Noise acquisition method and device, intelligent equipment and storage medium

Abstract

The invention relates to a noise acquisition method and device, intelligent equipment and a storage medium. The noise acquisition method comprises the following steps: when the intelligent equipment is in a working state, acquiring sound data within a preset duration; and if the sound data contains the working noise generated by the intelligent equipment, uploading the sound data to a cloud server. According to the noise acquisition method, the noise data can be acquired in time when the intelligent equipment generates the working noise, so that after-sales personnel or research and development personnel can check the noise data and analyze noise reasons, the difficulty of processing noise problem feedback by the after-sales personnel is reduced, the after-sales experience of a user is improved, and the user experience is improved. And meanwhile, research and development personnel can optimize products in a more targeted manner.

Description

Technical Field

[0001] The present disclosure relates to the technical field of intelligent devices, and in particular to a noise collection method, device, intelligent device and storage medium. Background Art

[0002] With the continuous development of social economy and the continuous improvement of living standards, smart devices have become an indispensable part of daily life, such as smart refrigerators and smart washing machines. Due to various uncontrollable factors, when users use smart devices, the smart devices may occasionally generate noise when they are in working state, affecting the user experience. However, when users raise feedback about occasional noise problems, it is difficult for after-sales personnel to arrive at the scene in time when the noise occurs. Therefore, when providing after-sales service for occasional noise problems, it is impossible to analyze the cause of the noise and solve the noise problem in time, thus affecting the user's after-sales experience. At the same time, R&D personnel are unable to further optimize the product based on the cause of the noise. Summary of the invention

[0003] In order to overcome the problems existing in the related art, the present disclosure provides a noise collection method, an apparatus, an intelligent device and a storage medium.

[0004] According to a first aspect of an embodiment of the present disclosure, a noise collection method is provided, the method comprising:

[0005] When the smart device is in working state, collect sound data within a preset time period;

[0006] If the sound data contains the working noise generated by the smart device, the sound data is uploaded to the cloud server.

[0007] In an exemplary embodiment, the method further comprises:

[0008] Based on a preset noise detection model, it is detected whether the sound data contains the working noise.

[0009] In an exemplary embodiment, the method further comprises:

[0010] Acquire historical sound data of the smart device, wherein the historical sound data includes sound data in different working states and working noise detected in the sound data;

[0011] Based on the historical sound data, the preset noise detection model is trained.

[0012] In an exemplary embodiment, the method further comprises:

[0013] Based on a first preset time interval, updating the historical sound data;

[0014] The preset noise detection model is trained based on the updated historical sound data.

[0015] In an exemplary embodiment, collecting sound data within a preset time period includes:

[0016] When the noise detection instruction is received, the sound data is collected.

[0017] In an exemplary embodiment, the receiving of a noise detection instruction includes:

[0018] Based on the voice interaction function of the smart device, the noise detection instruction is received.

[0019] In an exemplary embodiment, collecting sound data within a preset time period includes:

[0020] When the voice interaction function of the smart device is not used, the sound data is collected based on a second preset time interval.

[0021] According to a second aspect of an embodiment of the present disclosure, a noise collection device is provided, the device comprising:

[0022] A collection module, configured to collect sound data within a preset time period when the smart device is in working state;

[0023] The processing module is configured to upload the sound data to a cloud server if the sound data contains working noise generated by the smart device.

[0024] In an exemplary embodiment, the processing module is further configured to:

[0025] Based on a preset noise detection model, it is detected whether the sound data contains the working noise.

[0026] In an exemplary embodiment, the processing module is further configured to:

[0027] Acquire historical sound data of the smart device, wherein the historical sound data includes sound data in different working states and working noise detected in the sound data;

[0028] Based on the historical sound data, the preset noise detection model is trained.

[0029] In an exemplary embodiment, the processing module is further configured to:

[0030] Based on a first preset time interval, updating the historical sound data;

[0031] The preset noise detection model is trained based on the updated historical sound data.

[0032] In an exemplary embodiment, the acquisition module is further configured to:

[0033] When the noise detection instruction is received, the sound data is collected.

[0034] In an exemplary embodiment, the acquisition module is further configured to:

[0035] Based on the voice interaction function of the smart device, the noise detection instruction is received.

[0036] In an exemplary embodiment, the acquisition module is further configured to:

[0037] When the voice interaction function of the smart device is not used, the sound data is collected based on a second preset time interval.

[0038] According to a third aspect of an embodiment of the present disclosure, there is provided a smart device, including:

[0039] processor;

[0040] a memory for storing processor-executable instructions;

[0041] The processor is configured to execute the noise collection method as described in the first aspect of the embodiment of the present disclosure.

[0042] According to a fourth aspect of an embodiment of the present disclosure, a non-temporary computer-readable storage medium is provided. When instructions in the storage medium are executed by a processor of an intelligent device, the intelligent device can execute the noise collection method as described in the first aspect of the embodiment of the present disclosure.

[0043] The above method disclosed in the present invention has the following beneficial effects: it is possible to obtain noise data in a timely manner when the smart device generates working noise, so that after-sales personnel or R&D personnel can view the noise data and analyze the cause of the noise, thereby reducing the difficulty of after-sales personnel in handling noise problem feedback, improving the user's after-sales experience, and R&D personnel can optimize the product in a more targeted manner.

[0044] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0046] Figure 1 is a flow chart of a noise collection method according to an exemplary embodiment;

[0047] Figure 2is a flow chart of a noise collection method according to an exemplary embodiment;

[0048] Figure 3 is a schematic diagram of a smart refrigerator scene according to an exemplary embodiment;

[0049] Figure 4 is a flow chart of a noise collection method according to an exemplary embodiment;

[0050] Figure 5 is a block diagram of a noise collection device according to an exemplary embodiment;

[0051] Figure 6 The invention is a block diagram of a smart device according to an exemplary embodiment. DETAILED DESCRIPTION

[0052] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0053] In the exemplary embodiment of the present disclosure, in order to overcome the problem in the related art that it is impossible to provide after-sales service for occasional noise raised by users in a timely manner, a noise collection method is provided, including: when the smart device is in working state, collecting sound data within a preset time length; if the sound data contains working noise generated by the smart device, uploading the sound data to a cloud server. This method can obtain noise data in a timely manner when the smart device generates working noise, so that after-sales personnel or R&D personnel can view the noise data and analyze the cause of the noise, thereby reducing the difficulty of after-sales personnel in handling noise problem feedback, improving the user's after-sales experience, and R&D personnel can optimize products more targeted.

[0054] In an exemplary embodiment of the present disclosure, a noise collection method is provided. Figure 1 is a flow chart of a noise collection method according to an exemplary embodiment. Figure 1 As shown, the following steps are included:

[0055] Step S101, when the smart device is in working state, collecting sound data within a preset time period;

[0056] Step S102: if the sound data contains working noise generated by the smart device, the sound data is uploaded to the cloud server.

[0057] Smart devices refer to electronic devices with computing and processing capabilities, including smart appliances such as smart refrigerators and smart washing machines, smart homes, smart wearable devices, smart medical devices and other electronic devices.

[0058] In step S101, the smart device is in working state, which means that the system starts to run after the smart device is powered on. The preset time can be set according to actual needs, such as 30 seconds, 1 minute or 2 minutes. The sound data is collected by the sound collection device in the smart device, such as using a microphone to collect sound data.

[0059] In step S102, the working noise generated by the smart device refers to the unexpected sound generated when the smart device is in a working state, that is, the sound that affects normal study, work and rest other than the normal working sound. For example, the working noise of a smart refrigerator includes compressor noise, fan noise, damper noise, resonance noise, refrigerant flow noise, thermal expansion and contraction noise, etc.

[0060] The sound data collected by the sound collection device may contain the ambient sound of the environment where the smart device is located, the normal working sound of the smart device, and the working noise generated by the smart device. Analyze the collected sound data. If the sound data does not contain working noise, it means that the smart device is not abnormal and no processing is required; if the sound data contains working noise, it means that the smart device is abnormal. The sound data is uploaded to the cloud server through the smart module in the smart device so that after-sales personnel or R&D personnel can download the sound data from the cloud server, and solve the noise problem and optimize the product by analyzing the sound data. The collected sound data includes the sound spectrum. Since the spectrum of noise is different from that of normal sound, when analyzing the sound data, the sound spectrum can be used to determine whether it contains working noise.

[0061] It should be noted that a setting option for whether to upload sound data is set in the smart module of the smart device, and the relevant privacy terms are indicated. The user can choose whether to enable the function of uploading sound data.

[0062] In an exemplary embodiment of the present disclosure, if the collected sound data contains working noise, the sound data will be uploaded to the cloud server, so that the noise data can be obtained in time when the smart device generates working noise, so that after-sales personnel or R&D personnel can view the noise data and analyze the cause of the noise, thereby reducing the difficulty of after-sales personnel in handling noise problem feedback, improving the user's after-sales experience, and R&D personnel can optimize the product more targeted.

[0063] In an exemplary embodiment of the present disclosure, a noise collection method is provided. Figure 2 is a flow chart of a noise collection method according to an exemplary embodiment. Figure 2 As shown, the following steps are included:

[0064] Step S201, when the smart device is in working state, collecting sound data within a preset time period;

[0065] Step S202, obtaining historical sound data of the smart device, where the historical sound data includes sound data under different working states and working noise detected in the sound data;

[0066] Step S203, training a preset noise detection model based on historical sound data;

[0067] Step S204, based on a preset noise detection model, detecting whether the sound data contains working noise;

[0068] Step S205, updating historical sound data based on a first preset time interval;

[0069] Step S206, training a preset noise detection model based on the updated historical sound data;

[0070] Step S207: if the sound data contains working noise generated by the smart device, the sound data is uploaded to the cloud server.

[0071] The specific implementation of step S201 and step S207 refers to step S101 and step S102, which will not be repeated here.

[0072] In step S201, in some possible implementations, when collecting sound data, when the voice interaction function of the smart device is not used, based on the second preset time interval, sound data within a preset duration is collected. The voice interaction function is a function in the smart module of the smart device. The user sends a voice command to the smart device through the voice interaction function. When the voice interaction function is used, the sound collection device in the smart device needs to collect the user's voice information, so it is impossible to collect sound data at the same time; when the voice interaction function is not used, based on the second preset time interval, the sound collection device is used to collect sound data. The second preset time interval is an empirical value, which can be a preset value, or relevant setting options can be provided for the user to set. Collecting sound data within a preset duration based on the second preset time interval can save power consumption of the smart device.

[0073] In order to collect more working noise, when it is determined that the sound data contains working noise, the second preset time interval is modified to 0, and the sound data is continuously collected. When it is determined that the sound data no longer contains working noise, the second preset time interval is restored to the initial preset value.

[0074] In some possible implementations, when a noise detection instruction is received, sound data within a preset time length is collected. If the time interval for collecting sound data is long, or when the user perceives working noise, the sound data is collected by sending a noise detection instruction to the smart device. In one example, a noise detection instruction is received based on the voice interaction function of the smart device. For example, when a user uses the voice interaction function, the user's voice information is collected. If it is determined that the voice information similar to "detect noise" is contained, the voice interaction function is turned off and the sound data within the preset time length is collected. In another example, a noise detection instruction is received based on a noise detection button. For example, a physical button or virtual button related to noise detection is set in the smart device, and when the user clicks the button, the sound data within the preset time length is collected. When a noise detection instruction is received, sound data within the preset time length is collected, which can facilitate the user to start collecting sound data at any time and avoid not collecting sound data.

[0075] In step S202, the historical sound data includes sound data of the smart device in different working states, such as sound data in sleep state and sound data in operation state, including sound data without working noise and sound data with working noise, and also includes detection results of the sound data. For example, for sound data without working noise, the corresponding detection result is the absence of working noise; for sound data with working noise, the corresponding detection result is the presence of working noise and the content of the working noise. For example, when the smart device is a smart refrigerator, the working noise is fan noise.

[0076] In step S203, the historical sound data is used as training data to train a preset noise detection model. The preset noise detection model can be any algorithm model that can detect noise, such as a quantile noise estimation algorithm.

[0077] In step S204, the currently collected sound data is input into the trained preset noise detection model to obtain whether the sound data contains working noise and what working noise is contained. For example, when the smart device is a smart refrigerator, the working noise obtained includes fan noise and compressor noise.

[0078] In step S205, the first preset time interval is a preset value, which can be determined according to actual conditions. The sound data collected within the time period of the first preset time interval is added to the historical sound data, and the historical sound data is updated to increase the training data, so that the training result is more accurate and more applicable to the current smart device. The historical sound data of the user before the first use of the smart device is pre-stored in the smart device and is collected by other similar smart devices that have been used. After the user starts the smart device, the historical sound data is continuously expanded using the actually collected sound data, so that the result of the preset noise detection model is more applicable to the current smart device.

[0079] In step S206, after the historical sound data is updated, the updated historical sound data is used as training data to retrain the preset noise detection model, and after the sound data is collected next time, the preset noise detection model after charging training is used to determine whether the sound data contains the working noise generated by the smart device.

[0080] In the exemplary embodiments of the present disclosure, step S201 and step S207 may be independent embodiments, and steps S203 to S206 are optional. One or more of these steps may be omitted or replaced in different embodiments.

[0081] In an exemplary embodiment of the present disclosure, a noise collection method is provided. Applied to a smart refrigerator, Figure 3 is a schematic diagram of a smart refrigerator scene according to an exemplary embodiment. Figure 3 As shown, the smart refrigerator includes a smart module 301 and a smart control chip 302 (Microcontroller Unit, MCU), and the smart module 301 and the smart control chip 302 are connected through a serial communication protocol. The smart module 301 includes a noise collection module 3011 and a voice interaction module 3012. The voice interaction module 3012 is used to realize the voice interaction function, and the noise collection module 3011 is used to realize the detection and upload of working noise. The noise collection module 3022 and the voice interaction module 3012 both collect sound through a microphone 3013. When the noise collection module 3011 detects the presence of working noise, it uploads the collected sound data to the cloud server 303. When the voice interaction function is used, the voice interaction module 3012 interacts with the cloud server 304 through the spec protocol.

[0082] Based on the above application scenarios, Figure 4 is a flow chart of a noise collection method according to an exemplary embodiment. Figure 4 As shown, the following steps are included:

[0083] Step S4-1, determining whether the smart refrigerator is in working state;

[0084] If yes, execute steps S4-2-S4-5; if no, end the process.

[0085] Step S4-2, turning on voice interaction function wake-up detection and working noise detection;

[0086] Step S4-3, determining whether the voice interaction function is turned on;

[0087] If yes, go to step S4-4; if no, go to step S4-5;

[0088] Step S4-4, executing a voice interaction task;

[0089] Step S4-5, determining whether working noise is detected, that is, collecting sound data, and determining whether the collected sound data contains working noise;

[0090] If yes, upload the sound data to the cloud server; if no, end the process.

[0091] In an exemplary embodiment of the present disclosure, a noise collection device is provided. Figure 5 is a block diagram of a noise collection device according to an exemplary embodiment. Figure 5 As shown, including:

[0092] The collection module 501 is configured to collect sound data within a preset time period when the smart device is in working state;

[0093] The processing module 502 is configured to upload the sound data to a cloud server if the sound data contains working noise generated by the smart device.

[0094] In an exemplary embodiment, the processing module 502 is further configured to:

[0095] Based on a preset noise detection model, it is detected whether the sound data contains the working noise.

[0096] In an exemplary embodiment, the processing module 502 is further configured to:

[0097] Acquire historical sound data of the smart device, wherein the historical sound data includes sound data in different working states and working noise detected in the sound data;

[0098] Based on the historical sound data, the preset noise detection model is trained.

[0099] In an exemplary embodiment, the processing module 502 is further configured to:

[0100] Based on a first preset time interval, updating the historical sound data;

[0101] The preset noise detection model is trained based on the updated historical sound data.

[0102] In an exemplary embodiment, the acquisition module 501 is further configured to:

[0103] When the noise detection instruction is received, the sound data is collected.

[0104] In an exemplary embodiment, the acquisition module 501 is further configured to:

[0105] Based on the voice interaction function of the smart device, the noise detection instruction is received.

[0106] In an exemplary embodiment, the acquisition module 501 is further configured to:

[0107] When the voice interaction function of the smart device is not used, the sound data is collected based on a second preset time interval.

[0108] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0109] Figure 6 is a block diagram of a smart device 600 according to an exemplary embodiment.

[0110] Reference Figure 6 , the smart device 600 may include one or more of the following components: a processing component 602 , a memory 604 , a power component 606 , a multimedia component 608 , an audio component 610 , an input / output (I / O) interface 612 , a sensor component 614 , and a communication component 616 .

[0111] The processing component 602 generally controls the overall operation of the smart device 600, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 602 may include one or more processors 620 to execute instructions to complete all or part of the steps of the above method. In addition, the processing component 602 may include one or more modules to facilitate the interaction between the processing component 602 and other components. For example, the processing component 602 may include a multimedia module to facilitate the interaction between the multimedia component 608 and the processing component 602.

[0112] The memory 604 is configured to store various types of data to support operations on the smart device 600. Examples of such data include instructions for any application or method operating on the smart device 600, contact data, phone book data, messages, pictures, videos, etc. The memory 604 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0113] The power supply component 606 provides power to the various components of the smart device 600. The power supply component 606 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the smart device 600.

[0114] The multimedia component 608 includes a screen that provides an output interface between the smart device 600 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 608 includes a front camera and / or a rear camera. When the smart device 600 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and the rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0115] The audio component 610 is configured to output and / or input audio signals. For example, the audio component 610 includes a microphone (MIC), and when the smart device 600 is in an operation mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 604 or sent via the communication component 616. In some embodiments, the audio component 610 also includes a speaker for outputting audio signals.

[0116] I / O interface 612 provides an interface between processing component 602 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0117] The sensor assembly 614 includes one or more sensors for providing various aspects of status assessment for the smart device 600. For example, the sensor assembly 614 can detect the open / closed state of the smart device 600, the relative positioning of components, such as the display and keypad of the smart device 600, and the sensor assembly 614 can also detect the position change of the smart device 600 or a component of the smart device 600, the presence or absence of user contact with the smart device 600, the orientation or acceleration / deceleration of the smart device 600, and the temperature change of the smart device 600. The sensor assembly 614 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 614 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 614 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0118] The communication component 616 is configured to facilitate wired or wireless communication between the smart device 600 and other devices. The smart device 600 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 616 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 616 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0119] In an exemplary embodiment, the smart device 600 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

[0120] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 604 including instructions, and the instructions can be executed by the processor 620 of the smart device 600 to complete the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0121] A non-transitory computer-readable storage medium, when instructions in the storage medium are executed by a processor of a smart device, enables the smart device to execute a noise collection method, the method including any of the above methods.

[0122] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0123] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A noise collection method, characterized in that: The method comprises: When the smart device is in working state, collect sound data within a preset time period; If the sound data contains the working noise generated by the smart device, the sound data is uploaded to the cloud server.

2. The noise collection method according to claim 1, characterized in that: The method further comprises: Based on a preset noise detection model, it is detected whether the sound data contains the working noise.

3. The noise collection method according to claim 2, characterized in that: The method further comprises: Acquire historical sound data of the smart device, wherein the historical sound data includes sound data in different working states and working noise detected in the sound data; Based on the historical sound data, the preset noise detection model is trained.

4. The noise collection method according to claim 3, characterized in that: The method further comprises: Based on a first preset time interval, updating the historical sound data; The preset noise detection model is trained based on the updated historical sound data.

5. The noise collection method according to claim 1, characterized in that: The collecting of sound data within a preset time period includes: When the noise detection instruction is received, the sound data is collected.

6. The noise collection method according to claim 5, characterized in that: The receiving of the noise detection instruction comprises: Based on the voice interaction function of the smart device, the noise detection instruction is received.

7. The noise collection method according to claim 1, characterized in that: The collecting of sound data within a preset time period includes: When the voice interaction function of the smart device is not used, the sound data is collected based on a second preset time interval.

8. A noise collection device, characterized in that: The device comprises: A collection module, configured to collect sound data within a preset time period when the smart device is in working state; The processing module is configured to upload the sound data to a cloud server if the sound data contains working noise generated by the smart device.

9. A smart device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to execute the noise collection method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of an intelligent device, the intelligent device is enabled to execute the noise collection method according to any one of claims 1 to 7.

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