On-off control method and system for smart home

Abstract

The invention discloses an on-off control method and system for a smart home, and belongs to the field of smart home control, and the method comprises the following steps: carrying out the feature recognition of sound information which gives out a specific vocabulary after the specific vocabulary is detected, and judging whether the sound information is recorded sound information or not; if the sound information is the recorded sound information, identifying a specific number of the recorded sound information, and obtaining a corresponding personal file based on the specific number; compared with the prior art, the method has the advantages that when the voice of the user is recognized, the corresponding personal file of the user is matched, personalized setting is completed, and the functions of the equipment or the application are correspondingly adjusted based on the voice of different users, so that the equipment or the application is matched with the preferences, requirements and habits of the different users; in addition, when multiple contradictory operation actions are detected, shielding processing is carried out, and it is avoided that multiple fast contradictory operation actions affect the service life of the target equipment.

Description

Technical Field

[0001] The present invention belongs to the field of smart home control, and in particular relates to a switch control method and system for a smart home. Background Art

[0002] Smart home switch control is an important part of modern home intelligence. It integrates technologies such as the Internet of Things and wireless communications, connects multiple systems in the home such as lighting, security, energy management, etc., and realizes one-click control, remote monitoring and intelligent management functions, thereby improving the convenience, comfort and safety of home life.

[0003] By connecting with smart voice assistants (such as Xiao Ai, Tmall Genie, etc.), users can use voice commands to control target devices in the smart home. The disadvantage is that there is a lack of personalized settings. When multiple people live together, smart voice assistants cannot adjust the functions of devices or applications based on the voices of different users to match the preferences, needs and habits of different users. This needs to be improved. Summary of the invention

[0004] Based on this, it is necessary to provide a switch control method and system for a smart home to address the above problems.

[0005] The embodiment of the present invention is implemented as follows: a switch control method for a smart home comprises the following steps: After detecting the specific word, feature recognition is performed on the sound information that emits the specific word to determine whether the sound information is recorded sound information; If it is recorded sound information, identify the specific number of the recorded sound information, and obtain the corresponding personal file based on the specific number; Recognize voice commands, determine the target device to be controlled based on the recognized voice commands, match personal profiles, and complete personalized control of the target device.

[0006] In one embodiment, the present invention provides a method for controlling a switch of a smart home, wherein after detecting a specific word, the step of performing feature recognition on the sound information that emits the specific word and determining whether the sound information is recorded sound information specifically includes: After detecting specific words, the sound information is preprocessed to convert the continuous speech signal into a discrete digital signal (analog-to-digital conversion); remove background noise and retain meaningful information (filtering); divide the digital signal into multiple small segments for analysis (frame division, each frame is usually 25ms long, the frame shift is 10ms, and there is a certain overlap between frames); Feature extraction is performed on each small segment of the digital signal to obtain the processed voiceprint features, which include waveform features (such as amplitude, energy, etc.), frequency domain features (such as spectrum density, resonance peak, frequency, etc.), and time domain statistical features (such as mean, variance, etc.); The processed voiceprint features are compared with the voiceprint features in the recorded sound information library to determine whether the sound information matches the recorded sound information (by calculating metrics such as similarity or distance).

[0007] In one embodiment, the present invention provides a switch control method for a smart home, wherein after detecting a specific word, the sound information that emits the specific word is feature recognized, and before the step of determining whether the sound information is recorded sound information, the method further includes collecting sound information to complete the establishment of a sound information database, wherein the step of collecting sound information to complete the establishment of a sound information database specifically includes: Collecting sound information to be recorded; Use audio processing software to optimize the sound quality of the recorded sound information, including noise reduction, noise removal, and volume adjustment; Select a database system, which includes relational databases (MySQL, PostgreSQL, etc.) and non-relational databases (MongoDB, etc.), design a database table, and the fields of the database table include number, name, gender, and recording time. The sound information to be recorded is entered into the database table and becomes the recorded sound information.

[0008] In one embodiment, the present invention provides a method for controlling a switch of a smart home, wherein the steps of recognizing a voice command, determining a target device to be controlled according to the recognized voice command, matching a personal profile, and completing personalized control of the target device specifically include: Using speech recognition technology, the collected speech signals are converted into text information; Parse the identified text information and extract key information, including device name and operation action; search for the target device based on the parsed device name (before executing the control operation, check the current status of the target device and determine whether the corresponding control operation needs to be executed based on the device status to avoid unnecessary interference or damage); The user's personalized settings are obtained from the personal profile, including preference settings and device usage habits; specific control instructions are generated based on the parsed operation actions and the user's personalized settings, and the generated control instructions are sent to the target device.

[0009] In one embodiment, the present invention provides a method for controlling a switch of a smart home, wherein the steps of recognizing a voice command, determining a target device to be controlled according to the recognized voice command, matching a personal profile, and completing the personalized control of the target device further include: Collecting multiple voice signals within a first set time, determining whether there are conflicting operation actions of the same device name between the multiple voice signals; If there are conflicting operation actions with the same device name, the number of conflicting operation actions with the same device name is detected. When the number of conflicting operation actions reaches a threshold, the conflicting operation actions are shielded within a second set time.

[0010] In one embodiment, the present invention provides a switch control system for a smart home, comprising: A sound information judgment module is used to perform feature recognition on the sound information of the specific word after detecting the specific word, and judge whether the sound information is recorded sound information; A personal profile acquisition module, for identifying the specific number of the recorded sound information if it is recorded sound information, and acquiring the corresponding personal profile based on the specific number; The personalized control module is used to recognize voice commands, determine the target device to be controlled according to the recognized voice commands, match the personal profile, and complete personalized control of the target device.

[0011] In one embodiment, the present invention provides a switch control system for a smart home, and the sound information determination module includes: The sound information processing unit is used to pre-process the sound information after detecting specific words, converting the continuous voice signal into discrete digital signals (analog-to-digital conversion); removing background noise and retaining meaningful information (filtering); dividing the digital signal into multiple small segments for analysis (framing, each frame is usually 25ms long, the frame shift is 10ms, and there is a certain overlap between frames); The feature extraction unit is used to extract features from each small segment of the digital signal to obtain processed voiceprint features. The voiceprint features include waveform features (such as amplitude, energy, etc.), frequency domain features (such as spectrum density, resonance peak, frequency, etc.), and time domain statistical features (such as mean, variance, etc.); The voiceprint feature comparison unit is used to compare the processed voiceprint features with the voiceprint features in the recorded sound information library to determine whether the sound information matches the recorded sound information (by calculating similarity or distance or other metrics).

[0012] In one embodiment, the present invention provides a switch control system for a smart home, and the switch control system for the smart home further includes: a database establishment module, which is used to collect sound information to complete the establishment of a sound information database; the database establishment module includes: A sound information collecting unit, used for collecting sound information to be recorded; A sound quality optimization unit, which is used to optimize the sound quality of the recorded sound information using audio processing software. The sound quality optimization includes noise reduction, noise removal, and volume adjustment; The sound information input unit is used to select a database system, including relational databases (MySQL, PostgreSQL, etc.) and non-relational databases (MongoDB, etc.), design a database table, and the fields of the database table include number, name, gender, and recording time. The sound information to be recorded is entered into the database table and becomes the recorded sound information.

[0013] In one embodiment, the present invention provides a switch control system for a smart home, wherein the personalized control module includes: A voice signal conversion unit, used to convert the collected voice signal into text information using voice recognition technology; The text information parsing unit is used to parse the identified text information and extract key information therein, including device name and operation action; search for the target device according to the parsed device name (before executing the control operation, check the current status of the target device and determine whether the corresponding control operation needs to be executed according to the device status to avoid unnecessary interference or damage); The control instruction generation unit is used to obtain the user's personalized settings from the personal profile, and the personalized settings include preference settings and device usage habits; generate specific control instructions according to the parsed operation actions and the user's personalized settings, and send the generated control instructions to the target device.

[0014] In one embodiment, the present invention provides a switch control system for a smart home, and the personalized control module further includes: A conflicting operation action judgment unit, used to collect multiple voice signals within a first set time, and judge whether there are conflicting operation actions of the same device name between the multiple voice signals; The contradictory operation action shielding unit is used to detect the number of contradictory operation actions with the same device name if there are contradictory operation actions with the same device name. When the number of contradictory operation actions reaches a threshold, the contradictory operation actions are shielded within a second set time.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention completes personalized settings by matching the corresponding user personal profile when recognizing the user's voice, and adjusts the functions of the device or application accordingly based on the voices of different users to match the preferences, needs and habits of different users; in addition, when multiple contradictory operation actions are detected, shielding processing will be performed to avoid multiple rapid contradictory operation actions affecting the service life of the target device. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic flow chart of a smart home switch control method provided by an embodiment of the present invention.

[0017] Figure 2 A schematic diagram of a flow chart of sound information determination provided by an embodiment of the present invention.

[0018] Figure 3 A schematic diagram of a flow chart of establishing a sound information database provided by an embodiment of the present invention.

[0019] Figure 4 A schematic diagram of a personalized control process provided by an embodiment of the present invention.

[0020] Figure 5 A schematic diagram of the process of detecting and processing contradictory operation actions provided by an embodiment of the present invention.

[0021] Figure 6 A schematic diagram of a smart home switch control system provided by an embodiment of the present invention.

[0022] Figure 7 A schematic diagram of a sound information determination module provided in an embodiment of the present invention.

[0023] Figure 8 A schematic diagram of a database establishment module provided in an embodiment of the present invention.

[0024] Fig. 9 This is a first schematic diagram of a personalized control module provided in an embodiment of the present invention.

[0025] Fig.10 A second schematic diagram of a personalized control module provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0027] It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script.

[0028] In one embodiment, Figure 1 As shown, a switch control method for a smart home (applied to a switch control system for a smart home) comprises the following steps: Step S2, after detecting the specific word, performing feature recognition on the sound information that emits the specific word to determine whether the sound information is recorded sound information; Step S3, if it is recorded sound information, identify the specific number of the recorded sound information, and obtain the corresponding personal profile based on the specific number; Step S4, recognize the voice command, determine the target device to be controlled according to the recognized voice command, match the personal profile, and complete the personalized control of the target device.

[0029] After the characteristic words are detected by the intelligent voice assistant (such as Xiao Ai, Tmall Genie, etc.), "Xiao Ai" is taken as an example here. After "Xiao Ai" is detected, the sound information of "Xiao Ai" is identified, and the sound is converted to digital, filtered, and framed to obtain the voiceprint features. Based on the obtained voiceprint features, it is determined whether it is recorded sound information. If it is recorded sound information, the specific number of the recorded sound information is detected in the database table, and the corresponding personal profile is obtained based on the specific number. For example, if the number is 1, it is determined to be user Zhang San, and Zhang San's voice command is identified, such as "open the computer Douyin". At this time, based on Zhang San's personal profile, the computer is controlled to turn on. After the network connection is completed, the Douyin of Zhang San's corresponding account is opened to achieve personalized control. Similarly, if the number is 2, it is determined to be user Li Si, for example, the voice command is "turn on the air conditioner", then based on Li Si's personal profile and Li Si's historical air conditioning usage information, the air conditioning temperature is controlled to 24°C. Instead of Li Si needing to "turn on the air conditioner" and the air conditioner temperature being 25℃, Li Si needs to say the voice command "lower the air conditioner temperature by 1℃" again. This way, when multiple people live together, the functions of the device or application can be adjusted accordingly based on the voices of different users, making it simpler to control the device to match the preferences, needs and habits of different users.

[0030] In a preferred embodiment of the present invention, in step S2, after the switch control system detects a specific word, it performs feature recognition on the sound information that emits the specific word, and the recorded sound information is recorded in a database table, and by comparing the voiceprint features of the current sound information with the voiceprint features in the recorded sound information database, it is determined whether the sound information is the recorded sound information; In a preferred embodiment of the present invention, in step S3, if the sound information is recorded, the switch control system identifies the specific number of the recorded sound information, the recorded sound information has a corresponding number in the database table, and based on the specific number, obtains the corresponding personal file; In a preferred embodiment of the present invention, in step S4, the switch control system recognizes the voice command, determines the target device to be controlled according to the recognized voice command, matches the personal profile, and completes the personalized control of the target device.

[0031] In one embodiment, Figure 2 As shown, the step S2, after detecting a specific word, performs feature recognition on the sound information of the specific word, and determines whether the sound information is a recorded sound information step, specifically includes: Step S21, after detecting a specific word, pre-process the sound information, convert the continuous voice signal into a discrete digital signal (analog-to-digital conversion); remove background noise and retain meaningful information (filtering); divide the digital signal into multiple small segments for analysis (frame division, each frame length is usually 25ms, the frame shift is 10ms, and there is a certain overlap between frames); Step S22, extracting features from each small segment of the digital signal to obtain processed voiceprint features, which include waveform features (such as amplitude, energy, etc.), frequency domain features (such as spectrum density, resonance peak, frequency, etc.), and time domain statistical features (such as mean, variance, etc.); Step S23, comparing the processed voiceprint features with the voiceprint features in the recorded sound information database to determine whether the sound information matches the recorded sound information (determined by calculating similarity or distance or other metrics).

[0032] The similarity or distance between two voiceprint features is calculated using a specific similarity measurement algorithm or distance measurement method. Commonly used measurement methods include: Euclidean distance: It measures the straight-line distance between points in space and is suitable for measuring the differences between numerical features.

[0033] Cosine similarity: measures the cosine value of the angle between two vectors, reflecting the directional similarity between the vectors and is suitable for similarity measurement of high-dimensional data.

[0034] Manhattan distance: The sum of absolute axis distances in a standard coordinate system, suitable for measuring the difference between discrete or grid data.

[0035] Dynamic Time Warping (DTW): By elastically stretching the time axis to better align two time series data, it is possible to calculate the similarity between sounds of different lengths or different degrees of change on the time axis.

[0036] In practical applications, multiple distance measurement methods may be combined or different features may be fused, and the similarity between two sounds may be ultimately determined by weight adjustment.

[0037] According to the preset similarity threshold or distance threshold, determine whether the current sound information matches the recorded sound information. Combine the results of multiple features or multiple measurement methods, and use logical operations (such as AND, OR, NOT) to comprehensively determine the degree of match of the sound information. Further process and analyze the matching results, such as removing duplicates, optimizing sorting, etc., and finally determine whether the sound information matches the recorded sound information.

[0038] In one embodiment, Figure 3 As shown, the step S2, after detecting a specific word, performs feature recognition on the sound information that emits the specific word, and determines whether the sound information is a recorded sound information step, further includes step S1, collecting sound information to complete the establishment of a sound information database, and the step S1, collecting sound information to complete the establishment of a sound information database specifically includes: Step S11, collecting sound information to be recorded; Step S12, using audio processing software to optimize the sound quality of the sound information to be recorded, the sound quality optimization includes noise reduction, noise removal, and volume adjustment; Step S13, select a database system, the database system includes relational databases (MySQL, PostgreSQL, etc.), non-relational databases (MongoDB, etc.), design a database table, the fields of the database table include number, name, gender, recording time, and the sound information to be recorded is entered into the database table and becomes the recorded sound information.

[0039] The designed database table can be specifically:

[0040] Here, the fields of the database table include number, name, gender, and recording time. In actual use, the fields of the database table are not limited, and there can also be fields such as recording duration and update time. The number is automatically increased based on the order of the recordings.

[0041] In one embodiment, Figure 4As shown, the step S4, identifying the voice command, determining the target device to be controlled according to the identified voice command, matching the personal profile, and completing the personalized control step of the target device, specifically includes: Step S41, using speech recognition technology to convert the collected speech signal into text information; Step S42, parsing the identified text information to extract key information therein, including device name and operation action; searching for the target device according to the parsed device name (before executing the control operation, checking the current state of the target device, and judging whether the corresponding control operation needs to be executed according to the device state, so as to avoid unnecessary interference or damage); Step S43, obtaining the user's personalized settings from the personal profile, the personalized settings including preference settings and device usage habits; generating specific control instructions based on the parsed operation actions and the user's personalized settings, and sending the generated control instructions to the target device.

[0042] Take personalized settings as an example. For example, Zhang San is used to an air-conditioning temperature of 25℃, while Li Si is used to an air-conditioning temperature of 24℃. Based on the voice information, it is determined whether the voice command is from Zhang San or Li Si. Therefore, when turning on the air-conditioner, the most suitable temperature for the user is directly set based on the personalized settings, and no adjustment is required. Similarly, for lighting, Zhang San may like brighter lighting, while Li Si likes dimmer lighting. Similarly, the brightness of the lighting can be controlled based on personalized settings. In addition, the lighting also includes cool and warm tones, music, etc.

[0043] In one embodiment, Figure 5 As shown, the step S4, identifying the voice command, determining the target device to be controlled according to the identified voice command, matching the personal profile, and completing the personalized control of the target device, also includes: Step S45, collecting multiple voice signals within a first set time, and determining whether there are conflicting operation actions of the same device name among the multiple voice signals; Step S46, if there are conflicting operation actions with the same device name, the number of conflicting operation actions with the same device name is detected, and when the number of conflicting operation actions reaches a threshold, the conflicting operation actions are shielded within a second set time.

[0044] Considering that there may be conflicting operations on the target device caused by quarrels between users, for example, Zhang San and Li Si quarrel, Zhang San voice command "turn on the TV", Li Si voice command "turn off the TV", and the two repeat voice commands many times during the quarrel, for example, there are multiple conflicting voice signals within 10S (first set time), and the TV is turned on and off many times in a short period of time, which affects the service life of the TV. Therefore, in this situation, when it is detected that the number of times the TV is turned on and off reaches 5 times (threshold), the conflicting operations are blocked within 30 minutes (second set time). The first set time, the second set time, and the threshold are set according to the actual situation, and the second set time and threshold of different devices can also be different.

[0045] In one embodiment, Figure 6 As shown, a switch control system of a smart home includes: The sound information judging module 2 is used to perform feature recognition on the sound information of the specific word after detecting the specific word, and judge whether the sound information is the recorded sound information; The personal profile acquisition module 3 is used to identify the specific number of the recorded sound information if it is recorded sound information, and acquire the corresponding personal profile based on the specific number; The personalized control module 4 is used to recognize voice commands, determine the target device to be controlled according to the recognized voice commands, match the personal profile, and complete personalized control of the target device.

[0046] Smart voice assistants, such as Xiao Ai and Tmall Genie, have become an important part of modern smart homes and smart devices. These smart assistants have their own unique feature vocabulary, which not only reflects their functional characteristics, but also helps users interact with the device more conveniently. Xiao Ai is Xiaomi's smart voice assistant. Users can activate the device through the wake-up word "Xiao Ai" to put it into operation from sleep mode. Tmall Genie is a smart speaker launched by Alibaba. Its feature vocabulary "Tmall Genie" also includes wake-up words and function command words. Voice commands allow Xiao Ai and Tmall Genie to perform a variety of tasks to meet the diverse needs of users.

[0047] In one embodiment, Figure 7 As shown, the sound information determination module 2 includes: The sound information processing unit 21 is used to pre-process the sound information after detecting the specific words, convert the continuous voice signal into a discrete digital signal (analog-to-digital conversion); remove the background noise and retain the meaningful information (filtering); divide the digital signal into multiple small segments for analysis (frame division, each frame length is usually 25ms, the frame shift is 10ms, and there is a certain overlap between frames); The feature extraction unit 22 is used to extract features from each small segment of the digital signal to obtain processed voiceprint features, which include waveform features (such as amplitude, energy, etc.), frequency domain features (such as spectrum density, resonance peak, frequency, etc.), and time domain statistical features (such as mean, variance, etc.); The voiceprint feature comparison unit 23 is used to compare the processed voiceprint features with the voiceprint features in the recorded sound information library to determine whether the sound information matches the recorded sound information (by calculating similarity or distance or other metrics).

[0048] Filtering is an important step in signal processing, which is used to remove background noise and retain meaningful information. In speech signal processing, commonly used filtering methods include mean filtering and median filtering. Mean filtering reduces random noise by calculating the moving average of the signal. In speech signal processing, mean filtering can be used to remove background noise in recordings and improve audio quality. Median filtering is a nonlinear filtering technique. In speech signal processing, median filtering can also be used to remove background noise while better retaining the edge information of speech signals.

[0049] In one embodiment, Figure 8 As shown, the switch control system of the smart home further includes: a database establishment module 1, which is used to collect sound information to complete the establishment of a sound information database; the database establishment module 1 includes: A sound information collecting unit 11, used to collect the sound information to be recorded; A sound quality optimization unit 12, used to optimize the sound quality of the sound information to be recorded using audio processing software, the sound quality optimization includes noise reduction, noise removal, and volume adjustment; The sound information input unit 13 is used to select a database system, the database system includes relational databases (MySQL, PostgreSQL, etc.), non-relational databases (MongoDB, etc.), design a database table, the fields of the database table include number, name, gender, recording time, and the sound information to be recorded is entered into the database table and becomes the recorded sound information.

[0050] Volume adjustment is a key step to ensure that speech signals can be heard clearly in different environments. Volume adjustment can be adjusted through automatic gain control (AGC), which detects the amplitude of the speech signal and automatically adjusts the gain to maintain a stable volume of the speech signal. When the speech signal is weak, AGC increases the gain to increase the volume; when the speech signal is strong, AGC reduces the gain to prevent distortion caused by excessive volume.

[0051] In one embodiment, Fig. 9 As shown, the personalized control module 4 includes: The voice signal conversion unit 41 is used to convert the collected voice signal into text information using voice recognition technology; The text information parsing unit 42 is used to parse the identified text information and extract key information therein, the key information including the device name and the operation action; search for the target device according to the parsed device name (before executing the control operation, check the current state of the target device and determine whether the corresponding control operation needs to be executed according to the device state to avoid unnecessary interference or damage); The control instruction generating unit 43 is used to obtain the user's personalized settings from the personal profile, the personalized settings including preference settings and device usage habits; generate specific control instructions according to the parsed operation actions and the user's personalized settings, and send the generated control instructions to the target device.

[0052] Before executing a control operation, it is necessary to check the current state of the target device. For example, executing an operation that requires high power consumption when the device is overheated may accelerate hardware aging or even cause hardware damage. In this case, there is no need to execute the corresponding control operation.

[0053] In one embodiment, Fig.10 As shown, the personalized control module 4 also includes: The conflicting operation action judging unit 44 is used to collect multiple voice signals within a first set time and judge whether there are conflicting operation actions of the same device name among the multiple voice signals; The contradictory operation shielding unit 45 is used to detect the number of contradictory operation actions with the same device name if there are contradictory operation actions with the same device name, and shield the contradictory operation actions within a second set time when the number of contradictory operation actions reaches a threshold.

[0054] You can also set priorities to avoid equipment failure and damage. When the number of conflicting operations reaches a threshold, the priority will be determined. The priority is based on the number. The smaller the number, the higher the priority.

[0055] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0056] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0057] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0058] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0059] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0060] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A switch control method for a smart home, characterized in that: The switch control method of the smart home comprises the following steps: After detecting the specific word, feature recognition is performed on the sound information that emits the specific word to determine whether the sound information is recorded sound information; If it is recorded sound information, identify the specific number of the recorded sound information, and obtain the corresponding personal file based on the specific number; Recognize voice commands, determine the target device to be controlled based on the recognized voice commands, match personal profiles, and complete personalized control of the target device.

2. The switch control method of smart home according to claim 1, characterized in that: After the specific word is detected, the step of performing feature recognition on the sound information of the specific word and determining whether the sound information is recorded sound information specifically includes: After detecting specific words, the sound information is preprocessed to convert the continuous speech signal into a discrete digital signal; remove background noise and retain meaningful information; and divide the digital signal into multiple small segments for analysis; Perform feature extraction on each small segment of the digital signal to obtain processed voiceprint features, which include waveform features, frequency domain features, and time domain statistical features; The processed voiceprint features are compared with the voiceprint features in the recorded sound information library to determine whether the sound information matches the recorded sound information.

3. The switch control method of smart home according to claim 1, characterized in that: After the specific word is detected, the sound information of the specific word is identified, and before the step of determining whether the sound information is recorded sound information, the step of collecting sound information to complete the establishment of a sound information database is also included. The step of collecting sound information to complete the establishment of a sound information database specifically includes: Collecting sound information to be recorded; Use audio processing software to optimize the sound quality of the recorded sound information, including noise reduction, noise removal, and volume adjustment; Select a database system, which includes relational databases and non-relational databases, design a database table, and the fields of the database table include number, name, gender, and recording time. The sound information to be recorded is entered into the database table and becomes the recorded sound information.

4. The switch control method of smart home according to claim 1, characterized in that: The step of recognizing the voice command, determining the target device to be controlled according to the recognized voice command, matching the personal profile, and completing the personalized control of the target device specifically includes: Using speech recognition technology, the collected speech signals are converted into text information; Parse the identified text information and extract key information, including device name and operation action; search for the target device based on the parsed device name; The user's personalized settings are obtained from the personal profile, including preference settings and device usage habits; specific control instructions are generated based on the parsed operation actions and the user's personalized settings, and the generated control instructions are sent to the target device.

5. The switch control method of smart home according to claim 4, characterized in that: The step of recognizing the voice command, determining the target device to be controlled according to the recognized voice command, matching the personal profile, and completing the personalized control of the target device also includes: Collecting multiple voice signals within a first set time, determining whether there are conflicting operation actions of the same device name between the multiple voice signals; If there are conflicting operation actions with the same device name, the number of conflicting operation actions with the same device name is detected. When the number of conflicting operation actions reaches a threshold, the conflicting operation actions are shielded within a second set time.

6. A switch control system for a smart home, characterized in that: The switch control system of the smart home comprises: A sound information judgment module is used to detect a specific word and then perform feature recognition on the sound information of the specific word to determine whether the sound information is recorded sound information; A personal profile acquisition module, for identifying the specific number of the recorded sound information if it is recorded sound information, and acquiring the corresponding personal profile based on the specific number; The personalized control module is used to recognize voice commands, determine the target device to be controlled according to the recognized voice commands, match the personal profile, and complete personalized control of the target device.

7. The switch control system of the smart home according to claim 6, characterized in that: The sound information judgment module includes: The sound information processing unit is used to pre-process the sound information after detecting specific words, convert the continuous voice signal into a discrete digital signal; remove background noise and retain meaningful information; and divide the digital signal into multiple small segments for analysis; A feature extraction unit is used to extract features from each small segment of the digital signal to obtain processed voiceprint features, which include waveform features, frequency domain features, and time domain statistical features; The voiceprint feature comparison unit is used to compare the processed voiceprint features with the voiceprint features in the recorded sound information library to determine whether the sound information matches the recorded sound information.

8. The switch control system of the smart home according to claim 6, characterized in that: The switch control system of the smart home also includes: a database establishment module, which is used to collect sound information to complete the establishment of a sound information database; the database establishment module includes: A sound information collecting unit, used for collecting sound information to be recorded; A sound quality optimization unit, which is used to optimize the sound quality of the recorded sound information using audio processing software. The sound quality optimization includes noise reduction, noise removal, and volume adjustment. The sound information input unit is used to select a database system, the database system includes relational databases and non-relational databases, and design a database table. The fields of the database table include number, name, gender, and recording time. The sound information to be recorded is entered into the database table and becomes the recorded sound information.

9. The switch control system of the smart home according to claim 6, characterized in that: The personalized control module includes: A voice signal conversion unit, used to convert the collected voice signal into text information using voice recognition technology; A text information parsing unit is used to parse the identified text information and extract key information therein, wherein the key information includes a device name and an operation action; and search for a target device according to the parsed device name; The control instruction generation unit is used to obtain the user's personalized settings from the personal profile, and the personalized settings include preference settings and device usage habits; generate specific control instructions according to the parsed operation actions and the user's personalized settings, and send the generated control instructions to the target device.

10. The switch control system of the smart home according to claim 9, characterized in that: The personalized control module also includes: A conflicting operation action judging unit, used to collect multiple voice signals within a first set time, and judge whether there are conflicting operation actions of the same device name between the multiple voice signals; The contradictory operation action shielding unit is used to detect the number of contradictory operation actions with the same device name if there are contradictory operation actions with the same device name. When the number of contradictory operation actions reaches a threshold, the contradictory operation actions are shielded within a second set time.

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