Pedal-based timbre mode adjustment control method for intelligent guitar

Abstract

The invention relates to the technical field of guitar control, in particular to a pedal-based timbre mode adjustment control method for an intelligent guitar, and the method comprises the steps: receiving a pedal signal inputted by a user, converting the pedal signal into a pedal digital signal, and transmitting the pedal digital signal to a central processing unit through an internal communication module, the central processing unit calls a preset mapping relation; the digital signal is analyzed based on the mapping relation to determine a corresponding target timbre mode, the central processing unit sends a control instruction to the audio processing module, and the audio processing module adjusts the current timbre mode to the target timbre mode based on the audio processing module; and in the process of generating the control instruction, calling playing data and historical operation records of the user, generating tone switching logic corresponding to the user based on the playing data and the historical operation records, and generating a control instruction for controlling tone switching by the user based on the tone switching logic. According to the invention, the accuracy of timbre mode adjustment control of the intelligent guitar can be improved.

Description

Technical Field

[0001] This application relates to the technical field of guitar control, and in particular to a method for adjusting and controlling tone modes of an intelligent guitar based on a pedal. Background Art

[0002] With the development of electronic music, more and more music producers and performers tend to use electronic musical instruments for creation and performance. Although traditional electric guitars can change sounds by connecting external effectors, this approach often requires manual operation, which not only limits the flexibility of the performer but also affects the expressiveness of live performances; in recent years, some high-end electronic musical instruments have begun to introduce a pedal-based control mechanism to achieve rapid switching of tones and other parameters, thereby liberating the hands of the performer and enabling them to focus more on the performance itself.

[0003] However, the existing pedal-based control methods usually have the following deficiencies: one is slow response speed, which cannot meet the needs of professional performances; the other is single function, limited to basic tone switching, lacking deeper customization options; and the third is that the user interface is not friendly enough, making it difficult to perform quick settings and adjustments.

[0004] As can be seen from the above, how to improve the accuracy of tone mode adjustment and control of intelligent guitars still remains to be solved. Summary of the Invention

[0005] In order to improve the accuracy of tone mode adjustment and control of intelligent guitars, this application provides a method for adjusting and controlling tone modes of an intelligent guitar based on a pedal.

[0006] In a first aspect, this application provides a method for adjusting and controlling tone modes of an intelligent guitar based on a pedal, adopting the following technical solution: A method for adjusting and controlling tone modes of an intelligent guitar based on a pedal includes: receiving a foot signal input by a user through an intelligent pedal installed on the guitar, converting the foot signal into a foot digital signal, and sending it to a central processing unit through an internal communication module. The central processing unit retrieves a preset mapping relationship, where the mapping relationship includes the correspondence between foot position, force, and duration and tone modes; parsing the digital signal based on the mapping relationship to determine the corresponding target tone mode, and the central processing unit sending a control instruction to an audio processing module. The audio processing module adjusts the current tone mode to the target tone mode based on the audio processing module; during the process of generating the control instruction, retrieving the user's performance data and historical operation records, generating a tone switching logic corresponding to the user based on the performance data and historical operation records, and generating a control instruction for the user to control tone switching based on the tone switching logic.

[0007] By adopting the above technical solution, by collecting and analyzing the user's foot pedal signals in real time, and combining the user's historical performance data and operation records, a personalized tone switching logic is dynamically generated, thereby significantly improving the accuracy and response speed of tone mode adjustment, enabling the user to switch tones more naturally and smoothly, and enhancing the performance experience.

[0008] Optionally, the method further includes: obtaining the corresponding foot pedal action frequency and duration based on the intelligent pedal installed on the guitar, and determining the corresponding performance speed based on the foot pedal action frequency and duration; obtaining the corresponding performance intensity based on the multi-level pressure sensor of the intelligent pedal; when the performance speed is high and the performance intensity is high, the central processing unit reduces the minimum force or time interval required to trigger tone switching.

[0009] By adopting the above technical solution, by the intelligent pedal, the user's foot pedal action frequency, duration and performance intensity are monitored in real time, and the trigger threshold of tone switching is dynamically adjusted, so that when performing at high speed and high intensity, the system can respond to the user's operation faster, thereby improving the sensitivity and accuracy of tone mode switching, and enhancing the fluency and expressiveness of performance.

[0010] Optionally, the method further includes: obtaining the corresponding performance data based on the foot pedal digital signal, where the performance data includes foot pedal actions, force, duration, used tone mode, and performance style; retrieving the performance habits, preference data, and common tone modes of the target user; generating a tone recommendation list based on the performance habits, preference data, common tone modes, and the performance data.

[0011] By adopting the above technical solution, by analyzing the user's foot pedal digital signal to obtain detailed performance data, and combining the user's historical performance habits, preferences, and common tone modes, a personalized tone recommendation list is generated, thereby providing the user with tone selections that are more in line with their style and needs, and enhancing the diversity and creativity of performance.

[0012] Optionally, the method further includes: obtaining the performance audio signal of the target user, identifying the audio features of the performance audio signal, and determining the corresponding track type based on the audio features, where the audio features include rhythm, melody, harmonic structure, and pitch distribution; determining the corresponding typical tone requirements based on the track type; retrieving the tone recommendation list, and optimizing the tone recommendation list based on the typical tone requirements.

[0013] By adopting the above technical solution, by analyzing the user's performance audio signal, identifying the audio features of the track and determining its type, and then optimizing the tone recommendation list according to the typical tone requirements of the track, thereby providing the user with tone suggestions that are more in line with the current performance style and track type, and enhancing the accuracy and applicability of tone selection.

[0014] Optionally, the method further includes: when it is detected that the user steps on multiple pedals simultaneously, identifying the corresponding pedal combination mode; retrieving a pre-set combination mapping table, and determining a corresponding complex timbre setting based on the pedal combination mode and the combination mapping table; and sending an instruction to the audio processing module based on the preset timbre setting to instruct the audio processing module to switch to the corresponding timbre.

[0015] By adopting the above technical solution, by identifying the combination mode of the user stepping on multiple pedals simultaneously, retrieving the pre-set combination mapping table to determine the corresponding complex timbre setting, and sending an instruction to the audio processing module to achieve timbre switching, it allows the user to trigger complex timbre effects through simple pedal combination operations, improving the flexibility and expressiveness of performance.

[0016] Optionally, the method further includes: collecting evaluation data of past users on the timbre recommendation list; judging whether it is necessary to modify the mapping relationship based on the evaluation data; if so, determining the corresponding modifying user, retrieving the modification opinions in the evaluation data corresponding to the modifying user, and generating a mapping relationship for the modifying user based on the modification opinions.

[0017] By adopting the above technical solution, by collecting the evaluation data of users on the timbre recommendation list, judging whether it is necessary to adjust the mapping relationship according to these feedbacks, and generating a personalized mapping relationship based on the modification opinions of users when necessary, it continuously optimizes the accuracy of timbre recommendation and user satisfaction.

[0018] In a second aspect, the present application provides a method for adjusting and controlling the timbre mode of an intelligent guitar based on pedals, adopting the following technical solution: An apparatus for adjusting and controlling the timbre mode of an intelligent guitar based on pedals includes: A foot pedal signal receiving module, which is installed on the intelligent pedal of the guitar and is used to receive the foot pedal signal input by the user, convert the foot pedal signal into a foot pedal digital signal, and send it to the central processing unit through an internal communication module. The central processing unit retrieves a pre-set mapping relationship, where the mapping relationship includes the correspondence between the foot pedal position, force, and duration and the timbre mode; A target timbre mode adjustment module, which analyzes the digital signal based on the mapping relationship to determine the corresponding target timbre mode. The central processing unit sends a control instruction to the audio processing module, and the audio processing module is used to adjust the current timbre mode to the target timbre mode A timbre switching logic generation module, which retrieves the user's performance data and historical operation records during the process of generating the control instruction, generates a timbre switching logic corresponding to the user based on the performance data and historical operation records, and generates a control instruction for the user to control timbre switching based on the timbre switching logic.

[0019] In a third aspect, the present application provides a method for adjusting and controlling the tone mode of an intelligent guitar based on a pedal, adopting the following technical solution: A method for adjusting and controlling the tone mode of an intelligent guitar based on a pedal includes a processor, and a program of the method for adjusting and controlling the tone mode of the intelligent guitar based on a pedal as described in any one of the above is run in the processor.

[0020] In a fourth aspect, the present application provides a storage medium, adopting the following technical solution: A storage medium stores a program of the method for adjusting and controlling the tone mode of the intelligent guitar based on a pedal as described in any one of the above.

[0021] In summary, the present application includes at least one of the following beneficial technical effects: 1. By collecting and analyzing the user's foot pedal signals in real time, and combining the user's historical performance data and operation records, a personalized tone switching logic is dynamically generated, thereby significantly improving the accuracy and response speed of tone mode adjustment. The system can also dynamically adjust the trigger threshold of tone switching according to the user's playing speed and intensity, ensuring that it can respond to the user's operations faster during high-speed and high-intensity playing, and further enhancing the sensitivity and accuracy of tone switching.

[0022] 2. In addition, by analyzing the user's performance audio signal, identifying the audio characteristics of the track and determining its type, and then optimizing the tone recommendation list to provide tone suggestions that more conform to the current playing style and track type. At the same time, by identifying the combination method of the user stepping on multiple pedals simultaneously, a preset combination mapping table is retrieved to achieve complex tone settings, enhancing the flexibility and expressiveness of playing. Collecting the evaluation data of the user on the tone recommendation list, and continuously adjusting and optimizing the mapping relationship based on these feedbacks to ensure the accuracy of tone recommendation and user satisfaction, thereby comprehensively enhancing the tone mode adjustment and control experience of the intelligent guitar. Description of the Drawings

[0023] Figure 1 is a flowchart of a method for adjusting and controlling the tone mode of an intelligent guitar based on a pedal shown according to an exemplary embodiment.

[0024] Figure 2 is a structural block diagram of a device for adjusting and controlling the tone mode of an intelligent guitar based on a pedal shown according to an exemplary embodiment. Detailed Embodiments

[0025] The following details the embodiments of the present application, and the examples of the embodiments are shown in the drawings.

[0026] In the description of this specification, the description referring to terms such as "certain embodiments", "one embodiment", "some embodiments", "schematic embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiments or examples are included in at least one embodiment or example of the present application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0027] An embodiment of the present application discloses a method for adjusting and controlling the tone mode of an intelligent guitar based on a pedal. Referring to Figure 1 , it includes: S100, receiving a foot pedal signal input by a user through an intelligent pedal installed on the guitar, converting the foot pedal signal into a foot pedal digital signal, and sending it to a central processing unit through an internal communication module. The central processing unit retrieves a preset mapping relationship.

[0028] Among them, the intelligent pedal is installed on the guitar and has multi-level pressure sensing and multi-axis motion sensing functions. These sensors can capture the three-dimensional motion trajectory of the user's foot and the foot pedal actions with different forces. When the user steps on the pedal, the sensors on the pedal will collect the user's foot pedal signal in real time, including information such as the position, force, and duration of the foot pedal.

[0029] Then, the analog-to-digital converter (ADC) built into the intelligent pedal converts the analog signal into a digital signal, and the converted digital signal is sent to the central processing unit through an internal communication module (such as a high-speed serial bus or a wireless communication module). The communication module ensures the real-time performance and reliability of the signal.

[0030] In addition, a preset mapping relationship table is stored in the central processing unit. The mapping relationship table defines the corresponding relationship between the foot pedal position, force, and duration and the tone mode; for example, a specific foot pedal position and force may correspond to a certain tone mode (such as clean, distortion, reverb, etc.). The central processing unit retrieves the corresponding mapping relationship according to the received foot pedal digital signal to determine the target tone mode that the user intends to switch to.

[0031] S110, parsing the digital signal based on the mapping relationship to determine the corresponding target tone mode, the central processing unit sends a control instruction to the audio processing module, and the audio processing module adjusts the current tone mode to the target tone mode based on the audio processing module.

[0032] Among them, the central processing unit receives the pedal digital signal transmitted from the intelligent pedal, extracts key features from the pedal digital signal, and the key features include the position, strength, and duration of the pedal press. Match the extracted key features with a preset mapping relation table. For example, if the user presses the pedal at a certain specific position and applies a certain strength, the system will look up the mapping table to find the tone color mode corresponding to this position and strength; through the matching process, determine the target tone color mode that the user hopes to switch to. For example, if the pedal position and strength pressed by the user correspond to the "distortion" tone color mode, the system will determine the target tone color mode as "distortion".

[0033] In addition, the central processing unit generates corresponding control instructions according to the determined target tone color mode. These instructions contain specific parameters that need to be adjusted, such as tone color type, effects processor settings, etc. The control instructions usually adopt the standard communication protocol format to ensure that the audio processing module can correctly parse and execute them. The control instructions are sent to the audio processing module through an internal communication module (such as a high-speed serial bus or a wireless communication module). To ensure that the instructions are correctly received, the system may use some mechanisms to confirm the transmission status of the instructions, such as response signals or error detection codes.

[0034] The audio processing module receives the control instructions sent by the central processing unit, parses the control instructions, extracts the specific tone color mode and related parameters, and then performs corresponding tone color adjustments. The specific process is as follows: The audio processing module adjusts the parameters of the current tone color mode according to the parsed instructions. For example, if the target tone color mode is "distortion", the audio processing module will adjust the relevant distortion effects processor parameters; the audio processing module processes the input audio signal in real time and applies the new tone color mode, which may include operations such as filtering, gain adjustment, and effects processor application on the audio signal; to ensure the smoothness of the tone color switch, the audio processing module may adopt a progressive transition technology. For example, when switching from one tone color mode to another, the system will gradually adjust the parameters to make the tone color change more natural.

[0035] By accurately parsing user input, generating and transmitting control instructions in real time, and efficiently adjusting the tone color mode, the accuracy and response speed of the intelligent guitar tone color mode adjustment and control are significantly improved, enabling users to switch tone colors more naturally and smoothly, and enhancing the overall performance and creativity of playing.

[0036] S120, during the process of generating control instructions, retrieve the user's performance data and historical operation records, generate the tone color switching logic corresponding to the user based on the performance data and historical operation records, and generate control instructions for the user to control the tone color switch based on the tone color switching logic.

[0037] Among them, the user's performance data and historical operation records are stored in the system. These data include but are not limited to: Pedal actions: The position, force, and duration of the user stepping on the pedal.

[0038] The tone color mode used: The tone color modes used by the user at different time points.

[0039] Performance style: The user's performance style (such as rock, jazz, classical, etc.).

[0040] Operation records: The switching frequency of the tone color mode by the user, preference settings, etc.

[0041] Then, key features are extracted from the performance data and historical operation records, such as common pedal combinations, frequently used tone color modes, performance styles, etc.; machine learning algorithms (such as clustering analysis, decision trees, neural networks, etc.) are used to identify the user's performance habits and preferences. For example, the system can identify the tone color modes frequently used by the user in specific track types; based on the above analysis results, personalized tone color switching logic is generated. This logic takes into account the user's performance habits, preferences, and historical operation records, making the tone color switching more in line with the user's actual needs. Finally, the system can continuously update and optimize the tone color switching logic according to the user's latest performance data.

[0042] In the process of generating the corresponding control instructions, including from instruction generation to instruction format and then to instruction transmission, specifically including: 1. Instruction generation: According to the generated tone color switching logic, the central processing unit determines the target tone color mode that the user hopes to switch to. For example, if the user often uses the distortion effect in rock tracks, the system will automatically recommend the distortion tone color mode when detecting similar performance characteristics; according to the target tone color mode, specific control instructions are generated. These instructions contain the tone color parameters that need to be adjusted, such as tone color type, effect pedal settings, etc.

[0043] 2. Instruction format: The control instructions usually adopt the standard communication protocol format to ensure that the audio processing module can correctly parse and execute.

[0044] 3. Instruction transmission: The control instructions are sent to the audio processing module through an internal communication module (such as a high-speed serial bus or a wireless communication module). The communication module ensures the real-time and reliability of the instructions; in order to ensure that the instructions are correctly received, the system may use some mechanisms to confirm the transmission status of the instructions, such as acknowledgment signals or error detection codes.

[0045] By retrieving the user's performance data and historical operation records, a personalized tone switching logic is generated, and based on this, control instructions are generated, significantly improving the personalization and intelligence level of the intelligent guitar tone mode adjustment control, enabling the user to switch tones more naturally and smoothly, and enhancing the overall performance and user experience of the performance.

[0046] In the embodiment of the present application, the method further includes: S101, obtaining the corresponding foot pedal action frequency and duration based on the intelligent pedal installed on the guitar, and determining the corresponding performance speed based on the foot pedal action frequency and duration.

[0047] Among them, the intelligent pedal is equipped with multi-axis motion sensors that can capture the three-dimensional motion trajectory of the user's foot. These sensors can monitor the user's foot pedal actions in real time, and the system records the action frequency of each foot pedal (i.e., the number of times stepped on per unit time) and the duration (i.e., the duration of each step).

[0048] By analyzing the number of foot pedal actions within a period of time, the frequency of the foot pedal actions is calculated. For example, if the user steps on the pedal 60 times in one minute, then the foot pedal action frequency is 1 Hertz (Hz); by measuring the time from the start to the end of each foot pedal, the duration of each foot pedal is calculated. For example, if a foot pedal lasts for 0.5 seconds, then the duration is 0.5 seconds.

[0049] In addition, the system determines the user's performance speed based on the calculated foot pedal action frequency and duration. For example, if the foot pedal action frequency is 2 Hertz and the duration is 0.2 seconds, the system may determine that the user's performance speed is high speed.

[0050] In the embodiment of the present application, the speed classification: Low speed: If the foot pedal action frequency is low and the duration is long, the system will determine that the user's performance speed is low speed; Medium speed: If the foot pedal action frequency is moderate and the duration is moderate, the system will determine that the user's performance speed is medium speed; High speed: If the foot pedal action frequency is high and the duration is short, the system will determine that the user's performance speed is high speed.

[0051] S102, obtaining the corresponding performance intensity based on the multi-level pressure sensors of the intelligent pedal.

[0052] Among them, the intelligent pedal is equipped with a multi-level pressure sensor that can capture different forces exerted by the user's foot. These sensors can monitor the user's foot pressure in real time; the system records the pressure value of each footstep, usually in Newtons (N) or kilogram-force (kgf). Then, the system divides the playing intensity into different levels according to the pressure value, such as low intensity, medium intensity, and high intensity. The system determines the user's playing intensity based on the recorded pressure value. For example, if the pressure value is 10 Newtons, the system may determine that the user's playing intensity is medium intensity.

[0053] S103, when the playing speed is high speed and the playing intensity is high intensity, the central processing unit reduces the minimum force or time interval required to trigger tone switching.

[0054] Among them, when the system detects that the user's playing speed is high speed and the playing intensity is high intensity, the central processing unit reduces the minimum force required to trigger tone switching. For example, originally, a force of 5 Newtons was required to trigger tone switching, but now only 3 Newtons is needed; the central processing unit reduces the time interval required to trigger tone switching. For example, originally, a duration of 0.5 seconds was required to trigger tone switching, but now only 0.2 seconds is needed.

[0055] The central processing unit generates corresponding control instructions to instruct the audio processing module to perform tone switching at the new threshold. The control instructions are sent to the audio processing module through the internal communication module to ensure real-time response.

[0056] Based on the above steps, the system can dynamically adjust the threshold for triggering tone switching according to the user's playing speed and intensity, so that when playing at high speed and high intensity, the user can trigger tone switching faster, improving the system's response speed and sensitivity; by reducing the minimum force or time interval required to trigger tone switching, the user can switch tones more naturally and smoothly during fast playing, reducing misoperations and enhancing the overall fluency and expressiveness of playing. By dynamically adjusting the threshold, the system can better adapt to different playing styles and track types, helping the user achieve richer and more diverse tone effects.

[0057] In addition, the method further includes: S111, obtaining corresponding playing data based on the pedal digital signal.

[0058] Among them, the playing data acquisition includes: Pedaling action: The multi-axis motion sensor of the intelligent pedal is used to record the user's pedal position and action in real time; Force: The multi-level pressure sensor is used to record the force when the user steps on the pedal in real time; Duration: The duration of each pedaling action is recorded; Tone color mode used: The tone color mode used by the user at different time points is recorded; Playing style: By analyzing the user's playing data (such as rhythm, melody, harmony structure, etc.), the user's playing style (such as rock, jazz, classical, etc.) is determined.

[0059] Then, the data collected above is integrated to form a complete playing data set. This data may include information such as timestamps, pedal positions, forces, durations, the currently used tone color mode, and playing styles.

[0060] S112, retrieve the playing habits, preference data, and commonly used tone color modes corresponding to the target user.

[0061] Among them, the historical playing data and operation records of each user are stored in the system. This data includes the user's playing habits, preference data (such as favorite tone color modes, commonly used playing styles, etc.), and commonly used tone color modes. The central processing unit retrieves the relevant data of the target user from the database, and this data may include the user's past playing records, preference settings, commonly used tone color modes, etc.

[0062] By analyzing the user's historical playing data, the user's playing habits are identified. For example, the tone color modes often used by the user in specific track types, common pedal combinations, etc.; by analyzing the user's historical operation records, the user's preference data is identified. For example, which type of tone color mode the user prefers, preference settings in different playing styles, etc.; count the tone color modes most frequently used by the user to form a list of commonly used tone color modes.

[0063] S113, generate a tone color recommendation list based on the playing habits, preference data, commonly used tone color modes, and the playing data.

[0064] Among them, the user's playing habits, preference data, commonly used tone color modes are comprehensively analyzed with the current playing data. For example, if the user often uses the distortion effect in rock tracks and the current playing style is rock, the system will give priority to recommending the distortion tone color mode. Machine learning algorithms (such as clustering analysis, decision trees, neural networks, etc.) are used to generate a personalized tone color recommendation list. This list contains multiple recommended tone color modes and is sorted by priority. The system can continuously update and optimize the tone color recommendation list according to the user's latest playing data to ensure that the recommended tones always meet the user's current needs.

[0065] Based on the steps from S111 to S113 above, by collecting and analyzing the user's performance data, historical operation records, and common timbre patterns, the system can generate a personalized timbre recommendation list, making timbre switching more in line with the user's actual needs and preferences; based on the user's performance habits and preferences, the system can intelligently recommend suitable timbre patterns, reducing the cumbersome process of manual adjustment by the user and enhancing the user experience; the system can dynamically adjust the timbre recommendation list by continuously learning and updating the user's latest performance data to ensure that the recommended timbres always meet the user's latest needs.

[0066] For the timbre recommendation list, it is further optimized in the embodiments of this application. Therefore, the method further includes: S114, obtain the performance audio signal of the target user, the audio features recognized from the performance audio signal, and determine the corresponding track type based on the audio features.

[0067] Among them, the system collects the user's performance audio signal in real time through a microphone or pickup installed on the guitar. The collected original audio signal may contain noise and other interferences. Therefore, preprocessing such as noise reduction and filtering is required to improve the signal quality.

[0068] Feature extraction: Rhythm: Extract the rhythm features in the audio signal through beat detection algorithms (such as autocorrelation function, wavelet transform, etc.). This can help the system identify the beats and tempo of the music; Melody: Extract the melody features in the audio signal through pitch detection algorithms (such as fundamental frequency tracking, spectral analysis, etc.); Harmony structure: Extract the harmony structure features in the audio signal through chord recognition algorithms (such as hidden Markov model, convolutional neural network, etc.). This can help the system identify chord progressions and harmony changes; Pitch distribution: Extract the pitch distribution features in the audio signal through spectral analysis (such as Fourier transform). This can help the system identify the pitch range and pitch distribution. Integrate the above-extracted audio features into a comprehensive feature vector.

[0069] The system stores an audio feature template library for different track types. These template libraries contain the typical features of various track types. Classification algorithms (such as support vector machines, random forests, deep learning models, etc.) can be used to match the extracted comprehensive feature vector with the features in the template library to determine the closest track type; the system determines the track type of the current performance based on the matching result, such as rock, jazz, classical, blues, etc.

[0070] S115, determine the corresponding typical timbre requirements based on the track type.

[0071] Among them, the typical timbre requirements of different track types are predefined in the system. For example, rock tracks usually require distortion effects, delay effects, etc.; classical tracks tend to prefer the timbre of acoustic guitars or pianos. According to the determined track type, the system extracts the corresponding timbre configuration from the predefined library of typical timbre requirements.

[0072] S116, retrieve the timbre recommendation list and optimize the timbre recommendation list based on the typical timbre requirements.

[0073] Among them, the system retrieves the generated personalized timbre recommendation list, compares the existing timbre recommendation list with the typical timbre requirements, adjusts the timbre modes in the recommendation list to make them more in line with the typical timbre requirements of the current track; adjusts the priorities of each timbre mode in the recommendation list according to the typical timbre requirements to ensure that the timbre mode that best suits the current track is ranked at the front; if some typical timbre modes are missing from the existing recommendation list, the system will supplement these timbre modes to enrich the recommendation list. Generate a new timbre recommendation list according to the optimization result and provide it to the user.

[0074] Based on the steps from S114 to S116 above, by analyzing the user's performance audio signal in real time, the system can accurately identify the track type of the current performance. Based on the identified track type, the system can determine the corresponding typical timbre requirements and optimize the timbre recommendation list accordingly, making the recommended timbre more in line with the style and characteristics of the current track; through intelligent identification and optimization of the timbre recommendation list, users can quickly find the best timbre settings suitable for the current track, improving the overall expressiveness and creativity of the performance; and the system can dynamically adjust the timbre recommendation list according to the user's real-time performance situation to ensure that the recommended timbre always meets the user's current needs and enhance the adaptive ability of the system.

[0075] The method further includes: S104, when it is detected that the user steps on multiple pedals simultaneously, identify the corresponding pedal combination method.

[0076] Among them, the intelligent pedal is equipped with a multi-level pressure sensor that can capture different forces exerted by the user's foot. Each pedal has an independent pressure sensor, and the pedal is also equipped with a multi-axis motion sensor that can capture the three-dimensional motion trajectory of the user's foot to ensure accurate identification of the user's operation intention; the central processing unit monitors the status of each pedal in real time through the built-in algorithm, including whether each pedal is stepped on, the force and duration of stepping on.

[0077] When it is detected that the user steps on multiple pedals simultaneously, the system will identify the specific pedal combination method. For example, the user may step on pedals A and B simultaneously, or step on pedal C first and then pedal D; the system analyzes the states of each pedal (such as the order and intensity of stepping on), and confirms the specific pedal combination method. This step ensures the accuracy and reliability of the system.

[0078] S105, retrieve the pre-set combination mapping table, and determine the corresponding complex tone settings based on the pedal combination method and the combination mapping table.

[0079] Among them, a combination mapping table is pre-stored in the system. This table defines the relationship between different pedal combination methods and the corresponding complex tone settings. For example, the combination of pedals A and B may correspond to the "rock mode", while the combination of pedals C and D may correspond to the "jazz mode". The mapping table is usually a database or a configuration file, which contains multiple entries, and each entry describes a specific pedal combination and its corresponding tone settings.

[0080] The central processing unit looks up the corresponding entry in the combination mapping table according to the identified pedal combination method. For example, if the user steps on pedals A and B simultaneously, the system will find the matching entry in the mapping table; once the matching entry is found, the system will read the complex tone settings defined in this entry. These settings may include the combination of multiple effectors (such as distortion, delay, reverb, etc.) and specific parameter settings.

[0081] S106, send an instruction to the audio processing module based on the preset tone settings to instruct the audio processing module to switch to the corresponding tone.

[0082] Among them, the central processing unit generates corresponding control instructions according to the determined complex tone settings. These instructions contain the specific parameters that need to be adjusted, such as tone type, effector settings, etc.; the control instructions usually adopt the standard communication protocol format to ensure that the audio processing module can correctly parse and execute.

[0083] The control instructions are sent to the audio processing module through an internal communication module (such as a high-speed serial bus or a wireless communication module). In order to ensure that the instructions are correctly received, the system may use some mechanisms to confirm the transmission status of the instructions, such as response signals or error detection codes.

[0084] Among them, the audio processing module receives the control instructions sent by the central processing unit, the audio processing module parses the control instructions, extracts the specific tone mode and related parameters, and the audio processing module adjusts the parameters of the current tone mode in real time according to the parsed instructions. This may include operations such as filtering the audio signal, gain adjustment, and effector application.

[0085] To ensure the smoothness of timbre switching, the audio processing module may adopt progressive transition technology. For example, when switching from one timbre mode to another, the system gradually adjusts the parameters to make the timbre change more natural.

[0086] Based on the execution steps from S104 to S106 above, the system can identify the combination ways of the user stepping on multiple pedals simultaneously, realize the switching of complex timbre settings, and improve the flexibility and functionality of the system; through the preset combination mapping table, the system can quickly determine and apply the corresponding complex timbre settings, enabling the user to trigger complex timbre effects through simple pedal combination operations; the system can monitor the user's operations in real time and immediately generate and send control commands after detecting the pedal combination to ensure a quick response for timbre switching; through the progressive transition technology, the system can achieve smooth transition during timbre switching, avoid abrupt changes, and improve the overall fluency and expressiveness of the performance.

[0087] The method further includes: S121, collecting evaluation data of past users for the timbre recommendation list.

[0088] Among them, the system collects users' feedback through various ways, including but not limited to evaluation buttons in the user interface (UI), feedback forms in mobile applications, online questionnaires, etc.; users' feedback may include the overall satisfaction with the timbre recommendation list, the applicability of specific timbre modes, specific timbre settings recommended for improvement, etc.; the collected feedback data is stored in the system's database, and each feedback entry usually contains information such as user ID, feedback time, and feedback content.

[0089] It is also necessary to clean the collected feedback data, remove invalid or irrelevant feedback, and classify the feedback data by type, such as overall satisfaction, feedback on specific timbre modes, specific timbre settings recommended for improvement, etc.

[0090] S122, judging whether it is necessary to modify the mapping relationship based on the evaluation data.

[0091] Among them, statistical analysis is performed on the collected feedback data to calculate the frequencies and trends of different feedback types. For example, if multiple users feedback that a specific timbre mode is not suitable for a certain track type, this may indicate that the mapping relationship of this timbre mode needs to be adjusted. The system sets a threshold, and when a certain type of feedback reaches a certain quantity or proportion, the modification process of the mapping relationship is triggered. For example, if more than 50% of the users feedback that a certain timbre mode is inappropriate, the system will consider that modification is needed.

[0092] Based on the statistical analysis results, the system evaluates whether it is necessary to modify the existing mapping relationships. If modification is indeed required, the system proceeds to the next step. It should be noted that the system may inform the administrator or relevant team through internal notifications or emails that the mapping relationships need to be modified.

[0093] S123, if necessary, determine the corresponding modifying user, then retrieve the modification opinions in the evaluation data corresponding to the modifying user, and generate mapping relationships for the modifying user based on the said modification opinions.

[0094] Among them, users who put forward modification opinions are screened out from the feedback data. These users are usually those who provide specific modification suggestions. The system confirms the unique identifiers of these users (such as user IDs) for subsequent retrieval of their specific feedback data. The system retrieves the feedback data of these users from the database, especially the specific modification opinions they provided.

[0095] In addition, the system parses the retrieved modification opinions in detail to understand the specific needs and suggestions of the users. For example, a user may suggest moving a certain tone color mode from the "rock" category to the "jazz" category; and the system evaluates the feasibility and rationality of these modification opinions to ensure that the modified mapping relationships still conform to the overall design logic.

[0096] According to the users' modification opinions, the system generates new mapping relationships. For example, if a user suggests moving a certain tone color mode from the "rock" category to the "jazz" category, the system will make corresponding adjustments in the mapping table; at the same time, the system tests and validates the newly generated mapping relationships to ensure that they can work correctly and meet the users' needs.

[0097] Finally, update the new mapping relationships to the system's database to replace the original mapping relationships. In addition, the system notifies users through the user interface or mobile application, informing them that the mapping relationships have been updated, and inviting them to experience and give feedback again.

[0098] Based on the execution processes of the above S121 and S123, by collecting users' feedback data, understanding the actual usage situations and improvement suggestions of users for the tone color recommendation list, the accuracy and applicability of tone color recommendation can be continuously optimized; based on the specific modification opinions of users, the system can generate personalized mapping relationships, making the tone color recommendation more in line with the actual needs and preferences of users; by regularly collecting and analyzing users' feedback, the system can continuously improve the tone color recommendation list, enhancing the intelligent level and user experience of the system; through users' feedback and continuous optimization, the system can gradually reduce incorrect and inappropriate tone color recommendations, improving the reliability and stability of the system.

[0099] An embodiment of the present application discloses a pedal-based timbre mode adjustment and control device for an intelligent guitar. Refer to Figure 2 , the device includes but is not limited to: A foot pedal signal receiving module 200, which is installed on the intelligent pedal of the guitar and is used to receive the foot pedal signal input by the user, convert the foot pedal signal into a foot pedal digital signal, and send it to the central processing unit through the internal communication module. The central processing unit retrieves the preset mapping relationship, where the mapping relationship includes the correspondence between the foot pedal position, strength, and duration and the timbre mode; A target timbre mode adjustment module 210, which analyzes the digital signal based on the mapping relationship to determine the corresponding target timbre mode. The central processing unit sends a control instruction to the audio processing module, and the audio processing module is used to adjust the current timbre mode to the target timbre mode A timbre switching logic generation module 220, which retrieves the user's performance data and historical operation records during the process of generating the control instruction, generates the corresponding timbre switching logic for the user based on the performance data and historical operation records, and generates the control instruction for the user to control the timbre switching based on the timbre switching logic.

[0100] Further, the device includes but is not limited to: A performance speed determination module, which obtains the corresponding foot pedal action frequency and duration based on the intelligent pedal installed on the guitar, and determines the corresponding performance speed based on the foot pedal action frequency and duration; A performance intensity acquisition module, which is based on the multi-level pressure sensor of the intelligent pedal to obtain the corresponding performance intensity; When the performance speed is high and the performance intensity is high, the central processing unit reduces the minimum strength or time interval required to trigger the timbre switching.

[0101] Further, the device includes but is not limited to: A performance data acquisition module, which obtains the corresponding performance data based on the foot pedal digital signal, where the performance data includes foot pedal actions, strength, duration, used timbre mode, and performance style; A performance habit retrieval module, which is used to retrieve the performance habits, preference data, and commonly used timbre modes of the target user; A timbre recommendation list generation module, which generates a timbre recommendation list based on the performance habits, preference data, commonly used timbre modes, and the performance data.

[0102] Further, the device includes but is not limited to: A track type determination module, which acquires the performance audio signal of a target user and the audio features recognized from the performance audio signal, and is used to determine the corresponding track type based on the audio features, where the audio features include rhythm, melody, harmony structure, and pitch distribution; A typical timbre requirement determination module, which is used to determine the corresponding typical timbre requirement based on the track type; A timbre recommendation list optimization module, which retrieves the timbre recommendation list and optimizes the timbre recommendation list based on the typical timbre requirement.

[0103] Furthermore, the device includes but is not limited to: A pedal combination mode recognition module, which is used to recognize the corresponding pedal combination mode when it detects that the user steps on multiple pedals simultaneously; A complex timbre setting determination module, which retrieves a pre-set combination mapping table and determines the corresponding complex timbre setting based on the pedal combination mode and the combination mapping table; Send an instruction to the audio processing module based on the preset timbre setting to instruct the audio processing module to switch to the corresponding timbre.

[0104] Furthermore, the device includes but is not limited to: An evaluation data collection module, which is used to collect the evaluation data of past users for the timbre recommendation list; A judgment module, which is used to judge whether it is necessary to modify the mapping relationship based on the evaluation data; A modification opinion retrieval module, if necessary, determines the corresponding modifying user, and is used to retrieve the modification opinion in the evaluation data corresponding to the modifying user, and generate a mapping relationship for the modifying user based on the modification opinion.

[0105] An embodiment of the present application also discloses a method for adjusting and controlling the timbre mode of an intelligent guitar based on a pedal, including a processor, and a program of the method for adjusting and controlling the timbre mode of the intelligent guitar based on a pedal as described in any one of the above is run in the processor.

[0106] An embodiment of the present application also discloses a storage medium, which stores a program of the method for adjusting and controlling the timbre mode of the intelligent guitar based on a pedal as described in any one of the above.

[0107] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A pedal-based tone mode adjustment control method for an intelligent guitar, characterized in that: include: The intelligent pedal installed on the guitar receives a foot pedal signal input by the user, converts the foot pedal signal into a foot pedal digital signal, and sends the signal to the central processing unit through an internal communication module, and the central processing unit retrieves a preset mapping relationship, wherein the mapping relationship includes a corresponding relationship between a foot pedal position, a force and a duration and a timbre mode; The digital signal is parsed based on the mapping relationship to determine the corresponding target timbre mode, the central processing unit sends a control instruction to the audio processing module, and the audio processing module adjusts the current timbre mode to the target timbre mode based on the audio processing module; In the process of generating control instructions, the user's performance data and historical operation records are retrieved, the timbre switching logic corresponding to the user is generated based on the performance data and historical operation records, and the control instructions for the user to control the timbre switching are generated based on the timbre switching logic.

2. The pedal-based tone mode adjustment control method of an intelligent guitar according to claim 1, characterized in that: The method also includes: Acquire a corresponding pedaling action frequency and duration based on an intelligent pedal installed on the guitar, and determine a corresponding playing speed based on the pedaling action frequency and duration; The multi-level pressure sensor based on the smart pedal obtains the corresponding playing intensity; If the playing speed is high and the playing intensity is high, the central processing unit reduces the minimum force or time interval required to trigger the tone switching.

3. The pedal-based tone mode adjustment control method of an intelligent guitar according to claim 1, characterized in that: The method also includes: Acquiring corresponding performance data based on the pedal digital signal, wherein the performance data includes pedal action, strength, duration, used timbre mode and performance style; Retrieve the target user's corresponding playing habits, preference data and common timbre modes; A timbre recommendation list is generated based on playing habits, preference data, common timbre patterns and the playing data.

4. The pedal-based tone mode adjustment control method of the intelligent guitar according to claim 3, characterized in that: The method also includes: Acquire a target user's performance audio signal, identify audio features of the performance audio signal, and determine the corresponding music type based on the audio features, wherein the audio features include rhythm, melody, harmonic structure, and pitch distribution; Determining corresponding typical timbre requirements based on the music genre; The timbre recommendation list is retrieved, and the timbre recommendation list is optimized based on the typical timbre requirement.

5. The pedal-based tone mode adjustment control method of the smart guitar according to claim 1, characterized in that: The method also includes: When it is detected that the user presses multiple pedals at the same time, the corresponding pedal combination is identified; Retrieving a preset combination mapping table, and determining a corresponding complex timbre setting based on the pedal combination mode and the combination mapping table; Based on the preset timbre setting, an instruction is sent to the audio processing module to instruct the audio processing module to switch to a corresponding timbre.

6. The pedal-based tone mode adjustment control method of the smart guitar according to claim 3, characterized in that: The method also includes: Collecting past user evaluation data on the tone recommendation list; Determining whether the mapping relationship needs to be modified based on the evaluation data; If necessary, the corresponding modification user is determined, and the modification opinions in the evaluation data corresponding to the modification user are retrieved, and a mapping relationship for the modification user is generated based on the modification opinions.

7. A pedal-based tone mode adjustment control device for an intelligent guitar, characterized in that: include: A foot signal receiving module, which is installed on the smart pedal of the guitar to receive the foot signal input by the user, convert the foot signal into a foot digital signal, and send it to the central processing unit through the internal communication module, and the central processing unit retrieves a preset mapping relationship, wherein the mapping relationship includes a corresponding relationship between the foot position, force and duration and the timbre mode; The target timbre mode adjustment module analyzes the digital signal based on the mapping relationship to determine the corresponding target timbre mode, and the central processing unit sends a control instruction to the audio processing module, and the audio processing module is used to adjust the current timbre mode to the target timbre mode based on the audio processing module. The timbre switching logic generation module retrieves the user's performance data and historical operation records during the process of generating control instructions, generates the timbre switching logic corresponding to the user based on the performance data and historical operation records, and generates control instructions for the user to control the timbre switching based on the timbre switching logic.

8. The pedal-based tone mode adjustment control device for an intelligent guitar according to claim 7, characterized in that: The device also includes: A playing speed determination module, which obtains a corresponding foot-operating frequency and duration based on an intelligent pedal installed on the guitar, and determines a corresponding playing speed based on the foot-operating frequency and duration; The performance intensity acquisition module uses a multi-level pressure sensor based on the intelligent pedal to obtain the corresponding performance intensity; If the playing speed is high and the playing intensity is high, the central processing unit reduces the minimum force or time interval required to trigger the tone switching.

9. A pedal-based tone mode adjustment control method for an intelligent guitar, characterized in that: It comprises a processor, in which runs a program of the pedal-based tone mode adjustment control method of the smart guitar as described in any one of claims 1-6.

10. A storage medium, characterized in that: A program for the pedal-based tone mode adjustment control method of an intelligent guitar as described in any one of claims 1 to 6 is stored.

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