Devices, methods, and systems for audio applications

Abstract

A device and method for audio applications. The device includes a memory and a processor configured to receive a first audio signal, receive metadata associated with the first audio signal, create a first profile associated with the first audio signal, the first profile including a plurality of adjustable audio parameters, and process the first audio signal using the plurality of adjustable audio parameters of the first profile. The processor is configured to send the first audio signal processed using the first profile to one or more playback devices; receive one or more first user inputs from one or more sensors, analyze the one or more first user inputs, and adjust one or more of the plurality of audio parameters of the first profile based on the analysis, the metadata, or a combination of the analysis and the metadata; process the first audio signal using the adjusted first profile, and send the first audio signal processed using the adjusted first profile to one or more sound channels.

Description

Technical Field

[0001] This invention relates to methods, apparatus, and systems for audio applications. More specifically, the invention relates to a method for adjusting multiple audio parameters of an audio signal, and an apparatus including a processor configured to adjust the multiple audio parameters of the audio signal. Background Technology

[0002] Traditional sound systems known in industry include one or more channels (e.g., to support mono, stereo, surround sound, etc.), each of which is coupled to one or more speakers. Such sound systems are coupled to a music source (e.g., a radio, a physical medium (e.g., memory, CD, vinyl record, cassette tape, etc.) player, a network, or a similar device) and can play music through one or more channels.

[0003] Such sound systems are used in a variety of different configurations. Known sound systems can be used in enclosed rooms such as living spaces or vehicles (i.e., cars, ships, airplanes, or similar vehicles). Alternative known sound systems can be portable (and therefore not limited to a specific room), such as portable speakers / audio systems, headphones, earphones, or similar devices.

[0004] To enhance the user experience and take advantage of different types of sound systems, different channels, and / or speaker characteristics, some sound systems include user-adjustable sound settings (e.g., volume, equalizer, gain, reverb, and other adjustments). These can be adjusted using physical buttons (such as knobs directly or indirectly connected / coupled to the sound system) or can be software-operable (e.g., operated by a user equipment device coupled to the sound system via a network).

[0005] As sound systems become increasingly complex, users are finding it harder to cope with the sheer number of adjustable settings. Users without a strong technical background may not be able to adjust sound settings in a way that allows the system to create the best audio experience based on their individual preferences. Furthermore, with the increasing flexibility and adjustable sound settings of sound systems, such users may not be able to utilize the full capabilities of the system.

[0006] Therefore, there is a need in industry for an arrangement for audio applications that simplifies the complexity of sound systems for the average user and allows for adjustment of the sound to meet the user's personal preferences. Summary of the Invention

[0007] To achieve the above objectives, the present invention provides devices, methods and systems as described in the appended claims.

[0008] In a preferred embodiment, an apparatus including a memory and a processor is provided. The processor is operable to: receive a first audio signal (e.g., audio input), receive metadata associated with the first audio signal, and create a first profile associated with the first audio signal, the first profile including a plurality of adjustable audio parameters. The processor is configured to process the first audio signal using the plurality of adjustable audio parameters of the first profile; and to transmit the first audio signal processed using the first profile to one or more playback devices. The processor is configured to receive one or more first user inputs from one or more sensors, analyze the one or more first user inputs, and adjust one or more audio parameters of the plurality of audio parameters in the first profile based on the analysis, metadata, or a combination of analysis and metadata. The processor is configured to process the first audio signal using the adjusted first profile, and to transmit the first audio signal processed using the adjusted first profile to one or more playback devices.

[0009] Advantageously, by providing a guided method for collecting and analyzing data from audio signals and user data, and automatically adjusting sound settings according to user preferences, the need for adjusting technical sound settings can be eliminated from the user's purview. Therefore, a personalized sound system can be automatically provided, which improves the user experience.

[0010] In the implementation scheme, the processor is further operable to: receive one or more second user inputs, analyze the one or more second user inputs, adjust one or more audio parameters of a plurality of audio parameters of a first profile based on the analysis of the one or more second user inputs, process a first audio signal using the adjusted first profile, and send the first audio signal processed using the adjusted first profile to one or more playback devices.

[0011] Advantageously, the device can learn from additional amounts of collected data and use the results to more accurately predict and automatically adapt preference settings. This provides users with more personalized and optimized sound settings.

[0012] In the implementation scheme, the processor is further operable to: send a request for one or more first user inputs, and receive one or more first user inputs after sending the request.

[0013] Advantageously, the device can engage in active learning by prompting the user to provide input (e.g., statements such as "I like this," thumbs-up gestures, or similar movements). This provides an additional type of input to understand user preferences compared to relying solely on passive input (e.g., waiting for the user to increase the volume when playing music of a certain genre). The processor can periodically trigger the user, thus presenting intermediate learning results by requesting further user feedback. Therefore, the results are continuously improved.

[0014] In the implementation scheme, the processor is further operable to: send a request for one or more second user inputs, and receive one or more second user inputs after sending the request.

[0015] Advantageously, the device can engage in active learning by prompting the user to provide input (e.g., statements such as "I like this," thumbs-up gestures, or similar movements). This provides an additional type of input to understand user preferences compared to relying solely on passive input (e.g., waiting for the user to increase the volume when playing music of a certain genre). The processor can periodically trigger the user, thus presenting intermediate learning results by requesting further user feedback. Therefore, the results are continuously improved.

[0016] In the implementation scheme, the first audio signal is a music file, and the metadata includes one or more of the following: the genre of the music file, the alphanumeric data of the music file, and the duration of the music file.

[0017] Advantageously, audio signals (such as music) can be categorized into a large number of different categories and category types (e.g., based on their genre, any text data, digital data, duration of the music, etc.), and a unique profile can be created for any of these categories. Therefore, unique profiles can be created, for example, based on the genre of the music, the artist of the music, the language of the music, or any other metadata found in the audio signal.

[0018] In the implementation, one or more first and / or second user inputs include one or more of the following: images from a camera, videos from a camera, motion from a motion sensor, audio input from a microphone, physical input on a user interface, and biometric input from one or more sensors.

[0019] Advantageously, a user's true preferences for settings can be determined by recording their physical movement and biometrics.

[0020] In the implementation scheme, multiple audio parameters include one or more of the following: volume, equalizer settings, delay settings, gain settings, reverb settings, and one or more spatial immersion settings.

[0021] Advantageously, sound settings can be accurately adjusted to reflect the user's true preferences.

[0022] In the implementation scheme, one or more audio parameters among a plurality of audio parameters are preset when the first profile is created.

[0023] Advantageously, computational requirements are reduced by providing one or more preset audio parameters, which may be at or close to the user's preferences. These preset audio parameters can be based on other user profiles that have profiles similar to the user's profile.

[0024] In the implementation scheme, the processor is further operable to: receive a second audio signal, receive metadata associated with the second audio signal, determine a similarity score between the metadata of the second audio signal and the metadata of a first audio signal, and if the similarity score is higher than a predetermined threshold, process the second audio signal using a plurality of adjustable audio parameters of a first profile. The processor is further operable to: transmit the second audio signal processed using the first profile to one or more playback devices, receive one or more third user inputs from one or more sensors, analyze the one or more third user inputs, and adjust one or more audio parameters of a plurality of audio parameters of the first profile based on the analysis, metadata, or a combination of analysis and metadata. The processor is further operable to: process the second audio signal using the adjusted first profile, and transmit the second audio signal processed using the adjusted first profile to one or more playback devices.

[0025] Advantageously, it can play various types of audio signals (e.g., music). If different types of audio signals are determined to be similar to previously played audio signals, the system can apply the same profile, thereby providing audio signal playback according to the user's preferences.

[0026] In the implementation scheme, the processor is further operable to: receive a second audio signal, receive metadata associated with the second audio signal, determine a similarity score between the metadata of the second audio signal and the metadata of a first audio signal, and if the similarity score is below a predetermined threshold, create a second profile associated with the second audio signal, the second profile including a plurality of adjustable audio parameters, process the second audio signal using the plurality of adjustable audio parameters of the second profile, and send the second audio signal processed using the second profile to one or more playback devices. The processor is further operable to: receive one or more fourth user inputs from one or more sensors, analyze the one or more fourth user inputs, adjust one or more audio parameters of the plurality of audio parameters in the second profile based on the analysis, metadata, or a combination of analysis and metadata, process the second audio signal using the adjusted second profile, and send the second audio signal processed using the adjusted second profile to one or more playback devices.

[0027] Advantageously, it can play various types of audio signals (e.g., music). If a different type of audio signal is determined to be different from the type of audio signal previously played, the system can apply a different profile or create a new profile, thereby providing audio signal playback according to the user's preferences.

[0028] In a preferred embodiment, a system is provided. The system includes a device as defined above, one or more playback devices coupled to the device, one or more sensors coupled to the device, and a graphical user interface (GUI) coupled to the device.

[0029] Advantageously, by providing a guided method for collecting and analyzing data from audio signals and user data, and automatically adjusting sound settings according to user preferences, the need for adjusting technical sound settings can be eliminated from the user's purview. Therefore, a personalized sound system can be automatically provided, which improves the user experience.

[0030] In a preferred embodiment, a method is provided. The method includes: receiving a first audio signal, receiving metadata associated with the first audio signal, and creating a first profile associated with the first audio signal, the first profile including a plurality of adjustable audio parameters. The method includes: processing the first audio signal using the plurality of adjustable audio parameters of the first profile, and transmitting the processed first audio signal using the first profile to one or more playback devices. The method also includes: receiving one or more first user inputs from one or more sensors, analyzing the one or more first user inputs, and adjusting one or more audio parameters of the plurality of audio parameters in the first profile based on the analysis, metadata, or a combination of analysis and metadata. Finally, the method includes: processing the first audio signal using the adjusted first profile, and transmitting the processed first audio signal using the adjusted first profile to one or more playback devices.

[0031] Advantageously, by providing a guided method for collecting and analyzing data from audio signals and user data, and automatically adjusting sound settings according to user preferences, the need for adjusting technical sound settings can be eliminated from the user's purview. Therefore, a personalized sound system can be automatically provided, which improves the user experience.

[0032] In one implementation, the method further includes: receiving one or more second user inputs, analyzing the one or more second user inputs, and adjusting one or more audio parameters of a plurality of audio parameters of a first profile based on the analysis of the one or more second user inputs. The method further includes: processing a first audio signal using the adjusted first profile, and transmitting the first audio signal processed using the adjusted first profile to one or more playback devices.

[0033] Advantageously, the device can learn from additional amounts of collected data and use the results to more accurately predict and automatically adapt preference settings. This provides users with more personalized and optimized sound settings.

[0034] In one implementation, the method further includes: receiving a second audio signal, receiving metadata associated with the second audio signal, determining a similarity score between the metadata of the second audio signal and the metadata of a first audio signal, and processing the second audio signal using a plurality of adjustable audio parameters of a first profile if the similarity score is higher than a predetermined threshold. The method further includes: transmitting the second audio signal processed using the first profile to one or more playback devices, receiving one or more third user inputs from one or more sensors, analyzing the one or more third user inputs, and adjusting one or more audio parameters of a plurality of audio parameters of the first profile based on the analysis, metadata, or a combination of analysis and metadata. The method further includes: processing the second audio signal using the adjusted first profile, and transmitting the second audio signal processed using the adjusted first profile to one or more playback devices.

[0035] Advantageously, it can play various types of audio signals (e.g., music). If different types of audio signals are determined to be similar to previously played audio signals, the system can apply the same profile, thereby providing audio signal playback according to the user's preferences.

[0036] In an implementation, the method further includes: receiving a second audio signal; receiving metadata associated with the second audio signal; determining a similarity score between the metadata of the second audio signal and the metadata of a first audio signal; and if the similarity score is below a predetermined threshold, creating a second profile associated with the second audio signal, the second profile including a plurality of adjustable audio parameters. The method further includes: processing the second audio signal using the plurality of adjustable audio parameters of the second profile; sending the processed second audio signal using the second profile to one or more playback devices; receiving one or more fourth user inputs from one or more sensors; and analyzing the one or more fourth user inputs. The method further includes: adjusting one or more audio parameters of the plurality of audio parameters of the second profile based on analysis, metadata, or a combination of analysis and metadata; processing the second audio signal using the adjusted second profile; and sending the processed second audio signal using the adjusted second profile to one or more playback devices.

[0037] Advantageously, it can play various types of audio signals (e.g., music). If a different type of audio signal is determined to be different from the type of audio signal previously played, the system can apply a different profile or create a new profile, thereby providing audio signal playback according to the user's preferences. Attached Figure Description

[0038] The features, aspects and advantages of this disclosure may become more apparent from the following detailed description set forth in conjunction with the accompanying drawings, throughout which the same reference numerals refer to similar elements.

[0039] Figure 1 This demonstrates user interaction with the sound system;

[0040] Figure 2 A system according to the present invention is shown, the system including a computer, a network coupled to the computer, and a plurality of playback devices coupled to a plurality of audio channels, the computer including a processor, memory, and a graphical user interface (GUI);

[0041] Figure 3 The invention is shown Figure 2 Example scenarios on a graphical user interface;

[0042] Figure 4 The invention is shown Figure 2 Further example scenarios on the graphical user interface;

[0043] Figure 5 The invention is shown Figure 2 A further example scenario on the graphical user interface;

[0044] Figure 6 The invention is shown Figure 2 Another example scenario on a graphical user interface;

[0045] Figure 7 A flowchart illustrating a method for audio applications according to the present invention is provided; and

[0046] Figure 8 A flowchart depicts a further method for audio applications according to an alternative embodiment of the present invention. Detailed Implementation

[0047] Figure 1Sound systems 108a and 108b and a user 106 interacting with sound systems 108a and 108b are illustrated. Sound systems 108a and 108b (also referred to herein by reference numeral 108) can be any system including one or more playback devices (e.g., one or more audio playback devices, which may be speakers, drivers, televisions, user equipment devices, or similar devices) 102 coupled to computer 104. One or more playback devices (or drivers) 102 can be coupled (using wired or wireless connections) to computer 104 via one or more channels (e.g., to support mono, stereo, or surround sound playback). One or more playback devices 102 can be standalone speakers or can be part of a speaker system (such as a soundbar, television, mobile phone, or similar device). Computer 104 can be a user equipment such as a tablet computer and may include a graphical user interface (GUI). Computer 104 may be integrated into one or more playback devices 102 (such as in a mobile phone or other user equipment), or it may be separate from one or more playback devices 102 (such as a separate user equipment, tablet, remote control, or similar device to operate one or more speakers). Computer 104 may have audio data stored thereon (such as music, video, audiobooks, or any other type of audio data), and / or computer 104 may be operable to receive audio data from a source (such as from a network or physical storage medium coupled to computer 104). Computer 104 may be operable to alter the sound effects of audio before it is played by one or more playback devices 102. Computer 104 may also be operable to receive one or more inputs from user 106.

[0048] The sound system 108a may be a system (or unit) separate from the user. For example, the sound system 108a may be a soundbar, a television set, a user equipment device, a mobile phone, any type of handheld electronic device, or any other device that includes one or more speakers and a computer 104. As described above, the computer 104 may be part of one or more playback devices 102, or the computer may be separate from one or more playback devices 102.

[0049] The sound system 108b may be a large system (or unit) in which the user 106 is at least partially located within the sound system 108b. For example, the sound system 108b may be a vehicle, such as any type of road, off-road, water, underwater, or air vehicle, which includes one or more playback devices 102 and a computer 104 for operating the one or more playback devices 102. As described above, the computer 104 may be part of the one or more playback devices 102, or the computer may be detached from the one or more playback devices 102.

[0050] like Figure 1 As shown, with the increasing complexity of the sound system 108, users such as user 106 are increasingly overwhelmed by the number of user-adjustable settings. Figure 1 As shown on computer 104, adjustable settings can include various sound settings such as volume, delay, reverb, equalizer settings, gain settings, etc. For users 106 without a strong technical background, they may not be able to adjust the sound settings in a way that allows the sound system 108 to create the best sound experience according to their personal preferences. Furthermore, with the increased flexibility and adjustable sound settings of the sound system 108, such users 106 may not be able to utilize the full capabilities of the system.

[0051] This invention provides a device and system (hereinafter referred to as...) Figure 2 The invention describes a guided method for collecting and analyzing user data and automatically adjusting sound settings to the preferences of user 106, thereby helping user 106 to avoid the need for adjusting technical sound settings. This facilitates easy personalization of the sound system 108 according to the user's own preferences and improves the overall user experience. The invention customizes the experience of user 106 by learning user preferences based on collected data (such as preferred music genres, user input). User input may be received via an application on computer 104, a human-computer interface (HMI) on computer 104, verbal input, automatic emotion detection, or a combination thereof. The invention focuses on data collection and learning from it. Computer 104 may include an Experience Learning Engine (ELE), which may be a dedicated part of the processor and / or memory of computer 104 to collect and analyze user data and automatically adjust sound settings to the preferences of user 106. Advantageously, a personalized user experience is provided. Therefore, the experience provided to the user (e.g., audio or light effects) is based on the user's specific individual preferences. These preferences are the input data for the ELE and are the basis for learning and subsequent personalization.

[0052] Figure 2 A system 200 including device 202 is shown. Device 202 may be a computer, such as those described above. Figure 1The computer 104 described herein. Device 202 includes memory 206 and processor 204. Device 202 may include an Experience Learning Engine (ELE), which may be a dedicated part of the processor 204 and / or memory 204 of computer 202. Device 202 may include a graphical user interface (GUI) 208, which may include any type of display or projection system operable to display one or more images to a user. GUI 208 may be operable to receive one or more inputs from the user (e.g., touch input from a touchscreen or from one or more physical buttons or knobs). GUI 208 may be partially integrated with the computer (including processor 204 and memory 206), or the GUI may be separate and coupled (e.g., via a wired or wireless connection) to the computer. Device 202 may include one or more input / output interfaces (not shown). Device 202 may be coupled (e.g., utilizing a wired or wireless connection) to network 210, and the device may send data to and receive data from network 210. Data may include alphanumeric data, audio data, video data, or any other type of data / metadata.

[0053] System 200 may include one or more output channels 212 coupled to device 202. System 200 may include one or more playback devices 214. Each of the one or more playback devices 214 may be a speaker, driver, user equipment, television, or any other device that includes a means of playing audio signals. Each of the one or more output channels 212 may be coupled to one or more playback devices 214. Each of the one or more output channels 212 may be operable to receive the same or different audio signals from device 202. Thus, system 200 may play audio in mono, stereo, and / or surround sound. System 200 may include one or more sensors 216 coupled to device 202. System 200 may include one or more sensors 216 operable to detect different types of input (e.g., this may include one or more motion sensors, microphones, cameras, one or more touch or other types of tactile sensors, one or more biometric sensors, etc.).

[0054] Therefore, the ELE receives one or more inputs, processes those inputs, and sends one or more outputs from processor 204 and memory 206 to GUI 208, one or more playback devices 214, or a combination thereof. The one or more inputs may include one or more user inputs as described in this document, one or more user profiles (stored on memory 206 or network 210) as described in this document, or any combination thereof. The one or more outputs may include one or more adjusted audio parameters (e.g., adjustments to multiple audio parameters as described in this document), one or more user profiles as described in this document (each of which may include user preferences), user categorization (e.g., determining whether a user is a "manager," "child," "parent," or similar role), and a display of the learned user's preferences on GUI 208 (as described below). Figure 6 (as described herein) one or more animated avatars related to the user's preferences, or any combination thereof. Advantageously, device 202 can provide the user with customized, personalized sound, video, light, or other experiences.

[0055] Computer 202 can perform multiple operations to automatically provide a personalized sound system that improves user experience. Operations may include data collection operations, in which computer 202 receives multiple inputs. Operations may include learning operations, in which at least a portion of computer 202 (e.g., ELE) learns from the collected data and uses the results of the learned collected data to automatically predict and adapt preference settings. Operations may include computer 202 (e.g., ELE) presenting the learning results to a user and allowing the user to modify them. Operations may include user identification and / or classification operations, in which one or more profiles (such as user profiles and / or audio profiles) may be created, each of which stores predicted and preferred settings. User profiles may include one or more audio profiles.

[0056] As part of the data collection operation, the processor 204 of computer 202 receives multiple inputs. One input is an audio signal (e.g., which may be music data, audio data, video data with audio signals, or any other type of data including audio). The audio signal may be stored on memory 206 of the memory, or the audio signal may be received from an external source, such as network 210 or any physical medium (such as a CD, cassette tape, vinyl record, or other memory separate from computer 202). The processor 204 also receives metadata associated with the audio signal. The processor 206 is operable to create a profile associated with the received audio signal. This profile may be created based on the metadata associated with the received audio signal. For example, the profile may be created by the processor to correspond to the genre of music, the duration of the audio signal, or any other alphanumeric data within the audio signal. The profile includes multiple adjustable audio parameters, as described in more detail below. Processor 206 is configured to process audio signals using a plurality of adjustable audio parameters of a first profile, and to send the profile-processed audio signals to one or more playback devices 214 (or to one or more channels 212 coupled to one or more playback devices 214). The profile may be stored on memory 206 of computer 202. Alternatively or additionally, the profile may be stored on network 210 to allow easy access from any device connected to the network (e.g., any other computer), thereby ensuring that the user's settings are stored and accessible regardless of which device the user is using.

[0057] In this implementation, the audio signal is a music file, and the metadata includes one or more of the following: the genre of the music file, the alphanumeric data of the music file, the duration of the music file, and any other type of data. The alphanumeric data can be descriptive metadata that provides information about the nature of the music file. For example, this could include genre, artist name, release date, tempo, pitch, and any other information about the music file.

[0058] Advantageously, audio signals (such as music) can be categorized into a large number of different categories and category types (e.g., based on their genre, any text data, digital data, duration of the music, etc.), and a unique profile can be created for any of these categories. Therefore, unique profiles can be created, for example, based on the genre of the music, the artist of the music, the language of the music, or any other metadata found in the audio signal.

[0059] In the implementation, multiple audio parameters may include one or more of the following: volume, equalizer settings, delay settings, gain settings, reverb settings, and one or more spatial immersion settings. Audio parameters are not limited to this list and may include any number or type of parameters that can adjust the user's perceived audio experience. For example, more complex audio technologies have hundreds of different tuning parameters. Some of these are parameters that are easily understood by the end user (e.g., 'amount of immersion' or 'room size'). Other parameters may be low-level parameters used by engineers. These may include parameters such as 'attack time for mono detection', 'forgetting factor for center extraction', etc. Advantageously, sound settings can be precisely adjusted to reflect the user's true preferences.

[0060] Data collection operations include querying user preferences. This can include, for example: Figure 4 Active queries as described in the text, such as Figure 5 The active query may be a passive query as described herein, or a combination of both. An active query may include prompting the user to define personal preferences (such as preferred volume, equalizer settings, immersion settings, etc.) via an assistant (i.e., a welcome assistant) in applications 300, 400, 500 within the GUI. This may include the user selecting a preferred variant (such as a preset setting) by choosing a "like / dislike" button on the GUI. A passive query may include monitoring the user's interaction with an audio signal in the background (e.g., by measuring one or more body movements, one or more audio queues (such as "I like this"), or singing into the audio signal). A passive query may also include analysis of the user's behavior and emotions based on sensor data (e.g., biometric sensors, body temperature sensors, etc.). Active or passive queries may be recorded as user input by one or more sensors 216 coupled to computer 202. Processor 204 is operable to receive one or more user inputs from one or more sensors. One or more user inputs may include one or more of the following: images from a camera, video from a camera, motion from a motion sensor, audio input from a microphone, physical input on a user interface, and biometric input from one or more sensors. The list above is a non-exhaustive list, and one or more user inputs can include any other type of user input. Advantageously, a user's true preferences for settings can be determined by recording the user's physical movement and biometrics.

[0061] In the learning operation, at least a portion of computer 202 (e.g., ELE) learns from the collected data and uses the results of the learned collected data to automatically predict and adapt preference settings. Processor 204 is configured to analyze one or more user inputs and adjust one or more audio parameters of a profile based on analysis, metadata, or a combination of analysis and metadata. Each of the one or more user inputs can be categorized as a positive or negative input. In other words, each of the one or more user inputs can be categorized as confirmation that the user likes one or more of the current parameters (positive input) or that the user dislikes one or more of the current parameters (negative input). Each of the one or more user inputs can be assigned to one or more specific parameters. For example, processor 204 can passively determine that a user likes music from a particular genre, artist, etc., by analyzing the user's body movements (e.g., by recording the user with a sensor such as a camera) and observing "positive" input (which could be a nod). Processor 204 can actively determine that a user dislikes the volume level of the current audio signal by prompting / asking the user. In an example, this could include displaying questions on a GUI, stating "Do you like this volume?", "Is the volume too high?", "Is the volume too low?", or similar questions. Processor 204 can request answers (e.g., by displaying possible answers on a GUI, by posing an audible question, etc.) and is operable to receive affirmative or negative answers, such as "Yes", "No", "It is too high", "It is too low", "I like this", "I don't like this", etc. Therefore, processor 204 can determine a user's preference for an audio signal and one or more parameters of the audio signal from one or more user inputs. In an implementation, processor 204 may include a machine learning (ML) model to predict the user's preferred audio parameters for the audio signal. The ML model can also learn the user's input and is operable to determine whether the user input is classified as a positive or negative response.

[0062] Processor 204 is configured to process an audio signal using a modified profile and to send the processed audio signal to one or more playback devices (or to one or more channels coupled to one or more playback devices). In an embodiment, processor 204 can continuously receive and analyze each of multiple user inputs, even while the audio signal is being played through playback device 214. Processor 204 can continuously adjust one or more audio parameters of the profile each time it receives and analyzes one or more additional user inputs. Processor 204 can continuously process (i.e., update) the audio signal using the modified profile based on analysis, metadata, or a combination of analysis and metadata. Therefore, the audio signal is automatically adjusted to more closely resemble the user's preferred settings.

[0063] Advantageously, by providing a guided method for collecting and analyzing data from audio signals and user data, and automatically adjusting sound settings according to user preferences, the need for adjusting technical sound settings can be eliminated from the user's purview. Therefore, a personalized sound system can be automatically provided, which improves the user experience.

[0064] In the implementation, the profile may be a user profile (i.e., a profile specific to a user of computer 202). The user profile may include one or more additional profiles (such as one or more audio profiles, which may be specific to a group of similar metadata such as one or more genres, one or more artists). The user profile may be associated with the ELE of device 202. Therefore, the user profile may be created by the ELE and may subsequently be adapted by the ELE based on the collection and processing of one or more user inputs.

[0065] In the implementation, processor 204 can run a welcome assistant, such as one that can be displayed on GUI 208. Figure 3 The application 300 shown. The welcome assistant can prompt the user for user identity input. User identity input includes receiving a photo or video and performing camera-based recognition (such as, but not limited to, facial recognition), receiving audio signals via a microphone and performing audio signal analysis (such as, but not limited to, voice signature), Near Field Chip (NFC) handshake, Ultra Wideband (UWB) handshake, inserting a smart key, or entering an alphanumeric code (such as a password or passphrase, Bluetooth handshake, or association with a General Motors profile). After receiving user identity input, device 202 can load one or more user profiles (stored in memory 206 or network 210) associated with the user's identity credentials.

[0066] Alternatively or additionally, application 300 (Welcome Assistant) may offer the user the option to create a new user profile, and the new user profile may be stored on memory 206 or network 210. This may be advantageous in scenarios where multiple different users use the same device 202 and each of the different users has different preferred sound requirements. Creating a new user profile and adjusting each of the existing user profiles may involve, for example... Figure 4 Application 400 discusses one or more active query steps, such as Figure 5 The application may involve one or more passive query steps, or a combination of both, as discussed in Application 500. One or more user profiles as described herein may be created with blank settings, or may include preset initial preferences such as music genre, loudness level, preferred immersion level, speed compensation, etc.

[0067] Application 300 (Welcome Assistant) may include an interactive wizard to determine the user's top preferences. This may include prompting the user (via GUI 208) to input the type of music the user is interested in. Prompts to the user may include one or more visual cues (such as images and / or videos), one or more audio cues, or similar cues. For example, a visual cue could be a person with a speaker on their shoulder indicating a first preset, or a person sitting in a classical music hall indicating a different second preset. The interactive wizard may include a display of information (e.g., technical features, explanations, etc.) on multiple adjustable audio parameters. For example, this may include explanations of immersion and the various types of immersion that system 200 can provide. The interactive wizard may include playback of different music genres, different musical styles, etc., and prompts the user to provide input (e.g., tapping up / down, verbal instructions "I like / I don't like this," physical input to GUI 208, etc.) indicating whether the user likes or dislikes any of the playback. The interactive wizard may include an option to skip the interactive wizard.

[0068] In the implementation scheme, system 200 may be operable to perform active queries (or active query operations) as described above.

[0069] Processor 204 can run as Figure 4The application 400 shown provides an option to activate or deactivate an active query operation. Application 400 can be displayed on GUI 208. The display of application 400 can occur after the display of welcome screen 300. Device 202 can receive user input (such as voice commands, physical input from one or more physical buttons, touch input on a touchscreen such as GUI 208, motion input from a motion sensor or camera, or similar input) to activate or deactivate one or more active query operations. One or more active query operations (if activated) can include sending one or more prompts to the user to provide input data. Thus, one or more active query operations correspond to one or more requests for one or more user inputs. Processor 204 can send requests for one or more user inputs. Requests can include actively changing one or more of a plurality of audio parameters and prompting the user (e.g., by displaying a question on GUI 208, by playing an audio message such as a question on one or more playback devices, or similarly) to provide user input (response). User input can be a binary response (such as a positive or negative response). After sending one or more requests, processor 204 can receive one or more user inputs. User input may include one or more physical inputs on GUI 208 (e.g., selecting one or more displayed options on a touchscreen or physical button of system 200), one or more visual inputs recorded by one or more cameras coupled to processor 204 of system 200, one or more audio inputs recorded by one or more microphones coupled to processor 204 of system, or similar inputs.

[0070] For example, prompts may include statements such as “Do you like this?” and user input may include: selecting a “yes / no” option on GUI 208, speaking a voice command such as “yes / no” (which may be recorded by one or more microphones coupled to processor 204 and thus may be input to device 202), providing a thumb up or thumb down movement (or similar movement, which may be recorded by one or more cameras coupled to processor 204 and thus may be input to device 202) or similar input.

[0071] Advantageously, the device can engage in active learning by prompting the user to provide input (e.g., statements such as "I like this," thumbs-up gestures, or similar movements). This provides an additional type of input to understand user preferences compared to relying solely on passive input (e.g., waiting for the user to increase the volume when playing music of a certain genre). The processor can periodically trigger the user, thus presenting intermediate learning results by requesting further user feedback. Therefore, the results are continuously improved.

[0072] In the implementation scheme, system 200 may be operable to perform passive queries (or passive query operations) as described above.

[0073] Processor 204 can run as Figure 5 The application 500 shown provides an option to activate or deactivate a passive query operation. Application 500 can be displayed on GUI 208. The display of application 500 can occur after the display of welcome screen 300, after the display of application 400, or before the display of application 400. Device 202 can receive user input (such as voice commands as described above, physical input from one or more physical buttons, touch input on a touchscreen such as GUI 208, motion input from a motion sensor or camera, or similar input) to activate or deactivate one or more active query operations. One or more passive query operations (if activated) can include monitoring user interaction with audio signals in the background (e.g., by measuring one or more body movements, one or more audio queues (such as the user saying "I like this"), or singing into an audio signal). Passive queries can also include analysis of user behavior and emotions based on sensor data (e.g., biometric sensors, body temperature sensors, etc.). Active or passive queries can be recorded as user input by one or more sensors 216 coupled to computer 202. Processor 204 is operable to receive one or more user inputs from one or more sensors. One or more user inputs may include one or more of the following: images from a camera, video from a camera, motion from a motion sensor, audio input from a microphone, physical input on the user interface, and biometric input from one or more sensors. The above list is non-exhaustive, and one or more user inputs may include any other type of user input. Advantageously, a user's true preferences for settings can be determined by recording their physical movements and biometrics.

[0074] In one implementation, the processor 204 is further operable to receive additional (second) user input following one or more user inputs (first user inputs) received as described above. The second user input can be received from, for example... Figure 4 The described active query operation or from such Figure 5The described passive query operation is received. Processor 204 can analyze one or more second user inputs. This may include classifying the one or more second user inputs as positive or negative inputs. Processor 204 can adjust one or more audio parameters of a profile based on the analysis of the one or more second user inputs. In other words, if the second user input is classified as a negative input, processor 204 can adjust one or more audio parameters. Alternatively, if the second user input is classified as a positive input, processor 204 may not adjust the one or more audio parameters. Processor 204 can process the audio signal using the adjusted profile (referring to one or more adjusted audio parameters) and send the processed audio signal using the adjusted profile to one or more playback devices 214. Advantageously, the device can learn from additional amounts of collected data and use the results to more accurately predict and automatically adapt preference settings. This provides the user with more personalized and optimized sound settings.

[0075] In one implementation, the processor 204 is further operable to send a request for one or more second user inputs. This request may be as described above. Figure 4 This is part of the active query operation described above. Processor 204 can, as described above... Figure 4 Following the sending request described in the section on (first) user input, one or more second user inputs are received. Advantageously, device 202 can engage in active learning by prompting the user to provide input (e.g., a statement such as "I like this," a thumbs-up gesture, or a similar movement). This provides additional input types to understand user preferences compared to relying solely on passive input (e.g., waiting for the user to increase the volume when playing music of a certain genre). The processor can periodically trigger the user to present intermediate learning results by requesting further user feedback. Thus, the results are continuously improved.

[0076] Processor 204 can accept one or more user inputs (whether as...) Figure 4 Is it received as part of the active query operation described in the document, or as such? Figure 5The passive query operation described herein (received as part of, or a combination thereof) is categorized into positive or negative input. Processor 204 can associate each user input with a specific audio parameter among a plurality of audio parameters, with a subset of the plurality of audio parameters (which includes two or more audio parameters among the plurality of audio parameters), or with all audio parameters among the plurality of audio parameters. Processor 204 can adjust the associated audio parameters, the associated subset of audio parameters, or all audio parameters based on analysis depending on whether one or more user inputs are "positive" or "negative." For example, if the user input is categorized as "positive," processor 204 can determine that the user likes the current settings of the associated one or more audio parameters and may not adjust those associated one or more audio parameters. If the user input is categorized as "negative," processor 204 can determine that the user dislikes the current settings of the associated one or more audio parameters and may adjust those associated one or more audio parameters. Therefore, processor 204 can adjust one or more audio parameters among the plurality of audio parameters in the profile based on analysis.

[0077] In the implementation scheme, system 200 may be operable to display data from ELE (such as...) on GUI 208. Figure 6 The learning results of application 600 are shown. Application 600 can be displayed on GUI 208. The display of application 600 can occur after the display of welcome screen 300, after the display of application 400, or after the display of application 500. The display of application 600 can also occur before the display of welcome screen 300, before the display of application 400, or before the display of application 500. Application 600 can include an overview of the learning results by displaying an overview of each of a plurality of audio parameters or one or more subsets of audio parameters in application 600. This can include one or more avatars for each of the plurality of audio parameters and / or subsets of audio parameters. The learning results can include learning results related to metadata of the audio signal as described above. The learning results can correspond to the user's preference for the currently selected profile. For example, as Figure 6 As shown, the selected profiles have a 60% rock music listening history and a 30% classical music listening history. Figure 6 As shown, the selected profiles are for rock music with a preference for high volume and high immersion. The selected profiles are for classical music with a preference for medium volume and low immersion.

[0078] Learning outcomes may include ELE statistics and learning history, options to modify learned preferences (via GUI208), and options to activate or deactivate one or more learning operations (as described above). Figure 4 and Figure 5As described above, it allows comparison of different user profiles, comparison of passive and active learning states, and / or comparison of learning results with preset settings. Each of these learning results can be associated with a stored user profile. GUI 208 can be operable to receive one or more inputs (e.g., physical input received on a touchscreen such as GUI 208) to modify the learning results. This is advantageous when the user disagrees with the learned results and wants to manually change one or more parameters. The one or more inputs may include, for example, decreasing or increasing the size of icons in application 600 (such as 'loudness' or 'immersion' icons) or similar inputs. This input can be considered as described above in Figure 4 The active input described in [the text].

[0079] In the implementation scheme, one or more of the multiple audio parameters described above can be used to create a profile (e.g., using...). Figure 3 The profile created by application 300 as described in the document is preset. Advantageously, computational requirements are reduced by providing one or more preset audio parameters, which may be at or close to the user's preferences. The preset audio parameters can be preset based on other user profiles that have profiles similar to the user's profile.

[0080] In the implementation, processor 204 may include a machine learning (ML) model, ML algorithm, artificial intelligence (AI) black box, or the like, to predict preferred audio parameters of the user's audio signal. The ML model, ML algorithm, or AI black box may be operable to determine whether the user input is classified as a positive or negative response.

[0081] In the implementation, processor 204 may be operable to receive a different audio signal (i.e., a second audio signal). The second audio signal may be different from the audio signal described above (i.e., the first audio signal). Processor 204 may be operable to receive metadata associated with the second audio signal (as described above). Processor 204 may be operable to determine a similarity score between the metadata of the second audio signal and the metadata of the first audio signal. For example, processor 204 may feed the metadata of the second audio signal and the metadata of the first audio signal to an ML model, ML algorithm, AI black box, or the like. Processor 204 (i.e., ML model, ML algorithm, AI black box, or the like) may compare the metadata of the second audio signal with the metadata of the first audio signal. The ML model, ML algorithm, AI black box, or the like may determine and provide a similarity score (e.g., a numerical value such as a percentage).

[0082] If the similarity score is at or above a predetermined threshold, the processor 204 can determine that the second audio signal is similar to the first audio signal. The predetermined threshold can be any numerical value (e.g., it can be a number such as '10', '0.5', or any other suitable number), or it can be a percentage (e.g., 50% or ½). The examples of numerical values ​​and percentages are non-limiting examples, and the predetermined threshold can be any numerical or percentage value.

[0083] If processor 204 determines that the second audio signal is similar to the first audio signal, processor 204 is operable to process the second audio signal using a plurality of adjustable audio parameters of the first profile. Processor 204 may be operable to send the processed second audio signal using the first profile to one or more playback devices 214 (as described above). Processor 204 may be operable to receive one or more user inputs from one or more sensors 216 (as described above). Processor 204 may be operable to analyze one or more user inputs as described above, and adjust one or more audio parameters of the plurality of audio parameters of the first profile based on analysis, metadata, or a combination of analysis and metadata as described above. Processor 204 may be further operable to process the second audio signal using the adjusted first profile, and send the processed second audio signal using the adjusted first profile to one or more playback devices as described above. Advantageously, various types of audio signals (e.g., music) can be played. If different types of audio signals are determined to be similar in type to previously played audio signals, the system can apply the same profile to provide playback of audio signals according to user preferences.

[0084] If the similarity score is below a predetermined threshold, processor 204 may determine that the second audio signal is not similar to the first audio signal. If processor 204 determines that the second audio signal is not similar to the first audio signal, processor 204 is operable to create a second profile associated with the second audio signal if the similarity score is below the predetermined threshold. The second profile includes a plurality of adjustable audio parameters as described above. Processor 204 may be operable to process the second audio signal using the plurality of adjustable audio parameters of the second profile as described above, and to send the processed second audio signal using the second profile to one or more playback devices 216 as described above. Processor 204 may be further operable to receive one or more user inputs from one or more sensors 216 as described above. Processor 204 may be further configured to analyze one or more user inputs as described above, and to adjust one or more audio parameters of the plurality of audio parameters of the second profile based on the analysis, metadata, or a combination of analysis and metadata. Processor 204 may be configured to process the second audio signal using the adjusted second profile, and to send the processed second audio signal using the adjusted second profile to one or more playback devices 214 as described above. Advantageously, it can play various types of audio signals (e.g., music). If a different type of audio signal is determined to be different from the type of audio signal previously played, the system can apply a different profile or create a new profile, thereby providing audio signal playback according to the user's preferences.

[0085] Any references to “first,” “second,” “third,” “fourth,” or similar terms in this document are merely for the purpose of distinguishing multiple features and are not intended as limiting factors, nor do they indicate any order or arrangement of features.

[0086] Figure 7 The invention is illustrated as described above. Figures 1 to 6 The flowchart describes a method for audio applications. This method can be described as follows: Figure 2 The method is performed by the system 200 and / or device 202 described above. The method includes receiving an audio signal (e.g., a first audio signal as described above) at 702. The method includes receiving metadata associated with the audio signal at 704, and creating a profile associated with the audio signal (e.g., a first profile, such as a user profile as described above), which includes multiple adjustable audio parameters as described above, at 706. The method includes processing the audio signal using the multiple adjustable audio parameters of the profile at 708, and sending the processed audio signal using the profile to one or more playback devices (e.g., a first audio signal as described above) at 710. Figure 2The playback device 214 described herein. The method includes, at 712, receiving data from one or more sensors (e.g., such as...). Figure 2 The playback device 216 described above receives one or more user inputs as described above. The method includes analyzing one or more user inputs at 714, and adjusting one or more audio parameters of a profile based on the analysis, metadata, or a combination of analysis and metadata at 716. The method also includes processing the adjusted profile at 718 (e.g., via...). Figure 2 The processor 204 described herein transmits the audio signal, and at 720 transmits the processed audio signal using the adjusted profile to one or more playback devices.

[0087] Advantageously, by providing a guided method for collecting and analyzing data from audio signals and user data, and automatically adjusting sound settings according to user preferences, the need for adjusting technical sound settings can be eliminated from the user's purview. Therefore, a personalized sound system can be automatically provided, which improves the user experience.

[0088] In one implementation, the method further includes: receiving one or more second user inputs, analyzing the one or more second user inputs, and adjusting one or more audio parameters of a plurality of audio parameters of a first profile based on the analysis of the one or more second user inputs. The method further includes: processing a first audio signal using the adjusted first profile, and transmitting the first audio signal processed using the adjusted first profile to one or more playback devices.

[0089] Advantageously, the device can learn from additional amounts of collected data and use the results to more accurately predict and automatically adapt preference settings. This provides users with more personalized and optimized sound settings.

[0090] In one implementation, the method further includes: receiving a second audio signal, receiving metadata associated with the second audio signal, determining a similarity score between the metadata of the second audio signal and the metadata of a first audio signal, and processing the second audio signal using a plurality of adjustable audio parameters of a first profile if the similarity score is higher than a predetermined threshold. The method further includes: transmitting the second audio signal processed using the first profile to one or more playback devices, receiving one or more third user inputs from one or more sensors, analyzing the one or more third user inputs, and adjusting one or more audio parameters of a plurality of audio parameters of the first profile based on the analysis, metadata, or a combination of analysis and metadata. The method further includes: processing the second audio signal using the adjusted first profile, and transmitting the second audio signal processed using the adjusted first profile to one or more playback devices.

[0091] Advantageously, it can play various types of audio signals (e.g., music). If different types of audio signals are determined to be similar to previously played audio signals, the system can apply the same profile, thereby providing audio signal playback according to the user's preferences.

[0092] In an implementation, the method further includes: receiving a second audio signal; receiving metadata associated with the second audio signal; determining a similarity score between the metadata of the second audio signal and the metadata of a first audio signal; and if the similarity score is below a predetermined threshold, creating a second profile associated with the second audio signal, the second profile including a plurality of adjustable audio parameters. The method further includes: processing the second audio signal using the plurality of adjustable audio parameters of the second profile; sending the processed second audio signal using the second profile to one or more playback devices; receiving one or more fourth user inputs from one or more sensors; and analyzing the one or more fourth user inputs. The method further includes: adjusting one or more audio parameters of the plurality of audio parameters of the second profile based on analysis, metadata, or a combination of analysis and metadata; processing the second audio signal using the adjusted second profile; and sending the processed second audio signal using the adjusted second profile to one or more playback devices.

[0093] Advantageously, it can play various types of audio signals (e.g., music). If a different type of audio signal is determined to be different from the type of audio signal previously played, the system can apply a different profile or create a new profile, thereby providing audio signal playback according to the user's preferences.

[0094] Figure 8 It shows Figure 7 A general overview of the methods described herein and the additional method steps for audio applications, which may be related to the methods described above. Figure 7 The methods described and referenced above Figures 1 to 6 The described arrangement is combined. At 802 (or alternatively at 803), system 200 is woken up by receiving a command from the user (e.g., toggling an on / off button or by receiving a wake-up command). At 802, this can be achieved, for example, by... Figure 3The welcome assistant of application 300 described above identifies new users. When the welcome assistant runs, a user profile can be created at 804. Alternatively, if a user logs in using their credentials as described above, an existing user 803 can be identified, and an existing user profile can be retrieved at 805. The newly created user profile at 804 and / or the existing profile retrieved at 805 can be stored on the memory 206 of device 202, on network 210, on a separate device communicating with device 202, or any combination thereof. At 806, the processor 204 of device 202 can receive audio signals as described above, and can also receive metadata and one or more user inputs (e.g., as described above). Figure 4 and Figure 5 (As described above). At 808, processor 204 may update the profile (which may include processing the audio signal with multiple audio parameters or adjusted audio parameters) based on metadata associated with the audio signal, one or more user inputs, or a combination thereof, and may store the updated profile in a profile database (DB) at 810. At 812, processor 204 determines whether the user profile satisfies the user's preferences. This includes analyzing the user input as described above. If processor 204 determines that the user profile satisfies the user's preferences, it is determined that there is nothing new about the user and their preferences. Processor 204 may then query at 814 whether the user exists by actively querying the user for one or more inputs (e.g., ...). Figure 4 (As described in [the original text]). Alternatively or additionally, processor 204 may present the current learning results to the user (e.g., [the original text]). Figure 6 (As described above) and allows the user to make any changes to those learned. If processor 204 determines that the user profile does not meet the user's preferences, it determines that there is something new about the user and their preferences. Processor 204 can then adjust the user profile settings (e.g., by adjusting one or more of the multiple audio parameters of the user profile as described above). At 818, processor 204 can update the user profile with the new learned information and subsequently process the audio signal using the adjusted audio parameters, as in step 808 and as described above.

Claims

1. An apparatus comprising: Memory; as well as Processor, the processor being operable to: Receive the first audio signal; Receive metadata associated with the first audio signal; Create a first profile associated with the first audio signal, the first profile including multiple adjustable audio parameters; The first audio signal is processed using the plurality of adjustable audio parameters described in the first profile; The first audio signal, processed using the first profile, is sent to one or more playback devices. Receive one or more first user inputs from one or more sensors; Analyze the one or more first user inputs; One or more audio parameters of the first profile are adjusted based on the analysis, the metadata, or a combination of the analysis and the metadata. The first audio signal is processed using the adjusted first profile; and The processed first audio signal, after being processed using the adjusted first profile, is sent to the one or more playback devices.

2. The device of claim 1, wherein the processor is further operable to: Receive one or more second user inputs; Analyze the one or more second user inputs; Based on the analysis of the input from the one or more second users, adjust one or more audio parameters of the plurality of audio parameters in the first profile; The first audio signal is processed using the adjusted first profile; and The processed first audio signal, after being processed using the adjusted first profile, is sent to the one or more playback devices.

3. The device of claim 1 or 2, wherein the processor is further operable to: Send a request for the one or more first user inputs; and After sending the request, receive one or more first user inputs.

4. The device of claim 2 or 3, wherein the processor is further operable to: Send a request for input from the one or more second users; and After sending the request, receive the one or more second user inputs.

5. The device as claimed in any one of claims 1 to 4, wherein the first audio signal is a music file, and wherein the metadata includes one or more of the following: The genre of the music file; The alphanumeric data of the music file; and The duration of the music file.

6. The device as claimed in any one of claims 1 to 5, wherein the one or more first user inputs and / or second user inputs comprise one or more of the following: Images from the camera; Video from the camera; Motion from motion sensors; Sound input from the microphone; Physical input on the user interface; as well as Biometric input from one or more sensors.

7. The device as claimed in any one of claims 1 to 6, wherein the plurality of audio parameters includes one or more of the following: volume; Equalizer settings; Delay setting; Gain settings; Reverb settings; and One or more spatial immersion settings.

8. The device as claimed in any one of claims 1 to 7, wherein one or more of the plurality of audio parameters are preset when the first profile is created.

9. The device of any one of claims 1 to 8, wherein the processor is further operable to: Receive the second audio signal; Receive metadata associated with the second audio signal; Determine the similarity score between the metadata of the second audio signal and the metadata of the first audio signal; If the similarity score is higher than a predetermined threshold, the second audio signal is processed using the plurality of adjustable audio parameters of the first profile; The processed second audio signal, after being processed using the first profile, is sent to the one or more playback devices; Receive one or more third-user inputs from one or more sensors; Analyze the input from the one or more third-party users; One or more audio parameters of the plurality of audio parameters in the first profile are adjusted based on the analysis, the metadata, or a combination of the analysis and the metadata; The second audio signal is processed using the adjusted first profile; and The processed second audio signal, after being processed using the adjusted first profile, is sent to the one or more playback devices.

10. The device of any one of claims 1 to 8, wherein the processor is further operable to: Receive the second audio signal; Receive metadata associated with the second audio signal; Determine the similarity score between the metadata of the second audio signal and the metadata of the first audio signal; If the similarity score is below a predetermined threshold, a second profile is created associated with the second audio signal, the second profile including multiple adjustable audio parameters; The second audio signal is processed using the plurality of adjustable audio parameters described in the second profile; The processed second audio signal, after being processed using the second profile, is sent to the one or more playback devices; Receive one or more fourth user inputs from one or more sensors; Analyze the one or more fourth user inputs; One or more audio parameters of the plurality of audio parameters in the second profile are adjusted based on the analysis, the metadata, or a combination of the analysis and the metadata; The second audio signal is processed using the adjusted second profile; and The processed second audio signal, after being processed using the adjusted second profile, is sent to one or more channels.

11. A system comprising: The device as described in any one of claims 1 to 10; One or more playback devices coupled to the device; One or more sensors coupled to the device; A graphical user interface (GUI) coupled to the device.

12. A method comprising: Receive the first audio signal; Receive metadata associated with the first audio signal; Create a first profile associated with the first audio signal, the first profile including multiple adjustable audio parameters; The first audio signal is processed using the plurality of adjustable audio parameters described in the first profile; The processed first audio signal, after being processed using the first profile, is sent to one or more playback devices. Receive one or more first user inputs from one or more sensors; Analyze the one or more first user inputs; One or more audio parameters of the plurality of audio parameters in the first profile are adjusted based on the analysis, the metadata, or a combination of the analysis and the metadata; The first audio signal is processed using the adjusted first profile; as well as The processed first audio signal, after being processed using the adjusted first profile, is sent to the one or more playback devices.

13. The method of claim 12, further comprising: Receive one or more second user inputs; Analyze the one or more second user inputs; Based on the analysis of the input from the one or more second users, adjust one or more audio parameters of the plurality of audio parameters in the first profile; The first audio signal is processed using the adjusted first profile; as well as The processed first audio signal, after being processed using the adjusted first profile, is sent to the one or more playback devices.

14. The method of any one of claims 12 or 13, further comprising: Receive the second audio signal; Receive metadata associated with the second audio signal; Determine the similarity score between the metadata of the second audio signal and the metadata of the first audio signal; If the similarity score is higher than a predetermined threshold, the second audio signal is processed using the plurality of adjustable audio parameters of the first profile; The processed second audio signal, after being processed using the first profile, is sent to the one or more playback devices; Receive one or more third-user inputs from one or more sensors; Analyze the input from the one or more third-party users; One or more audio parameters of the plurality of audio parameters in the first profile are adjusted based on the analysis, the metadata, or a combination of the analysis and the metadata; The second audio signal is processed using the adjusted first profile; as well as The processed second audio signal, after being processed using the adjusted first profile, is sent to the one or more playback devices.

15. The method of any one of claims 12 or 13, further comprising: Receive the second audio signal; Receive metadata associated with the second audio signal; Determine the similarity score between the metadata of the second audio signal and the metadata of the first audio signal; If the similarity score is below a predetermined threshold, a second profile is created associated with the second audio signal, the second profile including multiple adjustable audio parameters; The second audio signal is processed using the plurality of adjustable audio parameters described in the second profile; The processed second audio signal, after being processed using the second profile, is sent to the one or more playback devices; Receive one or more fourth user inputs from one or more sensors; Analyze the one or more fourth user inputs; One or more audio parameters of the plurality of audio parameters in the second profile are adjusted based on the analysis, the metadata, or a combination of the analysis and the metadata; The second audio signal is processed using the adjusted second profile; as well as The processed second audio signal, after being processed using the adjusted second profile, is sent to the one or more playback devices.

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