Multi-screen interaction processing system and method based on smart television

Abstract

The invention discloses a multi-screen interaction processing system and method based on a smart television, and relates to the technical field of multi-screen interaction processing, and the system comprises a data collection module, a control model creation module, a multi-screen interaction data monitoring module and a multi-screen interaction dynamic processing module. Voice data output by users during multi-screen interaction and historical volume control data of the smart television are acquired through the data acquisition module, and a volume adjustment control model is established for each user through the control model establishment module. A multi-screen interaction data monitoring module monitors voice data output by a current user and parameters of the current television when the current user performs multi-screen interaction with the smart television, and a multi-screen interaction dynamic processing module generates smart television adjustment planning modes in different multi-screen interaction scenes. Parameter adjustment is performed according to the planning mode, so that parameter adaptive adjustment of the smart television is realized, and the convenience of use of the multi-screen interaction function is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-screen interaction processing, and specifically to a multi-screen interaction processing system and method based on a smart TV. Background Art

[0002] The multi-screen interaction function of a smart TV refers to the function of projecting the content of devices such as mobile phones, tablets, or computers onto the smart TV screen through wireless or wired means, realizing interaction and content sharing between multiple devices. When using a smart TV for multi-screen interaction, users can project the video on the terminal onto the smart TV for viewing, and can control the smart TV through voice to realize the function of controlling the playing content;

[0003] When performing multi-screen interaction, if the volume of the content played on the smart TV is inappropriate, the user needs to adjust the volume through voice control. Generally, the user needs to output specific voice commands for control, such as: increasing or decreasing the volume by how much, etc. And the volume adjusted based on the user's subjective judgment may still be inappropriate. Therefore, it is necessary to repeatedly input voice commands until the volume of the playing content is adjusted to an appropriate value, and the user also needs to judge how much volume should be adjusted, which reduces the convenience of using the multi-screen interaction function; Secondly, since there will be a situation where the voice information of multiple users regarding volume adjustment is recognized simultaneously, the prior art lacks a dynamic adaptive volume processing method when recognizing the voice information of multiple users, and cannot adaptively adjust the volume to meet the needs of multiple users at the same time. Summary of the Invention

[0004] The purpose of the present invention is to provide a multi-screen interaction processing system and method based on a smart TV to solve the problems proposed in the prior art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A multi-screen interaction processing system based on a smart TV, the system includes a data acquisition module, a control model creation module, a multi-screen interaction data monitoring module, and a multi-screen interaction dynamic processing module;

[0006] Collect the voice data output by users during previous multi-screen interactions and the historical volume control data of the smart TV through the data acquisition module;

[0007] Establish a volume adjustment control model for each user who has controlled the same smart TV through the control model creation module;

[0008] Monitor the voice data output by the current user and the parameter data of the current TV when the current user performs multi-screen interaction with the smart TV through the multi-screen interaction data monitoring module;

[0009] The multi-screen interaction dynamic processing module generates an intelligent TV adjustment planning method in different multi-screen interaction scenarios according to the volume adjustment control model, and adjusts parameters according to the planning method.

[0010] Preferably, the data acquisition module includes a voice information acquisition unit, a database generation unit, and a historical control data acquisition unit;

[0011] The voice information acquisition unit is used to collect the voices of users who have previously controlled the intelligent TV by voice during multi-screen interaction. The voice data is collected after the user grants permission.

[0012] The database generation unit is used to store the collected voice data of each user and generate a voice database, and set the levels of all users controlling the intelligent TV. The levels are set by the system by default. The voice database contains the control level data of the users and the corresponding voice data of the users.

[0013] The historical control data acquisition unit is used to collect the voice commands received by the intelligent TV when different users previously controlled the volume of the intelligent TV by voice, extract control data from the voice commands. The control data includes the increased volume and the decreased volume data. The historical control data acquisition unit is also used to collect the initial volume data of the TV before adjusting the volume.

[0014] Preferably, the control model creation module includes a historical data training unit and an adjustment control model establishment unit;

[0015] The historical data training unit is used to combine and process the control data corresponding to each user and the initial volume data of the TV before adjusting the volume, and perform fitting training on the combined and processed data.

[0016] The adjustment control model establishment unit is used to establish a volume adjustment control model for each user to the intelligent TV according to the data after fitting training. The volume adjustment control model includes a volume increase control model and a volume decrease control model.

[0017] Preferably, the multi-screen interaction data monitoring module includes a voice data receiving unit, an identity and instruction recognition unit, and a monitoring data output unit;

[0018] The voice data receiving unit is used to receive the voice command about volume adjustment output by the current user.

[0019] The identity and instruction recognition unit is used to identify the received voice command: match the voice signal features of the voice command with the voice commands in the voice database, confirm the user corresponding to the voice command, and obtain the level of the user controlling the intelligent TV.

[0020] The monitoring data output unit is used to monitor the initial volume data of the current TV set.

[0021] Preferably, the multi-screen interaction dynamic processing module includes a first planning mode generating unit, a second planning mode generating unit, and an adaptive adjustment unit;

[0022] The first planning mode generating unit is used to generate a first planning mode for volume adjustment when the number of users outputting voice commands currently is 1: if the voice command output by the user is to increase the volume, input the initial volume of the current TV set into the volume increase control model corresponding to the current user, and output the current optimal volume increase value; if the voice command output by the user is to decrease the volume, input the initial volume of the current TV set into the volume decrease control model corresponding to the current user, and output the current optimal volume decrease value;

[0023] The second planning mode generating unit is used to generate a second planning mode for volume adjustment when the number of users outputting voice commands currently is greater than 1 and all users output the same voice command, where the same voice command means that all users have output the voice command of "increase the volume" or all users have output the voice command of "decrease the volume": if the voice command output by the user is to increase the volume, input the initial volume of the current TV set into the volume increase control models corresponding to all users, and set the current optimal volume increase value according to the volume values output by each model; if the voice command output by the user is to decrease the volume, input the initial volume of the current TV set into the volume decrease control models corresponding to all users, and set the current optimal volume decrease value according to the volume values output by each model;

[0024] The adaptive adjustment unit is used to adjust the volume of the smart TV according to the first planning mode when the number of users outputting voice commands currently is 1; and adjust the volume of the smart TV according to the second planning mode when the number of users outputting voice commands currently is greater than 1 and all users output the same voice command.

[0025] A multi-screen interaction processing method based on a smart TV includes the following steps:

[0026] S1: Collect the voice data output by users during previous multi-screen interactions and the historical volume control data of the smart TV;

[0027] S2: Establish a volume adjustment control model for each user who has controlled the same smart TV respectively;

[0028] S3: When the current user conducts multi-screen interaction with the smart TV, monitor the voice data output by the current user and the parameter data of the current TV set;

[0029] S4: Generate the intelligent TV adjustment planning methods for different multi-screen interaction scenarios according to the volume adjustment control model, and adjust the parameters of the intelligent TV according to the planning methods.

[0030] Preferably, in step S1: Collect the voices of users who have controlled the intelligent TV by voice during previous multi-screen interactions, store the collected voice data of each user and generate a voice database, set the levels of all users controlling the intelligent TV as {1, 2,... N}, where N represents the number of users who have controlled the intelligent TV by voice, collect the voice commands received by the intelligent TV when different users have controlled the volume of the intelligent TV by voice in the past, extract control data from the voice commands, and the control data includes the increased volume and the decreased volume data, and collect the initial volume data of the TV before adjusting the volume in the past.

[0031] Preferably, in step S2: Retrieve the set of volumes increased by a randomly selected user each time in the past as {G1, G2,... G m}, the set of initial volumes of the TV before increasing the volume as {g1, g2,... g m}, where m represents the number of times a randomly selected user has increased the volume of the TV in the past, the set of volumes decreased by the corresponding user each time in the past as {H1, H2,... H n}, the set of initial volumes of the TV before decreasing the volume as {h1, h2,... h n}, where n represents the number of times a randomly selected user has decreased the volume of the TV in the past, perform combination processing on the retrieved data to obtain the first training data {(g1, G1), (g2, G2),... (g m , G m )}, obtain the second training data {(h1, H1), (h2, H2),... (h n , H n )}, perform linear fitting on the first training data to establish the volume increase control model of a randomly selected user: y = θ1 * x + θ2, where θ1 and θ2 represent the fitting coefficients of the volume increase control model, * represents the multiplication sign, x represents the independent variable representing the initial volume before increase in the volume increase control model, and y represents the dependent variable representing the increased volume in the volume increase control model, perform linear fitting on the second training data to establish the volume decrease control model of a randomly selected user: Y = α1 * X + α2, where α1 and α2 represent the fitting coefficients of the volume decrease control model, X represents the independent variable representing the initial volume before decrease in the volume decrease control model, and Y represents the dependent variable representing the decreased volume in the volume decrease control model, and establish the volume increase control model and the volume decrease control model for all users in the same way;

[0032] By collecting the historical data of different users controlling and adjusting the smart TV when using the multi-screen interaction function, analyzing the volume values that meet the requirements adjusted by different users with different initial volumes, and establishing a volume control model for different users. Considering that the requirements of the same user may be different when increasing and decreasing the volume, a volume increase control model and a volume decrease control model are established for the user respectively, which increases the probability that the smart TV can meet the user's needs after adaptive adjustment according to the model. When the user performs voice control to adjust the volume of the smart TV, there is no need to output specific voice commands. Just output the command to increase the volume or decrease the volume, and the system can adaptively adjust the TV volume according to the model, avoiding the situation of repeatedly inputting voice commands until the volume of the playing content is adjusted to an appropriate value, and improving the convenience of using the multi-screen interaction function.

[0033] Preferably, in step S3: Receive the voice command regarding volume adjustment output by the current user, identify the received voice command, confirm the user corresponding to the voice command, obtain the level of the user controlling the smart TV, and monitor that the initial volume of the current TV is L.

[0034] Preferably, in step S4: If the number of users currently outputting voice commands regarding volume adjustment is 1, generate the first planning method for volume adjustment: If the voice command output by the current user is to increase the volume, the volume increase control model corresponding to the current user is extracted as: y1 = a * x1 + b, where a and b represent the fitting coefficients of the volume increase control model corresponding to the current user, x1 represents the independent variable representing the initial volume before increase in the volume increase control model corresponding to the current user, and y1 represents the dependent variable representing the increased volume in the volume increase control model corresponding to the current user. Let x1 = L, and output the current optimal increased volume value as a * L + b, and control the volume of the smart TV to increase to L + (a * L + b); If the voice command output by the current user is to decrease the volume, the volume decrease control model corresponding to the current user is extracted as: Y1 = c * X1 + d, where c and d represent the fitting coefficients of the volume decrease control model corresponding to the current user, X1 represents the independent variable representing the initial volume before decrease in the volume decrease control model corresponding to the current user, and Y1 represents the dependent variable representing the decreased volume in the volume decrease control model corresponding to the current user. Let X1 = L, and output the current optimal decreased volume value as c * L + d, and control the volume of the smart TV to decrease to L - (c * L + d);

[0035] If the number of users currently outputting voice commands for volume adjustment is greater than 1 and all users output the same voice command, generate a second method for volume adjustment planning: Obtain that the number of users outputting the same voice command for volume adjustment is k, where k > 1. If the voice command output by the user is to increase the volume, input L into the volume increase control models corresponding to all users, and obtain the set of volume increase values output by the models as {A1, A2,... A k}, retrieve the set of levels of k users as {P1, P2,... P k}, set the current optimal volume increase value as F, F = ∑ k i＝1 [(P i / ∑ k i＝1 (P i )) * A i , where i represents the i-th user among the k users, and control the volume of the smart TV to increase to L + F; if the voice command output by the user is to decrease the volume, input L into the volume decrease control models corresponding to all users, and obtain the set of volume decrease values output by the models as {B1, B2,... B k}, set the current optimal volume decrease value as f, f = ∑ k i＝1 [(P i / ∑ k i＝1 (P i )) * B i , and control the volume of the smart TV to decrease to L - f;

[0036] When adjusting the volume of the smart TV according to the models corresponding to the users, not only the situation where only one user outputs a voice command is considered, but also the situation where multiple users may output the same voice command simultaneously to adjust the volume. In this case, the optimal adjustment value is set by combining the parameters output by multiple models and the levels of the users. While the adjustment value tends to meet the needs of the highest-level users, the probability that the adjusted volume meets the needs of multiple users is increased, further enhancing the convenience of multi-user control of the smart TV.

[0037] Compared with the prior art, the beneficial effects of the present invention are:

[0038] The present invention collects the historical data of different users controlling and adjusting a smart TV when using the multi-screen interaction function, analyzes the volume values that meet the requirements adjusted by different users with different initial volumes, and establishes a volume control model for different users. Considering that the requirements of the same user may be different when increasing and decreasing the volume, a volume increase control model and a volume decrease control model are established for the user respectively, which increases the probability that the requirements of the user can be met after the smart TV is adaptively adjusted according to the model. When the user performs voice control to adjust the volume of the smart TV, there is no need to output specific voice commands. Just output an instruction to increase or decrease the volume, and the system can adaptively adjust the TV volume according to the model, avoiding the situation of repeatedly inputting voice commands until the volume of the playing content is adjusted to an appropriate value, and improving the convenience of using the multi-screen interaction function.

[0039] When adjusting the volume of the smart TV according to the model corresponding to the user, not only the situation where only one user outputs a voice command is considered, but also the situation where multiple people may output the same voice command to adjust the volume at the same time is considered. In this case, the optimal adjustment value is set by combining the parameters output by multiple models and the level of the user. While the adjustment value tends to meet the needs of the highest-level user, the probability that the adjusted volume meets the needs of multiple users is increased, further improving the convenience of multiple users controlling the smart TV. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a schematic structural diagram of a multi-screen interaction processing system based on a smart TV according to the present invention;

[0041] Figure 2 is a schematic flow diagram of a multi-screen interaction processing method based on a smart TV according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0043] Embodiment 1:

[0044] As Figure 1As shown in the figure, this embodiment provides a multi-screen interaction processing system based on a smart TV. The system includes: a data acquisition module, a control model creation module, a multi-screen interaction data monitoring module, and a multi-screen interaction dynamic processing module. The data acquisition module collects the voice data output by the user during previous multi-screen interactions and the historical volume control data of the smart TV. The control model creation module separately establishes a volume adjustment control model for each user who has controlled the same smart TV. The multi-screen interaction data monitoring module monitors the voice data output by the current user and the parameter data of the current TV during the multi-screen interaction between the current user and the smart TV. The multi-screen interaction dynamic processing module generates an adjustment plan for the smart TV in different multi-screen interaction scenarios according to the volume adjustment control model and adjusts the parameters according to the plan.

[0045] The data acquisition module includes a voice information acquisition unit, a database generation unit, and a historical control data acquisition unit. The voice information acquisition unit is used to collect the voices of users who have controlled the smart TV by voice during previous multi-screen interactions, and the voice data is collected after the user grants permission. The database generation unit is used to store the voice data of each user collected and generate a voice database, set the levels of all users controlling the smart TV, which are set by the system by default. The voice database contains the control level data of the users and the corresponding voice data of the users. The historical control data acquisition unit is used to collect the voice commands received by the smart TV when different users have controlled the volume of the smart TV by voice in the past, extract the control data from the voice commands, and the control data includes the increased volume and the decreased volume data. The historical control data acquisition unit is also used to collect the initial volume data of the TV before adjusting the volume.

[0046] The control model creation module includes a historical data training unit and an adjustment control model establishment unit. The historical data training unit is used to combine the control data corresponding to each user and the initial volume data of the TV before adjusting the volume, and perform fitting training on the combined data. The adjustment control model establishment unit is used to establish a volume adjustment control model for each user to the smart TV according to the data after fitting training. The volume adjustment control model includes a volume increase control model and a volume decrease control model.

[0047] The multi-screen interaction data monitoring module includes a voice data receiving unit, an identity and instruction recognition unit, and a monitoring data output unit. The voice data receiving unit is used to receive the voice command about volume adjustment output by the current user. The identity and instruction recognition unit is used to recognize the received voice command: match the voice signal features of the voice command with the voice commands in the voice database, confirm the user corresponding to the voice command, and obtain the level of the corresponding user controlling the smart TV. The monitoring data output unit is used to monitor the initial volume data of the current TV.

[0048] The multi-screen interaction dynamic processing module includes a first planning mode generation unit, a second planning mode generation unit, and an adaptive adjustment unit. The first planning mode generation unit is used to generate a first planning mode for volume adjustment when the number of users outputting the current voice command is 1: if the voice command output by the user is to increase the volume, the initial volume of the current TV is input into the volume increase control model corresponding to the current user, and the current optimal volume increase value is output; if the voice command output by the user is to decrease the volume, the initial volume of the current TV is input into the volume decrease control model corresponding to the current user, and the current optimal volume decrease value is output. The second planning mode generation unit is used to generate a second planning mode for volume adjustment when the number of users outputting the current voice command is greater than 1 and all users output the same voice command, where the same voice command means that all users have output the voice command of "increase the volume" or all users have output the voice command of "decrease the volume": if the voice command output by the user is to increase the volume, the initial volume of the current TV is input into the volume increase control models corresponding to all users, and the current optimal volume increase value is set according to the volume values output by each model; if the voice command output by the user is to decrease the volume, the initial volume of the current TV is input into the volume decrease control models corresponding to all users, and the current optimal volume decrease value is set according to the volume values output by each model. The adaptive adjustment unit is used to adjust the volume of the smart TV according to the first planning mode when the number of users outputting the current voice command is 1; and to adjust the volume of the smart TV according to the second planning mode when the number of users outputting the current voice command is greater than 1 and all users output the same voice command.

[0049] Embodiment 2:

[0050] As Figure 2 shown, this embodiment provides a multi-screen interaction processing method based on a smart TV, which is implemented based on the multi-screen interaction processing system in the embodiment, and specifically includes the following steps:

[0051] S1: Collect the voice data output by users during previous multi-screen interactions and the historical volume control data of the smart TV: When collecting data during previous multi-screen interactions, collect the voices of users who have controlled the smart TV by voice. Store the collected voice data of each user and generate a voice database. Set the control levels of all users for the smart TV as {1, 2,... N}, where N represents the number of users who have controlled the smart TV by voice. When the TV recognizes the voices of more than one user, preferentially execute the voice command of the user with the highest level. For example, if the voices of users with levels 1, 2, and 3 are recognized simultaneously, preferentially execute the voice command of the user with level 3. Collect the voice commands received by the smart TV when different users have controlled the volume of the smart TV by voice in the past. Extract the control data from the voice commands. The control data includes the increased volume and the decreased volume data. Collect the initial volume data of the TV before adjusting the volume in the past.

[0052] S2: Establish a volume adjustment control model for each user who has controlled the same smart TV: Retrieve the set of volumes increased by a randomly selected user each time the TV was controlled in the past as {G1, G2,... G m}, and the set of initial volumes of the TV before the volume increase as {g1, g2,... g m}, where m represents the number of times a randomly selected user has increased the volume of the TV in the past. The set of volumes decreased by the corresponding user each time the TV was controlled in the past is {H1, H2,... H n}, and the set of initial volumes of the TV before the volume decrease is {h1, h2,... h n}, where n represents the number of times a randomly selected user has decreased the volume of the TV in the past. Combine the retrieved data to obtain the first training data {(g1, G1), (g2, G2),... (g m , G m )}, and obtain the second training data {(h1, H1), (h2, H2),... (h n , H n)}, after linearly fitting the first training data, a volume increase control model for a randomly selected user is established: y = θ1 * x + θ2, where θ1 and θ2 represent the fitting coefficients of the volume increase control model, * represents the multiplication sign, x represents the independent variable representing the initial volume before increase in the volume increase control model, and y represents the dependent variable representing the increased volume in the volume increase control model. After linearly fitting the second training data, a volume decrease control model for a randomly selected user is established: Y = α1 * X + α2, where α1 and α2 represent the fitting coefficients of the volume decrease control model, X represents the independent variable representing the initial volume before decrease in the volume decrease control model, and Y represents the dependent variable representing the decreased volume in the volume decrease control model. The volume increase control model and the volume decrease control model are established for all users in the same way. Each user corresponds to a volume increase control model and a volume decrease control model;

[0053] S3: When the current user conducts multi-screen interaction with the smart TV, monitor the voice data output by the current user and the parameter data of the current TV: Receive the voice command for volume adjustment output by the current user, identify the received voice command, confirm the user corresponding to the voice command, obtain the level of the user controlling the smart TV, and monitor that the initial volume of the current TV is L;

[0054] S4: Generate the adjustment planning method of the smart TV in different multi-screen interaction scenarios according to the volume adjustment control model, and adjust the parameters of the smart TV according to the planning method: If the number of users currently outputting the voice command for volume adjustment is 1, generate the first planning method for volume adjustment: If the voice command output by the current user is to increase the volume, extract the volume increase control model corresponding to the current user as: y1 = a * x1 + b, where a and b represent the fitting coefficients of the volume increase control model corresponding to the current user, x1 represents the independent variable representing the initial volume before increase in the volume increase control model corresponding to the current user, and y1 represents the dependent variable representing the increased volume in the volume increase control model corresponding to the current user. Let x1 = L, and output the current optimal increased volume value as a * L + b, and control the volume of the smart TV to increase to L + (a * L + b); If the voice command output by the current user is to decrease the volume, extract the volume decrease control model corresponding to the current user as: Y1 = c * X1 + d, where c and d represent the fitting coefficients of the volume decrease control model corresponding to the current user, X1 represents the independent variable representing the initial volume before decrease in the volume decrease control model corresponding to the current user, and Y1 represents the dependent variable representing the decreased volume in the volume decrease control model corresponding to the current user. Let X1 = L, and output the current optimal decreased volume value as c * L + d, and control the volume of the smart TV to decrease to L - (c * L + d);

[0055] If the number of users currently outputting voice commands for volume adjustment is greater than 1 and all users output the same voice command, generate a second planning method for volume adjustment: Obtain that the number of users outputting the same voice command for volume adjustment is k, where k > 1. If the voice command output by the user is to increase the volume, input L into the volume increase control models corresponding to all users, and obtain the set of volume increase values output by the models as {A1, A2,... A k}, retrieve the set of levels of k users as {P1, P2,... P k}, set the current optimal volume increase value as F, F = ∑ k i＝1 [(P i / ∑ k i＝1 (P i ))*A i , where i represents the i-th user among the k users, control the volume of the smart TV to increase to L + F. If F is not an integer, round F; if the voice command output by the user is to decrease the volume, input L into the volume decrease control models corresponding to all users, and obtain the set of volume decrease values output by the models as {B1, B2,... B k}, set the current optimal volume increase value as f, f = ∑ k i＝1 [(P i / ∑ k i＝1 (P i ))*B i , control the volume of the smart TV to decrease to L - f. If f is not an integer, round f;

[0056] For example: It is monitored that the number of users currently outputting voice commands for volume adjustment is 3 and all users output the same voice command. Use the second planning method to adjust the volume of the smart TV. It is monitored that the initial volume of the current TV is L = 15. Obtain that the voice commands output by the current 3 users are to increase the volume. Input 15 into the volume increase control models corresponding to the 3 users respectively, make the independent variables in each model equal to 15, and obtain the set of volume increase values output by each model as {A1, A2, A3} = {5, 7, 8}. Retrieve the set of levels of the 3 users as {P1, P2, P3} = {1, 2, 5}. Set the current optimal volume increase value as F, F = ∑ k i＝1 [(P i / ∑ k i＝1 (P i ))*A i ≈7, and control the volume of the smart TV to increase to 22.

[0057] It is obvious to those skilled in the art that the present invention is not limited to the details of the above-described exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, in any aspect, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be construed as limiting the claims involved.

Claims

1. A multi-screen interactive processing system based on a smart TV, characterized in that: The system includes a data acquisition module, a control model creation module, a multi-screen interactive data monitoring module and a multi-screen interactive dynamic processing module; The data collection module collects the voice data output by the user during the previous multi-screen interaction and the historical volume control data of the smart TV; The control model creation module is used to establish a volume adjustment control model for each user who has controlled the same smart TV; When the current user performs multi-screen interaction with the smart TV, the multi-screen interaction data monitoring module monitors the voice data output by the current user and the parameter data of the current TV; The multi-screen interactive dynamic processing module generates smart TV adjustment planning methods under different multi-screen interactive scenarios according to the volume adjustment control model, and performs parameter adjustment according to the planning method.

2. The multi-screen interactive processing system based on a smart TV according to claim 1, characterized in that: The data acquisition module includes a voice information acquisition unit, a database generation unit and a historical control data acquisition unit; The voice information collection unit is used to collect the voice of the user who has previously controlled the smart TV by voice during multi-screen interaction; The database generation unit is used to store the collected voice data of each user and generate a voice database, set the level of control of the smart TV by all users, and the voice database contains the control level data of the user and the voice data of the corresponding user; The historical control data collection unit is used to collect voice commands received by the smart TV when different users controlled the volume of the smart TV by voice in the past, and extract control data from the voice commands, wherein the control data includes increased volume and decreased volume data. The historical control data collection unit is also used to collect initial volume data of the TV before adjusting the volume.

3. The multi-screen interactive processing system based on a smart TV according to claim 2, characterized in that: The control model creation module includes a historical data training unit and an adjustment control model establishment unit; The historical data training unit is used to combine the control data corresponding to each user and the initial volume data of the TV before adjusting the volume, and perform fitting training on the combined data; The adjustment control model building unit is used to build a volume adjustment control model for each user on the smart TV according to the fitted training data, and the volume adjustment control model includes a volume increase control model and a volume decrease control model.

4. The multi-screen interactive processing system based on a smart TV according to claim 3, characterized in that: The multi-screen interactive data monitoring module includes a voice data receiving unit, an identity and command recognition unit, and a monitoring data output unit; The voice data receiving unit is used to receive a voice instruction on volume adjustment output by the current user; The identity and command recognition unit is used to recognize the received voice command: match the voice command with the voice command in the voice database for voice signal features, confirm the user corresponding to the voice command, and obtain the level of the corresponding user controlling the smart TV; The monitoring data output unit is used to monitor the initial volume data of the current TV.

5. The multi-screen interactive processing system based on a smart TV according to claim 4, characterized in that: The multi-screen interactive dynamic processing module includes a first planning mode generating unit, a second planning mode generating unit and an adaptive adjustment unit; The first planning mode generating unit is used to generate a first planning mode for volume adjustment when the number of users who currently output voice commands is 1: if the voice command output by the user is to increase the volume, the initial volume of the current TV is input into the volume increase control model corresponding to the current user, and the current optimal volume increase value is output; if the voice command output by the user is to reduce the volume, the initial volume of the current TV is input into the volume reduction control model corresponding to the current user, and the current optimal volume reduction value is output; The second planning mode generating unit is used to generate a second planning mode for volume adjustment when the number of users currently outputting voice commands is greater than 1 and all users output the same voice command: if the voice command output by the user is to increase the volume, the initial volume of the current TV is input into the volume increase control model corresponding to all users, and the current optimal increase volume value is set according to the volume value output by each model; if the voice command output by the user is to reduce the volume, the initial volume of the current TV is input into the volume reduction control model corresponding to all users, and the current optimal decrease volume value is set according to the volume value output by each model; The adaptive adjustment unit is used to adjust the volume of the smart TV according to the first planning method when the number of users currently outputting voice commands is 1; when the number of users currently outputting voice commands is greater than 1 and all users output the same voice commands, adjust the volume of the smart TV according to the second planning method.

6. A multi-screen interactive processing method based on a smart TV, characterized in that: The following steps are involved: S1: Collect the voice data output by the user during the previous multi-screen interaction and the historical volume control data of the smart TV; S2: Establish a volume adjustment control model for each user who has controlled the same smart TV; S3: When the current user performs multi-screen interaction with the smart TV, monitoring the voice data output by the current user and the parameter data of the current TV; S4: Generate adjustment planning methods for smart TVs in different multi-screen interactive scenarios based on the volume adjustment control model, and adjust parameters of the smart TVs based on the planning methods.

7. A multi-screen interactive processing method based on a smart TV according to claim 6, characterized in that: In step S1: the voices of users who have previously controlled the smart TV by voice during multi-screen interaction are collected, the collected voice data of each user is stored and a voice database is generated, the levels of all users controlling the smart TV are set to {1, 2, ... N}, N represents the number of users who have controlled the smart TV by voice, when the TV recognizes the voices of more than one user, the voice command of the user with the highest level is executed first, the voice commands received by the smart TV when different users have previously controlled the volume of the smart TV by voice are collected, control data is extracted from the voice commands, the control data includes increased volume data and decreased volume data, and the initial volume data of the TV before adjusting the volume is collected.

8. The multi-screen interactive processing method based on a smart TV according to claim 7, characterized in that: In step S2: retrieve a random volume set {G1, G2, ... G m }, the initial volume set of the TV before the volume is increased is {g1,g2,...g m }, m represents the number of times a random user has increased the volume of the TV in the past, and the corresponding volume set of each time the user has controlled the TV to decrease is {H1,H2,...H n }, the initial volume set of the TV before the volume is lowered is {h1,h2,...h n }, n represents the number of times a random user has lowered the volume of the TV in the past, and the retrieved data is combined to obtain the first training data {(g1, G1), (g2, G2), ... (g m ,G m )}, and obtain the second training data {(h1,H1), (h2,H2), ... (h n ,H n )}, a volume increase control model for a random user is established after a straight line fitting is performed on the first training data: y = θ1*x + θ2, θ1 and θ2 represent the fitting coefficients of the volume increase control model, x represents the independent variable representing the initial volume before the increase in the volume increase control model, and y represents the dependent variable representing the increased volume in the volume increase control model, and a volume reduction control model for a random user is established after a straight line fitting is performed on the second training data: Y = α1*X + α2, α1 and α2 represent the fitting coefficients of the volume reduction control model, X represents the independent variable representing the initial volume before the decrease in the volume decrease control model, and Y represents the dependent variable representing the decreased volume in the volume decrease control model, and the volume increase control model and the volume reduction control model are established for all users in the same way.

9. A multi-screen interactive processing method based on a smart TV according to claim 8, characterized in that: In step S3: receiving the voice command about volume adjustment output by the current user, identifying the received voice command, confirming the user corresponding to the voice command, obtaining the level of control of the smart TV by the corresponding user, and monitoring that the initial volume of the current TV is L.

10. A multi-screen interactive processing method based on a smart TV according to claim 9, characterized in that: In step S4: if the number of users who currently output voice instructions about volume adjustment is 1, a first planning method for volume adjustment is generated: if the voice instruction output by the current user is to increase the volume, the volume increase control model corresponding to the current user is extracted as: y1=a*x1+b, a and b represent the fitting coefficients of the volume increase control model corresponding to the current user, let x1=L, output the current optimal volume increase value as a*L+b, and control the volume of the smart TV to be increased to L+(a*L+b); if the voice instruction output by the current user is to reduce the volume, the volume reduction control model corresponding to the current user is extracted as: Y1=c*X1+d, c and d represent the fitting coefficients of the volume reduction control model corresponding to the current user, let X1=L, output the current optimal volume reduction value as c*L+d, and control the volume of the smart TV to be reduced to L-(c*L+d); If the number of users who currently output voice commands for volume adjustment is greater than 1 and all users output the same voice command, a second planning method for volume adjustment is generated: the number of users who output the same voice command for volume adjustment is obtained as k, k>1, if the voice command output by the user is to increase the volume, L is input into the volume increase control model corresponding to all users, and the volume increase value set output by the model is obtained as {A1, A2, ... A k }, the level set of k users retrieved is {P1,P2,...P k }, set the current optimal volume increase value to F, F = ∑ k i＝1 [(P i / ∑ k i＝1 (P i ))*A i ], i represents the i-th user among k users, controlling the volume of the smart TV to increase to L+F; If the voice command output by the user is to reduce the volume, L is input into the volume reduction control model corresponding to all users, and the volume reduction value set output by the model is {B1, B2, ... B k }, set the current optimal volume increase value to f, f = ∑ k i＝1 [(P i / ∑ k i＝1 (P i ))*B i ] to control the volume of the smart TV to be lowered to Lf.

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