording information to obtain a non-empty detection result includes: Perform liveness detection on the call recording information and obtain a liveness detection result as a non-empty detection result.

5. The method according to claim 4, wherein: The generating the archiver information according to the call recording information includes: Performing frame processing on the call recording information to obtain a call image sequence; For each call image in the call image sequence, the following steps are performed: Determining whether there is a complete face area in the call image; In response to determining that a complete face region exists in the call image, performing interception processing on the face region in the call image to obtain a face image; Performing definition detection on the face image to obtain definition information of the face image; Performing brightness detection on the face image to obtain brightness information of the face image; Performing color cast detection on the face image to obtain color cast information of the face image; Generate facial image parameters according to the facial image clarity information, the facial image brightness information and the facial image color cast information; According to the obtained facial image parameters, a facial image satisfying a preset image parameter condition is selected from the obtained facial images as a target facial image; According to the facial image clarity information, facial image brightness information and facial image color cast information corresponding to the target facial image, the target facial image is subjected to image adjustment processing to obtain an adjusted facial image; Performing feature extraction processing on the adjusted face image to obtain face image feature information; The archived person information is generated according to the facial image feature information and the user information.

6. The method according to claim 5, wherein: The performing definition detection on the face image to obtain definition information of the face image includes: Performing grayscale processing on the face image to obtain a face grayscale image; Eliminate each pixel point that meets a preset edge condition in the face image to obtain a face image after elimination; For each pixel in the grayscale image of the face, perform the following steps: Determine a pixel point in the face grayscale image that is right adjacent to the pixel point as a right adjacent pixel point; Determine a pixel point in the face grayscale image that is adjacent to the pixel point as an upper adjacent pixel point; Generate a first pixel value and a second pixel value according to a pixel value of the right adjacent pixel point and a pixel value of the pixel point; Generate a third pixel value and a fourth pixel value according to the pixel value of the upper adjacent pixel point and the pixel value of the pixel point; Determine the sum of the obtained first pixel values, second pixel values, third pixel values ​​and fourth pixel values ​​as a fifth pixel value; Determine the number of each pixel point included in the face grayscale image as the total number of pixel points; The ratio of the fifth pixel value to the total number of pixels is determined as the facial image clarity information corresponding to the facial image.

7. The method according to claim 5, wherein: The step of performing image adjustment processing on the target face image according to the face image clarity information, face image brightness information and face image color cast information corresponding to the target face image to obtain an adjusted face image includes: In response to determining that the facial image definition information corresponding to the target facial image satisfies a preset definition adjustment condition, performing definition adjustment processing on the target facial image to update the target facial image; In response to determining that the facial image brightness information corresponding to the target facial image meets a preset brightness adjustment condition, performing brightness adjustment processing on the target facial image to update the target facial image; In response to determining that the facial image color deviation information corresponding to the target facial image satisfies a preset color deviation adjustment condition, performing color deviation adjustment processing on the target facial image to update the target facial image; Performing a size adjustment process on the updated target face image to update the target face image; The updated target face image is determined as the adjusted face image.

8. The method according to claim 3, wherein: The call request is a voice call request, and the call recording information is a call recording voice; as well as The performing non-empty detection processing on the call recording information to obtain a non-empty detection result includes: Performing voiceprint identification processing on the call recording information to obtain a voiceprint identification result as a non-empty detection result; and The generating the archiver information according to the call recording information includes: Performing silence elimination and non-human voice elimination processing on the call recording information to obtain eliminated audio; Performing denoising on the eliminated audio to obtain denoised audio; Performing frame processing on the denoised audio to obtain an audio sequence; For each audio in the audio sequence, perform the following steps: Determining a signal-to-noise ratio corresponding to the audio; Determine the volume corresponding to the audio; In response to determining that the signal-to-noise ratio and the volume meet a preset elimination condition, eliminating the audio from the audio sequence to update the audio sequence; Performing feature extraction processing on each audio in the updated audio sequence to obtain audio feature information; For any two pieces of audio feature information obtained, determining distance information of the any two pieces of audio feature information; Selecting distance information that meets a preset distance condition from each determined distance information as target distance information; The two audio feature information corresponding to the target distance information and the user information are determined as archived person information.

9. An electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 8.

10. A computer readable medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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