Method and device for driving mouth of robot to open and close through voice, robot, electronic equipment and computer readable medium

Abstract

The invention relates to a method and device for driving the mouth of a robot to be opened and closed through voice and the robot. The method comprises the steps that 1, the target voice of the robot is obtained; 2, performing framing processing on the target voice, generating a plurality of pieces of framing audio data, and enabling the time length of each piece of framing audio data to be within a preset time length; a time sequence exists among the multiple pieces of framed audio data; 3, processing the multiple pieces of framed audio data, and generating mouth motion driving data corresponding to the framed audio data; 4, according to the time sequence of the multiple pieces of framed audio data, the mouth motion driving data corresponding to the framed audio data are sent to a robot motor driving layer so as to drive the mouth of the robot to move.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence, and in particular to a method for voice-driven robot mouth opening and closing, a robot, an electronic device, and a computer-readable medium. Background Art

[0002] At present, artificial intelligence technology and robot control technology are developing rapidly. Robots with human bionic structures have gradually entered people's work and life. Consumers have higher and higher requirements for the facial interactive motion simulation of bionic robots such as companionship, reception, and service. Looking at the development history of robot bionics, from the earliest virtual human face image robots on electronic screens to static robot images with physical bionic real person structures and skin, and now there are not only real person facial skin simulation images but also facial motion detail simulation. Consumers have higher and higher requirements for robot simulation. In facial expression movement, when interacting with people, especially in different languages, the opening and closing movement of the robot's mouth is one of the movement units that people focus on.

[0003] However, the current method of driving the robot's mouth opening and closing movements with voice is relatively costly to implement. Summary of the invention

[0004] The present application provides a method for voice-driven robot mouth opening and closing, an electronic device and a computer-readable medium, which have relatively low implementation costs.

[0005] According to one aspect of an embodiment of the present application, the present application provides a method for driving a robot's mouth to open and close by voice, the method comprising:

[0006] Step 1, obtain the robot's target voice;

[0007] Step 2, performing frame processing on the target speech to generate a plurality of framed audio data, so that the time length of each framed audio data is within a predetermined time length; and there is a time sequence between the plurality of framed audio data;

[0008] Step 3, processing the plurality of framed audio data respectively to generate mouth movement driving data corresponding to the framed audio data;

[0009] Step 4: according to the timing of the plurality of framed audio data, the mouth movement driving data corresponding to the framed audio data is sent to the robot motor driving layer to drive the robot's mouth movement.

[0010] The step 3 is specifically as follows:

[0011] Step 31, performing normalization processing on the framed audio data to generate normalized audio data corresponding to the framed audio data;

[0012] Step 32, sampling the normalized audio data according to a predetermined sampling rate to generate sampled signal data;

[0013] Step 33, performing motion amplitude compensation on the sampled signal data according to the mouth movement linkage structure conversion ratio, and generating mouth movement amplitude data corresponding to the framed audio data as mouth movement driving data.

[0014] The step 31 is specifically as follows:

[0015] Step 311, filtering and noise reduction processing is performed on the framed audio data, so that the sound intensity before the speech gap of the framed audio data is 0, and noise-reduced framed audio data is generated;

[0016] Step 312, performing DC component elimination processing on the noise-reduced framed audio data to generate DC component-eliminated framed audio data;

[0017] Step 313, normalizing the framed audio data after the DC component is eliminated to generate normalized framed audio data.

[0018] The step 311 includes:

[0019] Step 3111, converting each frame of audio data of the framed audio data into amplitude data;

[0020] Step 3112, determining the starting point and the ending point of the predetermined slice according to the noise threshold of the predetermined speech gap, and slicing the amplitude data;

[0021] Step 3113, eliminating the amplitude data below the noise threshold, reorganizing the audio data, and generating framed audio data after noise reduction.

[0022] The step 312 is specifically processed according to the following formula:

[0023] fA(t)=f(t)-fD

[0024] n=fs*t

[0025]

[0026] Among them, f A(t) is the AC component of the framed audio data, that is, the framed audio data after the DC component is eliminated; f(t) is the audio signal of the framed audio data; f D is the DC component of the framed audio data; t is the length of the framed audio data, fs is the sampling rate of the framed audio data; x is each audio sample data of the framed audio data; n is the sequence number of each audio sample data.

[0027] Step 313 is specifically processed according to the following formula:

[0028] X’ is the data after normalizing each audio sampling data;

[0029]

[0030] where min(x) is the minimum value of each audio sampling data in the framed audio data; max(x) is the maximum value of each audio sampling data in the framed audio data.

[0031] Step 32 is specifically as follows:

[0032] Adopt the downsampling method to reduce the sampling frequency FSa of the normalized audio data x(n) by M times, extract one point every M points, and generate the sampled signal data y(n). The frequency of y(n) is the frequency FSr of the robot's mouth movement;

[0033] M is determined according to the following formula:

[0034]

[0035] where FSa is the sampling frequency of the normalized audio data x(n); FSr is the frequency of the robot's mouth movement.

[0036] Step 33 is specifically as follows:

[0037] When X >= a: X’ = X + b

[0038] When X < a: X’ = X

[0039] X is the sampled signal data; X’ is the mouth movement amplitude data;

[0040] where a is the correction condition threshold; b is the compensation factor value;

[0041] The determination of the correction condition threshold a and the compensation factor b value is obtained by sampling and feature extraction analysis using the motion data of the mouth motor drive connection mechanism.

[0042] According to another aspect of the embodiments of the present application, the present application provides a device for driving the opening and closing of a robot's mouth through voice. The device includes:

[0043] An audio acquisition module for acquiring the target voice of the robot;

[0044] An audio framing module for performing framing processing on the target voice to generate multiple framed audio data;

[0045] A voice data processing module, used to process the plurality of framed audio data respectively, and generate mouth movement driving data corresponding to the framed audio data;

[0046] The sending module sends the mouth movement driving data corresponding to the framed audio data to the robot according to the timing of the multiple framed audio data, so as to drive the mouth movement of the robot.

[0047] The present application also provides a robot comprising the device.

[0048] According to another aspect of an embodiment of the present application, the present application provides an electronic device, including a memory, a processor, a communication interface and a communication bus, wherein the memory stores a computer program that can be run on the processor, the memory and the processor communicate through the communication bus and the communication interface, and the processor implements the steps of the data storage and reading method when executing the computer program.

[0049] According to another aspect of the embodiment of the present application, the present application also provides a computer-readable medium having a non-volatile program code executable by a processor, wherein the program code enables the processor to execute the steps of the data storage and reading method.

[0050] The above technical solution provided by the embodiment of the present application has the following advantages over the prior art: the method provided by the embodiment of the present application, the present invention generates multiple framed audio data by framing the target voice of the robot, so that the time length of each framed audio data is between the predetermined time length; there is a time sequence between the multiple framed audio data; the multiple framed audio data are processed respectively to generate the mouth movement drive data corresponding to the framed audio data; according to the time sequence of the multiple framed audio data, the mouth movement drive data corresponding to the framed audio data is sent to the robot motor drive layer to drive the robot's mouth movement. After acquiring the voice data, the noise reduction conversion does not require complex calculations, and the computing power requirements are not high: ordinary hardware equipment can fully meet the computing power requirements, and the implementation cost is relatively low. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0053] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0054] Figure 1 A flow chart of a method for voice-driven robot mouth opening and closing provided in an embodiment of the present application;

[0055] Figure 2 The original audio data in a method for driving a robot's mouth to open and close with voice provided in an embodiment of the present application;

[0056] Figure 3 The audio data reconstructed after noise reduction in the method for opening and closing the mouth of a robot driven by voice provided in an embodiment of the present application;

[0057] Figure 4 The audio data containing a DC component after noise reduction in a method for opening and closing a robot's mouth driven by voice provided in an embodiment of the present application;

[0058] Figure 5 Normalized audio data in a method for driving a robot's mouth to open and close with voice provided in an embodiment of the present application;

[0059] Figure 6 The resampled audio data suitable for the robot's mouth movement frequency in a method for driving a robot's mouth to open and close by voice provided in an embodiment of the present application;

[0060] Figure 7 The audio data of driving the mouth movement after compensation in the method of driving the robot mouth opening and closing by voice provided in the embodiment of the present application;

[0061] Figure 8 A flow chart of another method for voice-driven robot mouth opening and closing provided in an embodiment of the present application;

[0062] Fig. 9 A structural diagram of a device for driving a robot's mouth to open and close by voice provided in an embodiment of the present application;

[0063] Fig.10 A schematic diagram of an optional electronic device structure provided in an embodiment of the present application. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0065] The disclosure below provides many different embodiments or examples to implement different structures of the present invention. In order to simplify the disclosure of the present invention, the parts and settings of specific examples are described below. Of course, they are only examples, and the purpose is not to limit the present invention. In addition, the present invention can repeat reference numbers and / or letters in different examples. This repetition is for the purpose of simplification and clarity, and does not itself indicate the relationship between the various embodiments and / or settings discussed.

[0066] In order to solve the technical problems in the prior art of serious mismatch between sound and mouth movement, high investment cost, high requirements on software and hardware for processing audio data, high delay and poor compatibility, and training independent models to drive robot mouths of different languages ​​and different sizes, the present application provides a method, electronic device and computer-readable medium for driving the opening and closing of a robot's mouth by voice, which can establish a real-time mapping relationship between voice and robot mouth motor movement with low hardware cost without using a large neural network model, and can use voice signals to control the opening and closing movement of the robot's mouth in real time, so that the mouth movement and voice are accurately matched.

[0067] like Figure 1 As shown, Figure 1 The flowchart of the method for voice-driven robot mouth opening and closing provided in an embodiment of the present invention comprises the following steps:

[0068] Step 1: Obtain the target voice of the robot. Specifically, the target voice is collected by an audio collection device or generated by a large language model.

[0069] Step 2, the target speech is framed to generate multiple framed audio data, so that the time length of each framed audio data is between a predetermined time length; and there is a time sequence between the multiple framed audio data. Specifically, the target speech is framed to generate multiple framed audio data, so that the time length of each frame data can be between 1 and 2 seconds.

[0070] Step 3: Process the plurality of framed audio data respectively to generate mouth movement driving data corresponding to the framed audio data.

[0071] Step 4: according to the timing of the plurality of framed audio data, the mouth movement driving data corresponding to the framed audio data is sent to the robot motor driving layer to drive the robot's mouth movement.

[0072] The present invention can solve the problem of establishing a real-time mapping relationship between speech and robot mouth motor movement with low hardware cost without using a large neural network model. It can use speech signals to control the robot's mouth opening and closing movement in real time, so that the mouth movement and speech are accurately matched.

[0073] In this embodiment, the above step 3 specifically includes:

[0074] Step 31, performing normalization processing on the framed audio data to generate normalized audio data corresponding to the framed audio data;

[0075] Step 32, sampling the normalized audio data according to a predetermined sampling rate to generate sampled signal data;

[0076] Step 33, performing motion amplitude compensation on the sampled signal data according to the mouth movement linkage structure conversion ratio, and generating mouth movement amplitude data corresponding to the framed audio data as mouth movement driving data.

[0077] In this embodiment, the above step 31 specifically includes:

[0078] Step 311, filtering and denoising the framed audio data, so that the sound intensity before the speech gap of the framed audio data is 0, and generating denoised framed audio data. The speech filtering and denoising method specifically includes:

[0079] Step 3111, determine the noise threshold of the speech gap, which can usually be 30 to 40

[0080] dB.

[0081] Step 3112, converting the audio data of each frame into amplitude data, and then slicing it according to the starting and cutting-off points of the noise threshold.

[0082] Step 3113, eliminate the slice data below the threshold, and then reorganize the audio data. Figure 2 The original audio data is shown as Figure 3 Shown is the audio data after noise removal and reconstruction.

[0083] Step 312: the denoised audio data is processed as follows: Figure 4 As shown, it contains DC components and needs to be eliminated. The audio signal is f(t), which can be decomposed into the sum of the DC component fD and the AC component fA(t), that is:

[0084] fA(t)=f(t)-fD

[0085] Wherein, f A(t) is the AC component of the framed audio data, that is, the framed audio data after the DC component is eliminated; f(t) is the audio signal of the framed audio data; f D is the DC component of the framed audio data;

[0086] In mono audio data with a length of t and a sampling rate of fs, the number of audio data is n and each audio sample data is x.

[0087] n=fs*t

[0088]

[0089] Wherein: t is the length of the framed audio data, fs is the sampling rate of the framed audio data; x is each audio sample data of the framed audio data; and n is the sequence number of each audio sample data.

[0090] Step 313, the audio after the DC component is eliminated is normalized.

[0091] X' is the normalized data for each sample data:

[0092]

[0093] Wherein, min(x) is the minimum value of each audio sample data weight of the framed audio data;

[0094] max(x) is the maximum value of each audio sample data weight of the framed audio data.

[0095] like Figure 5 The data shown are normalized, and all the data are between [1,-1].

[0096] Since the robot's mouth movement frequency does not match the audio sampling rate, the sampling rate needs to be reduced and the audio data needs to be resampled.

[0097] In this embodiment, the above step 32 specifically includes:

[0098] According to the conversion ratio of the mouth movement linkage structure, the new sampled data is compensated for the movement amplitude. The mouth movement amplitude data is generated. At this time, the sampling frequency of the audio is FSa, and the frequency of the robot's mouth movement is FSr. FSa is much larger than FSr. Therefore, downsampling (decimation) is used to reduce the sampling frequency FSa of the signal x(n) by M times. The main step is to extract a point every M points to form the extracted signal y(n). The frequency of y(n) is the frequency FSr of the robot's mouth movement.

[0099] M is determined according to the following formula:

[0100]

[0101] where FSa is the sampling frequency of the normalized audio data x(n); F Sr is the frequency of the robot's mouth movement.

[0102] As Figure 6 shown is the data suitable for the robot's mouth movement frequency after resampling.

[0103] In this embodiment, step 33 above specifically includes:

[0104] For the resampled data, each data X needs to be determined according to the driving characteristics of the robot's mouth motor and structural components. For the determination of the correction condition a and the compensation factor b values, a large amount of movement data needs to be used by the mouth motor drive connection mechanism for sampling and feature extraction analysis. An additional correction value is added. This correction value is applied when X reaches the set threshold (a); if not reached, the X value itself is used, that is:

[0105] When X >= a: X' = X + b

[0106] When X < a: X' = X

[0107] where: X is the sampled signal data, X' is the mouth movement amplitude data, a is the correction condition threshold, and b is the compensation factor value.

[0108] As Figure 7 shown is the compensated mouth movement drive data.

[0109] After downsampling and compensation correction, the data is now normalized and all within the movement range of [0, 1], which can adapt to the mouth drive structures of robots with different opening amplitudes (male, female, child).

[0110] In this embodiment, step 4 above specifically includes:

[0111] According to the sampling rate and timing of the data, the data is sent to the robot motor drive layer to drive the robot's mouth movement.

[0112] The present invention has the following beneficial effects:

[0113] Different from the prior art, after voice data noise reduction and conversion, it can directly drive the opening and closing movement of the robot's mouth. Compared with other driving methods, this method has the following advantages:

[0114] Low computing power requirement: After obtaining the voice data, noise reduction and conversion do not require complex calculations, and ordinary hardware devices can fully meet the computing power requirements;

[0115] Low latency: After acquiring the language data, it can be quickly converted into robot mouth drive data, and the user can hardly feel the delay of sound and mouth movement;

[0116] Strong compatibility. The present invention is compatible with different languages. After conversion, different languages ​​can perfectly drive the robot's mouth movement to achieve synchronization of speech and movement.

[0117] It has wide applicability. The driving data generated by this driving algorithm can be suitable for robots with different mouth sizes (male, female, children, etc.).

[0118] Figure 8 A flowchart of another method for voice-driven robot mouth opening and closing provided in an embodiment of the present application; the method comprises:

[0119] The audio frame data can be obtained through a voice pickup device or generated through model speech synthesis.

[0120] Filtering and noise reduction processing;

[0121] Eliminate DC components;

[0122] Normalization processing;

[0123] Resampling;

[0124] Compensation correction;

[0125] The data transmitter sends data to the electrical drive data receiver to drive the mouth motor and structural parts.

[0126] According to another aspect of the embodiment of the present application, Fig. 9 As shown, corresponding to the method for driving the robot's mouth to open and close by voice in the above embodiment, this embodiment provides a device for driving the robot's mouth to open and close by voice, and the device includes:

[0127] The audio acquisition module 901 is used to obtain the target voice of the robot;

[0128] The audio framing module 902 is used to perform framing processing on the target speech to generate a plurality of framed audio data;

[0129] The voice data processing module 903 is used to process the plurality of framed audio data respectively to generate mouth movement driving data corresponding to the framed audio data;

[0130] The sending module 904 sends the mouth movement driving data corresponding to the framed audio data to the robot according to the time sequence of the multiple framed audio data, so as to drive the mouth movement of the robot.

[0131] The present application also provides a robot comprising the device.

[0132] According to another aspect of the embodiments of the present application, the present application provides an electronic device, such as Fig.10 As shown, it includes a memory 113, a processor 111, a communication interface 112 and a communication bus 114. The memory 113 stores a computer program that can be run on the processor 111. The memory 113 and the processor 111 communicate through the communication interface 112 and the communication bus 114. When the processor 111 executes the computer program, the steps of the above-mentioned data storage and reading method are implemented.

[0133] The memory and processor in the above electronic device communicate via a communication bus and a communication interface. The communication bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus may be divided into an address bus, a data bus, a control bus, etc.

[0134] The memory may include a random access memory (RAM) or a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0135] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0136] According to another aspect of the embodiments of the present application, a computer program product or a computer program is provided, the computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the steps of the data storage and reading method in any of the above embodiments.

[0137] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0138] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a general hardware platform, and of course, by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0139] It should be understood that the terms used herein are only for the purpose of describing specific example embodiments and are not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms "one", "an" and "said" as used herein may also be meant to include plural forms. The terms "include", "comprise", "contain", and "have" are inclusive, and therefore specify the existence of stated features, steps, operations, elements and / or parts, but do not exclude the existence or addition of one or more other features, steps, operations, elements, parts, and / or combinations thereof. The method steps, processes, and operations described herein are not interpreted as necessarily requiring them to be performed in the specific order described or illustrated, unless the execution order is clearly indicated. It should also be understood that additional or alternative steps may be used.

[0140] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for driving a robot's mouth to open and close by voice, characterized in that: include: Step 1, obtain the robot's target voice; Step 2, performing frame processing on the target speech to generate a plurality of framed audio data, so that the time length of each framed audio data is within a predetermined time length; and there is a time sequence between the plurality of framed audio data; Step 3, processing the plurality of framed audio data respectively to generate mouth movement driving data corresponding to the framed audio data; Step 4: according to the timing of the plurality of framed audio data, the mouth movement driving data corresponding to the framed audio data is sent to the robot motor driving layer to drive the robot's mouth movement.

2. The method according to claim 1, characterized in that The step 3 is specifically as follows: Step 31, performing normalization processing on the framed audio data to generate normalized audio data corresponding to the framed audio data; Step 32, sampling the normalized audio data according to a predetermined sampling rate to generate sampled signal data; Step 33, performing motion amplitude compensation on the sampled signal data according to the mouth movement linkage structure conversion ratio, and generating mouth movement amplitude data corresponding to the framed audio data as mouth movement driving data.

3. The method according to claim 2, characterized in that The step 31 is specifically as follows: Step 311, filtering and noise reduction processing is performed on the framed audio data, so that the sound intensity before the speech gap of the framed audio data is 0, and noise-reduced framed audio data is generated; Step 312, performing DC component elimination processing on the noise-reduced framed audio data to generate DC component-eliminated framed audio data; Step 313, normalizing the framed audio data after the DC component is eliminated to generate normalized framed audio data.

4. The method according to claim 3, characterized in that The step 311 includes: Step 3111, converting each frame of audio data of the framed audio data into amplitude data; Step 3112, determining the starting point and the ending point of the predetermined slice according to the noise threshold of the predetermined speech gap, and slicing the amplitude data; Step 3113, eliminating the amplitude data below the noise threshold, reorganizing the audio data, and generating framed audio data after noise reduction.

5. The method according to claim 3, characterized in that: The step 312 is specifically processed according to the following formula: fA(t)=f(t)-fD n=fs*t Wherein, f A(t) is the AC component of the framed audio data, that is, the framed audio data after the DC component is eliminated; f(t) is the audio signal of the framed audio data; f D is the DC component of the framed audio data; t is the length of the framed audio data, fs is the sampling rate of the framed audio data; x is each audio sample data of the framed audio data; n is the sequence number of each audio sample data; Or the step 313 is specifically processed according to the following formula: X' is the normalized data of each audio sampling data; Wherein, min(x) is the minimum value of the weight of each audio sample data of the framed audio data; max(x) is the maximum value of the weight of each audio sample data of the framed audio data.

6. The method according to claim 5, characterized in that The step 32 is specifically as follows: Adopt downsampling to reduce the sampling frequency FSa of the normalized audio data x(n) by M times, extract one point every M points to generate the sampled signal data y(n), and the frequency of y(n) is the frequency FSr of the robot's mouth movement; M is determined according to the following formula: where, FSa is the sampling frequency of the normalized audio data x(n); FSr is the frequency of the robot's mouth movement; Or, step 33 is specifically: When X >= a: X' = X + b When X < a: X' = X where, X is the sampled signal data; X' is the mouth movement amplitude data; a is the correction condition threshold; b is the compensation factor value; The determination of the correction condition threshold a and the compensation factor b value is obtained by sampling and feature extraction analysis using the motion data of the mouth motor drive connection mechanism.

7. A device for driving a robot's mouth to open and close by voice, characterized in that: The device includes: An audio acquisition module for acquiring the target voice of the robot; An audio framing module for performing framing processing on the target voice to generate multiple framed audio data; A voice data processing module for respectively processing the multiple framed audio data to generate the mouth movement drive data corresponding to the framed audio data; A sending module for sending the mouth movement drive data corresponding to the framed audio data to the robot according to the time sequence of the multiple framed audio data to drive the mouth movement of the robot.

8. A robot, characterized in that: Including the device according to claim 8.

9. An electronic device, comprising a memory, a processor, a communication interface and a communication bus, wherein the memory stores a computer program that can be run on the processor, and the memory and the processor communicate through the communication bus and the communication interface, characterized in that: When the processor executes the computer program, it implements the data storage and reading method according to any one of claims 1 to 6 above.

10. A computer readable medium having a non-volatile program code executable by a processor, characterized in that: The program code causes the processor to execute the method according to any one of claims 1 to 6.

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