Methods and systems for creating a light show at a venue

Abstract

A method for controlling lighting elements in a venue based on music data is disclosed. The method includes receiving data describing a plurality of lighting elements, including originating and focus locations, and grouping the lighting elements by shared features. Music data is segmented into multiple music segments, and for each segment, a lighting effect is assigned to at least one group of lighting elements, with lighting effects varying between consecutive segments. Lighting effects may include color, intensity, motion, and rhythm. The method further includes detecting changes in musical characteristics, optionally using machine learning models, and generating a graphical user interface for visualizing and adjusting lighting effects. User input may be received to customize transitions and lighting configurations. The system controls the lighting elements in real time, synchronizing lighting with music to create an immersive experience tailored to the venue and musical performance.

Description

Docket No.: 87924.62. WOU1METHODS AND SYSTEMS FOR CREATING A LIGHT SHOW AT A VENUERELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application No. 63 / 716.440, filed November 5. 2025, the entire contents of which are incorporated herein by reference.TECHNICAL FIELD

[0002] The disclosure relates to models for mapping lighting effects to particular lighting elements in a venue.BACKGROUND OF THE INVENTION

[0003] Light shows at concerts are crafted through a combination of artistic design and advanced technology. A lighting designer collaborates with the artist and production team to align the light show with the concert’s theme, mood, and music. This involves understanding the setlist, tempo, and emotional tone of the music. Lighting designers often use 3D software to create a virtual representation of the stage, experimenting with different lighting effects and transitions to see how they will appear in the venue.

[0004] Lights are typically controlled using the DMX (Digital Multiplex) protocol, which allows for precise control over each light’s attributes, such as color, brightness, and movement. The light show is often synced to the music using time codes or MIDI (Musical Instrument Digital Interface) systems. For complex shows, lights are preprogrammed to sync with the music or video elements. This can be done using software that links lighting cues to specific moments in the performance.

[0005] In total, this process can be quite extensive and time consuming for any individual show. For artists on tour, they are performing at different venues with different layouts for lighting and staging and potentially even different setlists each night. This inefficient process must be repeated for each new venue, manually experimenting with timing and attempting to visualize how lighting effects may transition from arena to arena. Ultimately, this fully manual process requires a great deal of patience and expertise to manually program each individual lighting element for every song that a singer performs at a venue, which is only exacerbated during theDocket No.: 87924.62. WOU1 repetitive iterations of re-doing the lighting effects at different venues with different layouts.SUMMARY OF THE INVENTION

[0006] In general, the disclosure is directed to methods and systems for analyzing a layout of various lights at a venue and automatically generating lighting effects for various groups of lights in the venue. These techniques may include receiving location data for the lights and automatically creating various groups of lights, based on information such as origin location, focal location, or some other common characteristic between the lights. The system may then apply certain effects to certain groups of lights at various times. For instance, the system may analyze music data and apply various lighting effects to the various groups of lights matching certain segments of the music data. Furthermore, the lighting effects may correspond to the music segments, such as creating a visual feeling that matches the musical characteristics of the particular music segment.

[0007] By automatically grouping lighting elements and applying lighting effects to those lighting elements, a user may create a custom light show that is specific to a particular venue that matches the various segments of music data created by the system analyzing the music data. This speeds the process for creating such light shows and greatly reduces the amount of user input provided into these systems, thereby contributing to the improved durability of the computer components. Furthermore, by incorporating the specific lights at specific locations at a specific venue and applying lighting effects to those specific lights at the venue, the techniques of this disclosure integrate particular machines and other non-generic computer components that amount to practically applying any data processing technique described herein. Additionally, the analysis and segmentation techniques described herein are described in a meaningful way beyond generally linking the use of the analysis and segmentation to a particular technological environment by using this analysis specifically to develop a light show for a particular venue based on particular music data.

[0008] In one example, the disclosure is directed to a method including receiving, by one or more processors, data descriptive of a plurality of lighting elements in a venue, the data including a plurality of groups of one or more lighting elements from the plurality of lighting elements, originating location for each of the plurality of lightingDocket No.: 87924.62. WOU1 elements, and focus location for each of the plurality of lighting elements. The method further includes receiving, by the one or more processors, music data. The method also includes automatically segmenting, by the one or more processors, the music data into a plurality of music segments. The method further includes, for each of the plurality of music segments, assigning, by the one or more processors, a lighting effect to one or more of the groups of one or more lighting elements, wherein either the lighting effect or the one or more of the groups of one or more lighting elements are different for two consecutive music segments of the plurality of music segments.

[0009] In another example, the disclosure is directed to a method including receiving, by one or more processors, data descriptive of a plurality of lighting elements in a venue, the data including originating location for each of the plurality of lighting elements and focus location for each of the plurality of lighting elements. The method further includes creating, by one or more processors, a plurality of groups of one or more lighting elements, wherein each group of one or more lighting elements has a unique common feature. The method also includes assigning, by one or more processors, a lighting effect to a first group one or more lighting elements from the plurality of groups of one or more lighting elements.

[0010] In another example, the disclosure is directed to a method for performing any of the techniques of this disclosure.

[0011] In another example, the disclosure is directed to a device configured to perform any of the methods of this disclosure

[0012] In another example, the disclosure is directed to an apparatus comprising means for performing any of the method of this disclosure.

[0013] In another example, the disclosure is directed to a non-transitory computer- readable storage medium having stored thereon instructions that, when executed, cause one or more processors of a computing device to perform any of the methods of this disclosure.

[0014] In another example, the disclosure is directed to a system comprising one or more computing devices configured to perform a method of this disclosure.

[0015] In another example, the disclosure is directed to any of the techniques described herein.

[0016] The details of one or more examples of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, andDocket No.: 87924.62. WOU1 advantages of the disclosure will be apparent from the description and drawings, and from the claims.BRIEF DESCRIPTION OF DRAWINGS

[0017] The following drawings are illustrative of particular examples of the present disclosure and therefore do not limit the scope of the invention. The drawings are not necessarily to scale, though examples can include the scale illustrated, and are intended for use in conjunction with the explanations in the following detailed description wherein like reference characters denote like elements. Examples of the present disclosure will hereinafter be described in conjunction with the appended drawings.

[0018] FIG. 1 is a block diagram illustrating a lighting layout for a music venue and a computing device configured to generate and apply lighting effects to the lights in the music venue, in accordance with one or more techniques of this disclosure.

[0019] FIG. 2 is a block diagram illustrating a more detailed example of a computing device configured to perform the techniques described herein.

[0020] FIG. 3 is an example user interface illustrating various characteristics of a lighting effect that can be applied to a group of lighting elements, in accordance with one or more techniques of this disclosure.

[0021] FIG. 4 is an example user interface illustrating an example sequence of lighting effects for at least a portion of music data, in accordance with one or more techniques of this disclosure.

[0022] FIG. 5 is an example user interface illustrating example groupings of lighting elements in a venue, in accordance with one or more techniques of this disclosure.

[0023] FIG. 6 is a flow diagram illustrating an example method for creating a light show for a venue, in accordance with one or more techniques of this disclosure.

[0024] FIG. 7 is a flow diagram illustrating an example method for grouping lighting elements at a venue, in accordance with one or more techniques of this disclosure.DETAILED DESCRIPTION

[0025] The following detailed description is exemplary in nature and is not intended to limit the scope, applicability, or configuration of the techniques or systems described herein in any way. Rather, the following description provides some practical illustrations for implementing examples of the techniques or systems described herein.Docket No.: 87924.62. WOU1Those skilled in the art will recognize that many of the noted examples have a variety of suitable alternatives.

[0026] The development of light shows for music venues has traditionally been a labor- intensive and time-consuming process, requiring significant expertise and manual effort from lighting designers. These professionals are required to meticulously program individual lighting elements to align with the theme, mood, and musical characteristics of a performance. This process often involves the use of 3D software to simulate the venue layout and experiment with lighting effects, as well as syncing the light show to the music using time codes or MIDI systems. While effective, these conventional approaches are highly inefficient, particularly for artists on tour who perform at different venues with varying layouts, lighting configurations, and setlists. The repetitive nature of manually reprogramming lighting effects for each venue exacerbates the inefficiency, making it challenging to scale or adapt light shows dynamically. Furthermore, these methods lack automation and rely heavily on human input, which increases the risk of errors and limits the ability to achieve synchronization between lighting effects and musical elements.

[0027] The present disclosure addresses these limitations by introducing a system and method for automating the creation of light shows tailored to specific venues and musical performances. The described concept leverages advanced data processing techniques, including machine learning models, to analyze venue layouts and music data. By receiving data descriptive of the lighting elements in a venue, including their originating and focus locations, the system automatically groups the lighting elements based on shared characteristics, such as spatial proximity or directional focus. Additionally, the system processes music data to segment the musical content into distinct sections, detecting changes in musical characteristics such as beats-per-minute, dynamics, or instrumentation. For each musical section, the system assigns lighting effects to the predefined groups of lighting elements, ensuring that the lighting effects dynamically correspond to the musical transitions. This automated approach eliminates the need for manual programming of individual lighting elements, significantly reducing the time and expertise required to create a light show.

[0028] The solution further incorporates specialized algorithms and machine learning models to enhance the accuracy and efficiency of the process. For example, the system may use spectrogram transformations and track segmentation techniques to analyzeDocket No.: 87924.62. WOU1 individual musical tracks, enabling precise detection of transitions and musical features. The system also provides a graphical user interface (GUI) that allows users to visualize and modify lighting effects intuitively. High-level user inputs, such as natural language descriptors, can be translated into low-level lighting parameters using machine learning networks, enabling users to make adjustments without requiring technical expertise. By automating the grouping of lighting elements, the segmentation of music data, and the assignment of lighting effects, the system not only streamlines the creation of light shows but also ensures a high degree of synchronization and customization for each venue and performance. This represents a notable improvement over conventional approaches, offering scalability, adaptability, and enhanced user experience.

[0029] The techniques described herein provide several technical effects that collectively enhance the process of designing and executing light shows in music venues. By automating the receipt and analysis of data descriptive of a plurality of lighting elements, including their originating and focus locations, the system enables efficient grouping of lighting elements based on shared spatial or directional characteristics. This automation reduces the manual effort required to configure lighting setups for different venues, thereby improving scalability and adaptability' across diverse performance environments.

[0030] The techniques described herein further segment music data into distinct musical segments, utilizing advanced algorithms and, in some embodiments, machine learning models to detect changes in musical characteristics such as beats-per-minute, time signature, dynamics, and instrumentation. This segmentation allows for precise synchronization between musical transitions and lighting effects, resulting in a more immersive and responsive visual experience for audiences.

[0031] By assigning lighting effects, such as color, intensify, motion, rhythm, phase, duty cycle, and waveform characteristics, to specific groups of lighting elements for each music segment, the system ensures that lighting changes are contextually relevant and dynamically tailored to the performance. The ability to receive user input, including natural language descriptors and graphical adjustments, further empowers users to customize lighting effects intuitively, reducing the need for specialized technical knowledge and minimizing the risk of programming errors.

[0032] The generation of graphical user interfaces for visualizing and modify ing lighting effects streamlines the workflow for lighting designers and operators, enablingDocket No.: 87924.62. WOU1 real-time feedback and rapid iteration. The system’s capacity to control lighting elements in accordance with assigned effects enhances operational efficiency and reliability , while also contributing to the durability of input devices by reducing the frequency and complexity of user interactions.

[0033] Overall, the technical effects of the techniques described herein include improved automation and accuracy in light show creation, enhanced synchronization between lighting and musical elements, greater adaptability to venue-specific configurations, reduced manual programming effort, and an intuitive user interface for effect customization. These improvements collectively advance the state of the art in automated lighting control systems for live performances and entertainment venues.

[0034] The techniques described herein is directed to a specific technological solution that integrates data processing techniques with physical lighting control systems to create automated, venue-specific light shows synchronized to musical performances. The subject matter of the techniques described herein include a practical application that improves the functioning of lighting control systems and the overall experience in live entertainment environments.

[0035] The techniques described herein recites concrete steps, including receiving data descriptive of lighting elements and their locations, automatically grouping these elements based on shared features, segmenting music data using advanced algorithms and machine learning models, and assigning lighting effects to groups of lighting elements in response to detected musical transitions. These steps are performed by one or more processors and result in the real-time control of physical lighting hardware within a venue. The system further provides a graphical user interface for visualizing and adjusting lighting effects, and enables user input through both graphical and natural language modalities, which are translated into actionable lighting parameters.

[0036] By automating the analysis and configuration of lighting elements and synchronizing lighting effects with music, the invention addresses longstanding technical challenges in the field, such as the inefficiency and complexity of manual programming, the difficulty of adapting light shows to different venue layouts, and the need for precise timing between audio and visual elements. The system’s integration of machine learning models for music segmentation and effect translation further demonstrates a technical improvement over conventional approaches.Docket No.: 87924.62. WOU1

[0037] The techniques described herein is directed to a technological process that is rooted in computer and lighting control technology, produces a tangible result in the form of coordinated lighting effects, and is not merely a generic implementation of an abstract idea. The techniques described herein provide a specific and practical solution to a technical problem, resulting in improved automation, adaptability, and user experience in the creation and execution of light shows for live performances.

[0038] FIG. 1 is a block diagram illustrating system 100 that includes venue information 102, which is a lighting layout for a music venue, and computing device 110 configured to generate and apply lighting effects to lights 104 in the music venue, in accordance with one or more techniques of this disclosure.

[0039] Venue information 102 may be any data representative of a layout of lights 104 in a venue. In some instances, such as in FIG. 1, venue information may be in a schematic form (or any other graphical representation) showing a physical, scaled down representation of a location of each of lights 104. In other instances, venue information 102 may be in the form of a graph, or coordinate data (either two-dimensional or three- dimensional) that assign number values to the positions of each light in the venue. In still other instances, venue information 102 may be in the form of plain language descriptions. Ultimately, venue information 102 may be any piece of data readable by computing device 110 to adequately describe either absolute or relative positions of lights 104 within a venue (positions including both physical location and a focal point of the light) such that computing device 110 may adequately group the lights.

[0040] Lights 104 are represented by each circle in venue information 102. Lights 104 may be any electrically-powered element that can be activated, deactivated, and / or adjusted (e.g., turned on, turned off, made brighter, change colors, etc.) in order to create a lighting effect. These can include LED lights, high bay lights, PAR cans, floodlights, or any other light that can be used in an indoor or outdoor venue.

[0041] Music data 106 may be any file or set of files that can be analyzed and segmented by computing device 110. For instance, music data 106 may be a file or set of files that includes the music itself, such as a WAV file, an MP3 file, an M4A file, an MP4 file, an AAC file, a FLAC file, a PCM file, or any other file that includes audio. In other instances, music data 106 may include descriptions of the characteristics of the music, such as length, points of changes in instrumentation, dynamics, beat, or feel, or any other descriptors of the audio where a lighting effect will be applied.Docket No.: 87924.62. WOU1

[0042] Computing device 110 may be any computer with the processing power required to adequately execute the techniques described herein. For instance, computing device 110 may be any one or more of a mobile computing device (e.g., a smartphone, a tablet computer, a laptop computer, etc.), a desktop computer, a smarthome component (e.g., a computerized appliance, a home security system, a control panel for home components, a lighting system, a smart power outlet, etc ), an integrated computer system, a vehicle, a wearable computing device (e.g., a smart watch, computerized glasses, a heart monitor, a glucose monitor, smart headphones, etc.), a virtual realit / augmented reality / extended reality (VR / AR / XR) system, a video game or streaming system, a network modem, router, or server system, or any other computerized device that may be configured to perform the techniques described herein. In some examples, computing device 110 may be a standalone computing device that directly receives the venue information 102 and music data 106 and performs the analysis of this data internally. In other examples, computing device 110 may be a server device that receives the venue information 102 and music data 106 from a separate computing device and performs the analysis of this data remotely. In still other examples, computing device 110 may be a computing device that uploads venue information 102 and music data 106 to a remote server for processing.

[0043] In accordance with the techniques of this disclosure, computing device 110 may receive data descriptive of a plurality of lighting elements in a venue, such as venue information 102. The data may include an originating location for each of the plurality of lighting elements and a focus location for each of the plurality of lighting elements. Computing device 110 may create a plurality of groups of one or more lighting elements, wherein each group of one or more lighting elements has a unique common feature. Computing device 110 may assign a lighting effect to a first group one or more lighting elements from the plurality of groups of one or more lighting elements.

[0044] Also in accordance with the techniques of this disclosure, computing device 110 may receive data descriptive of a plurality of lighting elements in a venue, the data including a plurality of groups of one or more lighting elements from the plurality of lighting elements, originating location for each of the plurality' of lighting elements, and focus location for each of the plurality of lighting elements. Computing device 110 may receive music data. Computing device 110 may automatically segment the music data into a plurality of music segments. For each of the plurality of music segments,Docket No.: 87924.62. WOU1 computing device 110 may assign a lighting effect to one or more of the groups of one or more lighting elements, wherein either the lighting effect or the one or more of the groups of one or more lighting elements are different for two consecutive music segments of the plurality of music segments.

[0045] By automatically grouping lighting elements and applying lighting effects to those lighting elements, a user may create a custom light show that is specific to a particular venue that matches the various segments of music data created by the system analyzing the music data. This speeds the process for creating such light shows and greatly reduces the amount of user input provided into these systems. As input devices (e.g., a mouse, a keyboard, or a touchscreen) receive more physical interactions from users as they input indications into the system, these devices are more prone to wear- and-tear and breaking. By reducing the amount of user input provided into these systems, the techniques described herein are thereby contributing to the improved durability of the computer components. Furthermore, by incorporating the specific lights at specific locations at a specific venue and applying lighting effects to those specific lights at the venue, the techniques of this disclosure integrate particular machines and other non-generic computer components that amount to practically applying any data processing technique described herein. Additionally, the analysis and segmentation techniques described herein are described in a meaningful way beyond generally linking the use of the analysis and segmentation to a particular technological environment by using this analysis specifically to develop a light show for a particular venue based on particular music data.

[0046] The techniques described herein include a system and method for automating the creation and execution of light shows in music venues, tailored to both the physical layout of the venue and the characteristics of the musical performance. The system receives detailed data describing the location and focus of each lighting element within a venue and automatically groups these elements based on shared spatial or directional features. It further analyzes music data, segmenting the musical content into distinct segments using advanced algorithms and, in some embodiments, machine learning models to detect changes in musical characteristics such as tempo, dynamics, and instrumentation.

[0047] For each music segment, the system assigns contextually relevant lighting effects to the appropriate groups of lighting elements, ensuring that lighting transitionsDocket No.: 87924.62. WOU1 are synchronized with musical changes. The solution also provides a graphical user interface that enables users to visualize, adjust, and customize lighting effects, including the abili to input high-level descriptors in natural language, which are translated into low-level lighting parameters. This approach significantly reduces the manual effort and expertise required to design and program light shows, enhances the adaptability- of lighting configurations to different venues and performances, and improves the overall synchronization and immersive quality of live entertainment experiences.

[0048] Consider a touring music artist performing at a large indoor arena equipped with a diverse array of lighting fixtures, including spotlights. LED panels, and moving head lights positioned throughout the venue. Prior to the concert, the production team uses the disclosed system to upload a digital map of the arena, detailing the originating and focus locations of each lighting element. The system automatically analyzes this data and groups the lighting elements based on shared characteristics, such as fixtures located on the same truss, lights aimed at the stage center, or elements positioned at similar heights.

[0049] The team then uploads the setlist and corresponding music files for the performance. The system segments each song into distinct musical sections by detecting changes in tempo, rhythm, and instrumentation, utilizing machine learning models to identity- transitions and key musical features. For each segment, the system automatically assigns lighting effects, such as color changes, intensity' shifts, motion patterns, and rhythmic pulses, to the relevant groups of lighting elements, ensuring that the visual presentation dynamically matches the mood and energy of the music.

[0050] During rehearsals, the lighting designer interacts with a graphical user interface provided by the system, which displays a timeline of the music alongside the assigned lighting effects. The designer can make adjustments by selecting lighting groups and modifying effect parameters, either through direct graphical controls or by entering natural language instructions such as "‘make this section more intense7’ or '“add more blue to the chorus.” The system translates these high-level inputs into precise lighting commands, updating the shoyv configuration in real time.

[0051] On the night of the concert, the system controls the lighting elements in synchronization with the live music, automatically executing the programmed effects and transitions. The result is a highly coordinated and immersive light show that adaptsDocket No.: 87924.62. WOU1 to the unique layout of the arena and the nuances of the artist’s performance, all achieved with minimal manual programming and maximum creative flexibility.

[0052] The disclosed system is designed to scale efficiently across a wide range of venue sizes and lighting configurations, from intimate clubs to large stadiums and outdoor festivals. Its modular architecture allows for the integration of additional lighting elements and control nodes without significant reconfiguration, supporting distributed processing and networked communication among multiple devices. The system can dynamically manage hundreds or even thousands of lighting fixtures, automatically grouping and assigning effects based on real-time data and venue-specific layouts. Advanced optimization strategies ensure that lighting commands are executed with minimal latency, maintaining precise synchronization with musical segments even in complex, high-density environments. This scalability enables production teams to deploy the system in diverse settings, accommodating varying technical requirements and creative ambitions while preserving the core benefits of automation, adaptability, and user-friendly control.

[0053] FIG. 2 is a block diagram illustrating a more detailed example of a computing device configured to perform the techniques described herein. Computing device 210 of FIG. 2 is described below as an example of computing device 110 of FIG. 1. FIG. 2 illustrates only one particular example of computing device 210, and many other examples of computing device 210 may be used in other instances and may include a subset of the components included in example computing device 210 or may include additional components not shown in FIG. 2.

[0054] Computing device 210 may be any computer with the processing power required to adequately execute the techniques described herein. For instance, computing device 210 may be any one or more of a mobile computing device (e.g., a smartphone, a tablet computer, a laptop computer, etc.), a desktop computer, a smarthome component (e.g., a computerized appliance, a home security system, a control panel for home components, a lighting system, a smart power outlet, etc ), an integrated computer system, a vehicle, a wearable computing device (e.g., a smart watch, computerized glasses, a heart monitor, a glucose monitor, smart headphones, etc.), a virtual reality / augmented reality / extended reality (VR / AR / XR) system, a video game or streaming system, a network modem, router, or server system, or any other computerized device that may be configured to perform the techniques described herein.Docket No.: 87924.62. WOU1

[0055] As shown in the example of FIG. 2, computing device 210 includes user interface components (UIC) 212, one or more processors 240, one or more communication units 242, one or more input components 244, one or more output components 246, and one or more storage components 248. UIC 212 includes display component 202 and presence-sensitive input component 204. Storage components 248 of computing device 210 include communication module 220, analysis module 222, and data store 226.

[0056] One or more processors 240 may implement functionality and / or execute instructions associated with computing device 210 to automatically create or assist a user with creating a light show for a venue. That is, processors 240 may implement functionality and / or execute instructions associated with computing device 210 to analyze a layout for a venue, form groups of lights based on common characteristics of those lights in the venue, and apply lighting effects to one or more of those groups of lights based on a musical analysis performed on music data.

[0057] Examples of processors 240 include any combination of application processors, display controllers, auxiliary processors, one or more sensor hubs, and any other hardware configured to function as a processor, a processing unit, or a processing device, including dedicated graphical processing units (GPUs). Modules 220 and 222 may be operable by processors 240 to perform various actions, operations, or functions of computing device 210. For example, processors 240 of computing device 210 may retrieve and execute instructions stored by storage components 248 that cause processors 240 to perform the operations described with respect to modules 220 and 222. The instructions, when executed by processors 240, may cause computing device 210 automatically create or assist a user with creating a light show for a venue.

[0058] Communication module 220 may execute locally (e.g., at processors 240) to provide functions associated with managing a user interface, receiving venue information and music data from various data sources, and controlling lighting elements in accordance with the determined lighting effects. In some examples, communication module 220 may act as an interface to a remote service accessible to computing device 210. For example, communication module 220 may be an interface or application programming interface (API) to a remote server that manages a user interface, receives venue information and music data from various data sources, and controls lighting elements in accordance with the determined lighting effects.Docket No.: 87924.62. WOU1

[0059] In some examples, analysis module 222 may execute locally (e.g., at processors 240) to provide functions associated with analyzing venue information to determine one or more groups of lighting elements, analyzing music data to create music segments, and generating lighting effects for each of the music segments using the groups of lighting elements. In some examples, analysis module 222 may act as an interface to a remote service accessible to computing device 210. For example, analysis module 222 may be an interface or application programming interface (API) to a remote server that analyzes venue information to determine one or more groups of lighting elements, analyzes music data to create music segments, and generates lighting effects for each of the music segments using the groups of lighting elements.

[0060] One or more storage components 248 within computing device 210 may store information for processing during operation of computing device 210 (e.g., computing device 210 may store data accessed by modules 220 and 222 during execution at computing device 210). In some examples, storage component 248 is a temporary memory, meaning that a primary purpose of storage component 248 is not long-term storage. Storage components 248 on computing device 210 may be configured for short-term storage of information as volatile memory and therefore not retain stored contents if powered off. Examples of volatile memories include random access memories (RAM), dynamic random access memories (DRAM), static random access memories (SRAM), and other forms of volatile memories known in the art.

[0061] Storage components 248, in some examples, also include one or more computer- readable storage media. Storage components 248 in some examples include one or more non-transitory computer-readable storage mediums. Storage components 248 may be configured to store larger amounts of information than typically stored by volatile memory. Storage components 248 may further be configured for long-term storage of information as non-volatile memory space and retain information after power on / off cycles. Examples of non-volatile memories include magnetic hard discs, optical discs, floppy discs, flash memories, or forms of electrically programmable memories (EPROM) or electrically erasable and programmable (EEPROM) memories. Storage components 248 may store program instructions and / or information (e.g., data) associated with modules 220 and 222 and data store 226. Storage components 248 may include a memory configured to store data or other information associated with modules 220 and 222 and data store 226.Docket No.: 87924.62. WOU1

[0062] Communication channels 250 may interconnect each of the components 212, 240, 242, 244, 246, and 248 for inter-component communications (physically, communicatively, and / or operatively). In some examples, communication channels 250 may include a system bus, a network connection, an inter-process communication data structure, or any other method for communicating data.

[0063] One or more communication units 242 of computing device 210 may communicate with external devices via one or more wired and / or wireless networks by transmitting and / or receiving network signals on one or more networks. Examples of communication units 242 include a network interface card (e.g., such as an Ethernet card), an optical transceiver, a radio frequency transceiver, a GPS receiver, a radiofrequency identification (RFID) transceiver, a near-field communication (NFC) transceiver, or any other type of device that can send and / or receive information. Other examples of communication units 242 may include short wave radios, cellular data radios, wireless network radios, as well as universal serial bus (USB) controllers.

[0064] One or more input components 244 of computing device 210 may receive input. Examples of input are tactile, audio, and video input. Input components 244 of computing device 210, in one example, include a presence-sensitive input device (e.g., a touch sensitive screen, a PSD), mouse, keyboard, voice responsive system, camera, microphone or any other type of device for detecting input from a human or machine. In some examples, input components 244 may include one or more sensor components (e.g., sensors 252). Sensors 252 may include one or more biometric sensors (e.g., fingerprint sensors, retina scanners, vocal input sensors / microphones. facial recognition sensors, cameras), one or more location sensors (e.g., GPS components, Wi-Fi components, cellular components), one or more temperature sensors, one or more movement sensors (e.g., accelerometers, gyros), one or more pressure sensors (e.g., barometer), one or more ambient light sensors, and one or more other sensors (e.g.. infrared proximity sensor, hygrometer sensor, and the tike). Other sensors, to name a few other non-limiting examples, may include a radar sensor, a lidar sensor, a sonar sensor, a heart rate sensor, magnetometer, glucose sensor, ol factory sensor, compass sensor, or a step counter sensor.

[0065] One or more output components 246 of computing device 210 may generate output in a selected modality. Examples of modalities may include a tactile notification, audible notification, visual notification, machine generated voice notification, or otherDocket No.: 87924.62. WOU1 modalities. Output components 246 of computing device 210, in one example, include a presence-sensitive display, a sound card, a video graphics adapter card, a speaker, a cathode ray tube (CRT) monitor, a liquid crystal display (LCD), a light emitting diode (LED) display, an organic LED (OLED) display, a virtual / augmented / extended reality (VR / AR / XR) system, a three-dimensional display, or any other type of device for generating output to a human or machine in a selected modality.

[0066] UIC 212 of computing device 210 may include display component 202 and presence-sensitive input component 204. Display component 202 may be a screen, such as any of the displays or systems described with respect to output components 246. at which information (e.g., a visual indication) is displayed by UIC 212 while presencesensitive input component 204 may detect an object at and / or near display component 202.

[0067] While illustrated as an internal component of computing device 210, UIC 212 may also represent an external component that shares a data path with computing device 210 for transmitting and / or receiving input and output. For instance, in one example, UIC 212 represents a built-in component of computing device 210 located within and physically connected to the external packaging of computing device 210 (e g., a screen on a mobile phone). In another example, UIC 212 represents an external component of computing device 210 located outside and physically separated from the packaging or housing of computing device 210 (e.g., a monitor, a projector, etc. that shares a wired and / or wireless data path with computing device 210).

[0068] UIC 212 of computing device 210 may detect two-dimensional and / or three- dimensional gestures as input from a user of computing device 210. For instance, a sensor of UIC 212 may detect a user's movement (e.g., moving a hand, an arm, a pen, a stylus, a tactile object, etc.) within a threshold distance of the sensor of UIC 212. UIC 212 may determine a two or three-dimensional vector representation of the movement and correlate the vector representation to a gesture input (e.g., a hand- wave, a pinch, a clap, a pen stroke, etc.) that has multiple dimensions. In other words, UIC 212 can detect a multi-dimension gesture without requiring the user to gesture at or near a screen or surface at which UIC 212 outputs information for display. Instead, UIC 212 can detect a multi-dimensional gesture performed at or near a sensor which may or may not be located near the screen or surface at which UIC 212 outputs information for display.Docket No.: 87924.62. WOU1

[0069] In accordance with the techniques of this disclosure, communication module 220 may receive data descriptive of a plurality of lighting elements in a venue. The data may include a plurality of groups of one or more lighting elements from the plurality of lighting elements, an originating location for each of the plurality of lighting elements, and a focus location for each of the plurality of lighting elements. In some instances, the groups of one or more lighting elements each comprise a subset of the plurality of lighting elements with one or more of a similar origination location and a similar focus location.

[0070] Communication module 220 may receive music data. Analysis module 222 may automatically segment the music data into a plurality of music segments.

[0071] In some instances, in automatically segmenting the music data, analysis module 222 may create a timeline for the music data. Analy sis module 222 may detect a change in one or more musical characteristics in the music data at a first time. Analysis module 222 may place a transition indication in the timeline for the music data at the first time.

[0072] In some instances, in detecting the change in the one or more musical characteristics, analysis module 222 may separate, using a machine learning model, the music data into a plurality of individual tracks based on instrument type. For each of the plurality of individual tracks, analysis module 222 may transform the respective individual track into a spectrogram. Analysis module 222 may then segment, using the machine learning model, the respective individual track into a plurality of track portions. Analysis module 222 may place the transition indication between at least a first track portion and a second track portion of the plurality of track portions.

[0073] For example, the input audio may be source separated using a machine learning model trained to analyze music data into a number of individual tracks (e.g., Bass, Drum, Vocal, Other, etc.). The separated audio sources are available in the application for the operator to isolate sound sources. Each track may be transformed into a spectrogram (or a two-dimensional frequency-time vector). This data is used in the application for targeted sound-reactive lighting (e.g., ‘'This lighting effect should follow the drum track”). The analysis model operates on each spectrogram individually. The results are collated into useful data for the application. The system may then segment boundary times and labels (e.g., 'start', 'end', 'intro', 'outro', 'break', 'bridge', 'insf, 'solo', ’verse', ’chorus'). The system may also analyze beat and downbeat information, beat times, beat numbers (e.g., tapping 1,2, 3, 4), and analyze that the downbeat is beat #1.Docket No.: 87924.62. WOU1

[0074] In some instances, communication module 220 may further receive an indication of user input adjusting a transition sensitivity. When increasing the transition sensitivity, analysis module 220 may create more music segments in the plurality of music segments. Conversely, when decreasing the transition sensitivity, analysis module 220 may create fewer music segments in the plurality of music segments.

[0075] The one or more musical characteristics in the music data may include any descriptors of the audio in the music date, including any one or more of a beats-per- minute in the music data, a time signature in the music data, a feel of a sound in the music data, a key in the music data, a percussion line in the music data, a bass line in the music data, a presence of an element in the music data (e.g., a new instrument or other musical element is added to or removed from the music data), a subdrop in the music data, and a dynamic in the music data, among other things.

[0076] Analysis module 222 may for each of the plurality of music segments, assigning, by the one or more processors, a lighting effect to one or more of the groups of one or more lighting elements, wherein either the lighting effect or the one or more of the groups of one or more lighting elements are different for two consecutive music segments of the plurality of music segments. The lighting effect may include a change or application of any one or more of a light color, a light color warmth, a light intensity, a light motion effect, a light rhythm effect, a fixture phase, a group phase, a duty cycle, a light pattern, a light direction, a light frequency characteristic, a light amplitude characteristic, a floor characteristic, an offset characteristic, and a light waveform characteristic.

[0077] In some instances, in assigning the lighting effect to one or more of the groups of one or more lighting elements, analysis module 222 may analyze one or more musical characteristics of the respective segment. Analysis module 222 may create the lighting effect for the respective segment based at least in part on the one or more musical characteristics of the respective segment.

[0078] In some instances, analysis module 222 may generate a graphical user interface including at least information descriptive of a first lighting effect for a first musical segment of the plurality' of musical segments. Communication module 220 may output, to a display component (e.g., display component 202), the graphical user interface. In some instances, communication module 220 may further receive an indication of user input altering a first aspect of the first lighting effect. Analysis module 222 mayDocket No.: 87924.62. WOU1 updating, by the one or more processors, the first lighting effect to include the altered first aspect of the first lighting effect. The indication of user input may include any one or more of a natural language descriptor of an alteration for the first aspect of the first lighting effect, and a specific alteration at a graphical indication of the first aspect of the first lighting effect.

[0079] In some instances, communication module 220 may control the plurality of lighting elements at the venue according to the lighting effect for each of the plurality of music segments.

[0080] In some instances, the entirety or any part of the lighting show may be created, changed, or otherwise influenced based on natural language input. For instance, communication module 220 may receive a natural language input describing one or more details of the lighting effect (e.g., “I want this show to be heavy on light flashes and transitions'’, “Make this show have very smooth and flowing transitions’', “Edit this transition to be more dramatic”, etc.). Analysis module 222 may, accordingly, determine the lighting effect based at least in part on the natural language input.

[0081] In accordance with the techniques of this disclosure, communication module 220 may receive data descriptive of a plurality of lighting elements in a venue, the data including originating location for each of the plurality of lighting elements and focus location for each of the plurality of lighting elements. Analysis module 222 may create a plurality of groups of one or more lighting elements, wherein each group of one or more lighting elements has a unique common feature. The unique common feature may include any one or more of a similar origination location, and a similar focus location. The similar origination location may include any one or more of being on a same lighting fixture, being consecutive lighting elements in the venue, being on a same layer (e.g., interior vs. exterior of the venue), being at a similar height in the venue, being on a same pole, being on a same mounting, being a same color light, and being at a similar x-y coordinate in the venue. The similar focus location may include a lighting element being directed at a same area within the venue.

[0082] Analysis module 222 may assign a lighting effect to a first group one or more lighting elements from the plurality' of groups of one or more lighting elements.

[0083] In some instances, analysis module 222 may generate a graphical user interface including a graphical representation of the venue and a graphical representation of each lighting element in the venue. Communication module 220 may output, to displayDocket No.: 87924.62. WOU1 component 202, the graphical user interface. In some such instances, communication module 220 may receive a selection of the first group of one or more lighting elements. Analysis module 222 may update the graphical user interface to include a visual highlight of each graphical representation of a lighting element in the first group of one or more lighting elements. Communication module 220 may output, to display component 202, the updated graphical user interface.

[0084] In some instances, communication module 220 may receive an indication of user input selecting one or more lighting elements from the plurality of lighting elements. Analysis module 222 may create a custom group of lighting elements based on the selected one or more lighting elements. Analysis module 222 may include the custom group of lighting elements in the plurality of groups of one or more lighting elements.

[0085] Analysis module 222 may generate the graphical representation of each lighting element in the venue to include both a graphical representation of an origination location for each respective lighting element and a graphical representation of a focus location for each respective lighting element.

[0086] In some instances, communication module 220 may control the plurality7of lighting elements at the venue according to the lighting effect for the first group of one or more lighting elements.

[0087] FIG. 3 is an example user interface 300 illustrating various characteristics of a lighting effect that can be applied to a group of lighting elements, in accordance with one or more techniques of this disclosure. User interface 300 shows one automatically generated lighting effect for one segment of the music data. In this segment, the system (e.g., computing device 110 or computing device 210) has created this music segment that includes a four-beat measure in the music. Based on an analysis of the sound in the music data, such as determining that a drum emphasizes beats 1 and 3 in the measure, the system creates a lighting effect that shines the lights on beats 1 and 3 and ramps down the lights after an initial spike, the lights being low or off by beats 2 and 4. User interface 300 also shows various characteristics of the lighting elements during this effect, including intensity, motion, rhythm, focus, waveform, frequency, amplitude, floor, ofiset, direction, fixture phase, group phase, and duty cycle, although other instances of user interface 300 could include fewer or more lighting element and light effect characteristics.Docket No.: 87924.62. WOU1

[0088] From this user interface, a user may make edits to the computer-determined lighting effect, if desired, using a simple interface that makes the process intuitive and efficient. For instance, if the user wishes to change the duty cycle such that the effect occurs on even' beat or only once per measure, the user may interact with the sliding user interface element to adjust the duty cycle. By only having to edit a previous lighting effect rather than set every' aspect of the lighting element from scratch, the system may still reduce the number of user inputs into the system. Once the lighting effect is to the user’s liking, the system may save the characteristics of the lighting effect, assign the lighting effect to the proper group of lighting elements, and control the lighting elements according to the lighting effect when the music data is running.

[0089] Additionally or alternatively, the system may receive high level descriptor inputs into this user interface, such as natural language descriptors to make changes to sections of the show: From this input the system translates the high level descriptors to low level effect parameters. For instance, high level inputs could include "'Make this section less INTENSE”, ‘‘This effect needs more MOTION”, or “I want this to be more on the beat” (RHYTHM). The system may implement machine learning as a possible effective translation layer using a scoring function and a set of inputs. The machine learning networks may act as a translation layer, from the natural language "high level” to the wave function control ‘low level”. The system may include one small network per descriptor, the network may leam which low' level parameters to adjust to meet the desired change in high level parameter.

[0090] The system may generate scores for the terms in the high level input. The scores may show output against high level descriptors. For instance, an INTENSITY score may be calculated by changes in brightness and speed of movements. A WARMTH score may be calculated by an average color temperature. A MOTION score may be calculated by a degree of change of lights over time. A RHYTHM score may be how well aligned certain changes in the light are to the beat.

[0091] The system and the evaluation function may be spatially aware, i.e. to differentiate between the left and right of the venue, as well as be aware of the power of each light. The system may evaluate against similar descriptors as the audio inference machine learning models. Furthermore, the system may handle multiple effects at the same time, settling conflicts if trying to adjust two effects simultaneously.Docket No.: 87924.62. WOU1

[0092] This iterative loop process continues until the system determines that the light show matches desired characteristics based both on the audio analysis and the user input. The system will make changes if that determination is no, such as determining that a particular section is not as INTENSE as the audio analysis suggests.

[0093] FIG. 4 is an example user interface 400 illustrating an example sequence of lighting effects for at least a portion of music data, in accordance with one or more techniques of this disclosure. As show n in FIG. 4 and user interface 400, the system (e.g., computing device 210) determined there to be six different groups of lights in a particular venue: Four Sides, Full Pitchmap, Small Groups, Snake, Four Comers Pitchmap, and Medium Groups. Based further on an analysis of an audio data file, the system has assigned a number of lighting effects (e.g., triangle, sine, ramp down, and square) to different groups of the lights at different points during the song, transitioning between effects when the system detects there to be a shift in the overall feel of the song. From this interface, the user can cause the system to do a number of tasks, including exporting the light show to a system that is configured to control the lights at the particular venue, add a new effect at a point in the light show, split an effect (i.e., select an additional point within an effect where a new' effect will occur after such selection), or edit an effect (i.e., maintain the timing of an effect but change what lighting effect occurs during that time or characteristics of that lighting effect).

[0094] FIG. 5 is an example user interface 500 illustrating example groupings of lighting elements in a venue, in accordance with one or more techniques of this disclosure. User interface 500 includes a mapping of lights, including origination points (e.g., where the light is located within the venue) and focus point (e.g., where the light is directed to shine when illuminated). User interface 500 also includes indications of the various groups of lights determined for the venue. Selection of one of those groups may cause the system to alter user interface 500 such that lights in the selected group are visually highlighted in a distinct manner (e.g.. adding a glow effect to the lights in the group, or removing color or visual characteristics of lights not in the group). Users may also create new groups by manually selecting one or more lights within the venue and adding that selection as a new group that can be controlled by the systems and techniques described herein.

[0095] FIG. 6 is a flow' diagram illustrating an example method for creating a light show' for a venue, in accordance with one or more techniques of this disclosure. TheDocket No.: 87924.62. WOU1 techniques of FIG. 6 may be performed by one or more processors of a computing device, such as system 100 of FIG. 1 and / or computing device 210 illustrated in FIG. 2. For purposes of illustration only, the techniques of FIG. 6 are described within the context of computing device 210 of FIG. 2, although computing devices having configurations different than that of computing device 210 may perform the techniques of FIG. 6.

[0096] In accordance with the techniques of this disclosure, communication module 220 receives data descriptive of a plurality of lighting elements in a venue, the data including a plurality of groups of one or more lighting elements from the plurality of lighting elements, originating location for each of the plurality of lighting elements, and focus location for each of the plurality of lighting elements (602). Communication module 220 receives music data (604). Analysis module 222 automatically segments the music data into a plurality of music segments (606). For each of the plurality of music segments, analysis module 222 assigns a lighting effect to one or more of the groups of one or more lighting elements (608), wherein either the lighting effect or the one or more of the groups of one or more lighting elements are different for two consecutive music segments of the plurality of music segments.

[0097] FIG. 7 is a flow diagram illustrating an example method for grouping lighting elements at a venue, in accordance with one or more techniques of this disclosure. The techniques of FIG. 7 may be performed by one or more processors of a computing device, such as system 100 of FIG. 1 and / or computing device 210 illustrated in FIG. 2. For purposes of illustration only, the techniques of FIG. 7 are described within the context of computing device 210 of FIG. 2, although computing devices having configurations different than that of computing device 210 may perform the techniques of FIG. 7.

[0098] In accordance with the techniques of this disclosure, communication module 220 receives data descriptive of a plurality of lighting elements in a venue, the data including originating location for each of the plurality of lighting elements and focus location for each of the plurality of lighting elements (702). Analysis module 222 creates a plurality of groups of one or more lighting elements, wherein each group of one or more lighting elements has a unique common feature (704). Analysis module 222 assigns a lighting effect to a first group one or more lighting elements from the plurality of groups of one or more lighting elements (706).Docket No.: 87924.62. WOU1

[0099] Example 1. A method comprising: receiving, by one or more processors, data descriptive of a plurality of lighting elements in a venue, the data including a plurality of groups of one or more lighting elements from the plurality of lighting elements, originating location for each of the plurality of lighting elements, and focus location for each of the plurality of lighting elements; receiving, by the one or more processors, music data; automatically segmenting, by the one or more processors, the music data into a plurality of music segments; and for each of the plurality of music segments, assigning, by the one or more processors, a lighting effect to one or more of the groups of one or more lighting elements, wherein either the lighting effect or the one or more of the groups of one or more lighting elements are different for two consecutive music segments of the plurality of music segments.

[0100] Example 2. The method of Example 1, wherein the lighting effect comprises one or more of: a light color, a light color warmth, a light intensity, a light motion effect, a light rhythm effect, a fixture phase, a group phase, a duty cycle, a light pattern, a light direction, a light frequency characteristic, a light amplitude characteristic, a floor characteristic, an offset characteristic, and a light waveform characteristic.

[0101] Example 3. The method of any one or more of Examples 1-2, wherein automatically segmenting the music data comprises: creating, by the one or more processors, a timeline for the music data; detecting, by the one or more processors, a change in one or more musical characteristics in the music data at a first time; and placing, by the one or more processors, a transition indication in the timeline for the music data at the first time.

[0102] Example 4. The method of Example 3, further comprising: receiving, by the one or more processors, an indication of user input adjusting a transition sensitivity', wherein increasing the transition sensitivity causes the one or more processors to create more music segments in the plurality of music segments, and wherein decreasing the transition sensitivity causes the one or more processors to create fewer music segments in the plurality of music segments.

[0103] Example 5. The method of any one or more of Examples 3-4, wherein the one or more musical characteristics in the music data comprise one or more of: a beats- per-minute in the music data, a time signature in the music data, a feel of a sound in the music data, a key in the music data, a percussion line in the music data, a bass line in theDocket No.: 87924.62. WOU1 music data, a presence of an element in the music data, a subdrop in the music data, and a dynamic in the music data.

[0104] Example 6. The method of any one or more of Examples 3-5, wherein detecting the change in the one or more musical characteristics comprises: separating, by the one or more processors and using a machine learning model, the music data into a plurality of individual tracks based on instrument type; and for each of the lurality of individual tracks: transforming, by the one or more processors, the respective individual track into a spectrogram; segmenting, by the one or more processors and using the machine learning model, the respective individual track into a plurality of track portions; and placing, by the one or more processors, the transition indication between at least a first track portion and a second track portion of the plurality of track portions.

[0105] Example 7. The method of any one or more of Examples 1-6, further comprising: generating, by the one or more processors, a graphical user interface including at least information descriptive of a first lighting effect for a first musical segment of the plurality7of musical segments; and outputting, by the one or more processors and to a display component, the graphical user interface.

[0106] Example s. The method of Example 7, further comprising: receiving, by the one or more processors, an indication of user input altering a first aspect of the first lighting effect; and updating, by the one or more processors, the first lighting effect to include the altered first aspect of the first lighting effect.

[0107] Example 9. The method of Example 8, wherein the indication of user input comprises one or more of: a natural language descriptor of an alteration for the first aspect of the first lighting effect, and a specific alteration at a graphical indication of the first aspect of the first lighting effect.

[0108] Example 10. The method of any one or more of Examples 1-9, further comprising: controlling, by the one or more processors, the plurality of lighting elements at the venue according to the lighting effect for each of the plurality of music segments, wherein the groups of one or more lighting elements each comprise a subset of the plurality of lighting elements with one or more of a similar origination location and a similar focus location.

[0109] Example 11. The method of any one or more of Examples 1-10, further comprising: receiving, by the one or more processors, a natural language inputDocket No.: 87924.62. WOU1 describing one or more details of the lighting effect; and determining, by the one or more processors, the lighting effect based at least in part on the natural language input.

[0110] Example 12. The method of any one or more of Examples 1-11, wherein assigning the lighting effect to one or more of the groups of one or more lighting elements comprises: analyzing, by the one or more processors, one or more musical characteristics of the respective segment; and creating, by the one or more processors, the lighting effect for the respective segment based at least in part on the one or more musical characteristics of the respective segment.

[0111] Example 13. A method comprising: receiving, by one or more processors, data descriptive of a plurality of lighting elements in a venue, the data including originating location for each of the plurality of lighting elements and focus location for each of the plurality of lighting elements; creating, by one or more processors, a plurality of groups of one or more lighting elements, wherein each group of one or more lighting elements has a unique common feature; and assigning, by one or more processors, a lighting effect to a first group one or more lighting elements from the plurality of groups of one or more lighting elements.

[0112] Example 14. The method of Example 13, wherein the unique common feature comprises one or more of: a similar origination location, and a similar focus location.

[0113] Example 15. The method of Example 14, wherein the similar origination location comprises one or more of: being on a same lighting fixture, being consecutive lighting elements in the venue, being on a same layer, being at a similar height in the venue, being on a same pole, being on a same mounting, being a same color light, and being at a similar x-y coordinate in the venue.

[0114] Example 16. The method of any one or more of Examples 14-15, wherein the similar focus location comprises a lighting element being directed at a same area within the venue.

[0115] Example 17. The method of any one or more of Examples 13-16, further comprising: generating, by the one or more processors, a graphical user interface including a graphical representation of the venue and a graphical representation of each lighting element in the venue; outputting, by the one or more processors and to a display component, the graphical user interface; receiving, by the one or more processors, a selection of the first group of one or more lighting elements; updating, by the one or more processors, the graphical user interface to include a visual highlight of eachDocket No.: 87924.62. WOU1 graphical representation of a lighting element in the first group of one or more lighting elements; and outputting, by the one or more processors and to the display component, the updated graphical user interface.

[0116] Example 18. The method Example 17, further comprising: receiving, by the one or more processors, an indication of user input selecting one or more lighting elements from the plurality of lighting elements; creating, by the one or more processors, a custom group of lighting elements based on the selected one or more lighting elements; and including, by the one or more processors, the custom group of lighting elements in the plurality of groups of one or more lighting elements.

[0117] Example 19. The method of any one or more of Examples 17-18, further comprising: generating, by the one or more processors, the graphical representation of each lighting element in the venue to include both a graphical representation of an origination location for each respective lighting element and a graphical representation of a focus location for each respective lighting element.

[0118] Example 20. The method of any one or more of Examples 13-19, further comprising: controlling, by the one or more processors, the plurality of lighting elements at the venue according to the lighting effect for the first group of one or more lighting elements.

[0119] Example 21. A method for performing any of the techniques of any combination of Examples 1-20.

[0120] Example 22. A device configured to perform any of the methods of any combination of Examples 1-20.

[0121] Example 23. An apparatus comprising means for performing any of the method of any combination of Examples 1-20.

[0122] Example 24. A non-transitory computer-readable storage medium having stored thereon instructions that, when executed, cause one or more processors of a computing device to perform the method of Examples 1-20.

[0123] Example 25. A system comprising one or more computing devices configured to perform a method of Examples 1-20.

[0124] Example 26. Any of the techniques described herein.

[0125] Although the various examples have been described with reference to preferred implementations, persons skilled in the art will recognize that changes may be made in form and detail without departing from the spirit and scope thereof.Docket No.: 87924.62. WOU1

[0126] It is to be recognized that depending on the example, certain acts or events of any of the techniques described herein can be performed in a different sequence, may be added, merged, or left out altogether (e.g., not all described acts or events are necessary' for the practice of the techniques). Moreover, in certain examples, acts or events maybe performed concurrently, e.g., through multi -threaded processing, interrupt processing, or multiple processors, rather than sequentially.

[0127] In one or more examples, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. Computer-readable media may include computer-readable storage media, which corresponds to a tangible medium such as data storage media, or communication media including any medium that facilitates transfer of a computer program from one place to another, e.g., according to a communication protocol. In this manner, computer- readable media generally may correspond to (1) tangible computer-readable storage media which is non-transitory or (2) a communication medium such as a signal or carrier wave. Data storage media may be any available media that can be accessed by one or more computers or one or more processors to retrieve instructions, code and / or data structures for implementation of the techniques described in this disclosure. A computer program product may include a computer-readable medium.

[0128] It is contemplated that the various aspects, features, processes, and operations from the various embodiments may be used in any of the other embodiments unless expressly stated to the contrary-. Certain operations illustrated may be implemented by a computer executing a computer program product on a non-transient, computer-readable storage medium, where the computer program product includes instructions causing the computer to execute one or more of the operations, or to issue commands to other devices to execute one or more operations.

[0129] By way' of example, and not limitation, such computer-readable storage media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage, or other magnetic storage devices, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium. For example, if instructions are transmitted from aDocket No.: 87924.62. WOU1 website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. It should be understood, however, that computer-readable storage media and data storage media do not include connections, carrier waves, signals, or other transitory media, but are instead directed to non-transitory, tangible storage media. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0130] Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor,’’ as used herein may refer to any of the foregoing structures or any other structure suitable for implementation of the techniques described herein. In addition, in some aspects, the functionality described herein may be provided within dedicated hardware and / or software modules configured for encoding and decoding, or incorporated in a combined codec. Also, the techniques could be fully implemented in one or more circuits or logic elements.

[0131] The techniques of this disclosure may be implemented in a wide variety of devices or apparatuses, including a wireless handset, an integrated circuit (IC) or a set of ICs (e.g., a chip set). Various components, modules, or units are described in this disclosure to emphasize functional aspects of devices configured to perform the disclosed techniques, but do not necessarily require realization by different hardware units. Rather, as described above, various units may be combined in a codec hardware unit or provided by a collection of interoperative hardware units, including one or more processors as described above, in conjunction with suitable software and / or firmware.

[0132] Various embodiments of the invention may be implemented at least in part in any conventional computer programming language. For example, some embodiments may be implemented in a procedural programming language (e.g., “C”), or in an object oriented programming language (e.g., “C++”). Other embodiments of the invention mayDocket No.: 87924.62. WOU1 be implemented as a pre-configured, stand-alone hardware element and / or as preprogrammed hardware elements (e.g., application specific integrated circuits, FPGAs, and digital signal processors), or other related components.

[0133] Those skilled in the art should appreciate that such computer instructions can be written in a number of programming languages for use with many computer architectures or operating systems. Furthermore, such instructions may be stored in any memory device, such as semiconductor, magnetic, optical or other memory devices, and may be transmitted using any communications technology, such as optical, infrared, microwave, or other transmission technologies.

[0134] Among other ways, such a computer program product may be distributed as a removable medium with accompanying printed or electronic documentation (e.g., shrink wrapped software), preloaded with a computer system (e.g., on sy stem ROM or fixed disk), or distributed from a server or electronic bulletin board over the network (e.g., the Internet or World Wide Web). In fact, some embodiments may be implemented in a software-as-a-service model (“SAAS”) or cloud computing model. Of course, some embodiments of the invention may be implemented as a combination of both software (e.g., a computer program product) and hardware. Still other embodiments of the invention are implemented as entirely hardware, or entirely software.

[0135] While the various systems described above are separate implementations, any of the individual components, mechanisms, or devices, and related features and functionality, within the various system embodiments described in detail above can be incorporated into any of the other system embodiments herein.

[0136] The terms “abouf ’ and '‘substantially, ” as used herein, refers to variation that can occur (including in numerical quantity or structure), for example, through typical measuring techniques and equipment, with respect to any quantifiable variable, including, but not limited to, mass, volume, time, distance, wave length, frequency, voltage, current, and electromagnetic field. Further, there is certain inadvertent error and variation in the real world that is likely through differences in the manufacture, source, or precision of the components used to make the various components or cany' out the methods and the like. The terms “about"’ and “substantially” also encompass these variations. The term “about” and “substantially” can include any variation of 5% or 10%, or any amount - including any integer - between 0% and 10%. Further,Docket No.: 87924.62. WOU1 whether or not modified by the term '‘about’7or "substantially,” the claims include equivalents to the quantities or amounts.

[0137] Numeric ranges recited within the specification are inclusive of the numbers defining the range and include each integer within the defined range. Throughout this disclosure, various aspects of this disclosure are presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the disclosure. Accordingly, the description of a range should be considered to have specifically disclosed all the possible sub-ranges, fractions, and individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed sub-ranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example. 1, 2, 3, 4, 5, and 6, and decimals and fractions, for example, 1.2. 3.8, 1 ‘A, and 4% This applies regardless of the breadth of the range. Although the various embodiments have been described with reference to preferred implementations, persons skilled in the art will recognize that changes may be made in form and detail without departing from the spirit and scope thereof.

[0138] Various examples of the disclosure have been described. Any combination of the described systems, operations, or functions is contemplated. These and other examples are within the scope of the following claims.

Claims

Docket No.: 87924.

62. WOU1CLAIMS1. A method comprising: receiving, by one or more processors, data descriptive of a plurality of lighting elements in a venue, the data including a plurality of groups of one or more lighting elements from the plurality of lighting elements, originating location for each of the plurality of lighting elements, and focus location for each of the plurality of lighting elements; receiving, by the one or more processors, music data; automatically segmenting, by the one or more processors, the music data into a plurality of music segments; and for each of the plurality' of music segments, assigning, by the one or more processors, a lighting effect to one or more of the groups of one or more lighting elements, wherein either the lighting effect or the one or more of the groups of one or more lighting elements are different for two consecutive music segments of the plurality of music segments.

2. The method of claim 1, wherein the lighting effect comprises one or more of: a light color, a light color warmth, a light intensity, a light motion effect, a light rhythm effect, a fixture phase, a group phase, a duty' cycle, a light pattern, a light direction, a light frequency characteristic, a light amplitude characteristic, a floor characteristic. an offset characteristic, and a light waveform characteristic.Docket No.: 87924.

62. WOU13. The method of claim 1, wherein automatically segmenting the music data comprises: creating, by the one or more processors, a timeline for the music data: detecting, by the one or more processors, a change in one or more musical characteristics in the music data at a first time; and placing, by the one or more processors, a transition indication in the timeline for the music data at the first time.

4. The method of claim 3, further comprising: receiving, by the one or more processors, an indication of user input adjusting a transition sensitivity, wherein increasing the transition sensitivity causes the one or more processors to create more music segments in the plurality of music segments, and wherein decreasing the transition sensitivity causes the one or more processors to create fewer music segments in the plurality of music segments.

5. The method of claim 3. wherein the one or more musical characteristics in the music data comprise one or more of: a beats-per-minute in the music data, a time signature in the music data, a feel of a sound in the music data, a key in the music data, a percussion line in the music data, a bass line in the music data, a presence of an element in the music data, a subdrop in the music data, and a dynamic in the music data.Docket No.: 87924.

62. WOU16. The method of claim 3. wherein detecting the change in the one or more musical characteristics comprises: separating, by the one or more processors and using a machine learning model, the music data into a plurality of individual tracks based on instrument type; and for each of the plurality of individual tracks: transforming, by the one or more processors, the respective individual track into a spectrogram; segmenting, by the one or more processors and using the machine learning model, the respective individual track into a plurality of track portions; and placing, by the one or more processors, the transition indication between at least a first track portion and a second track portion of the plurality of track portions.

7. The method of claim 1, further comprising: generating, by the one or more processors, a graphical user interface including at least information descriptive of a first lighting effect for a first musical segment of the plurality of musical segments; and outputting, by the one or more processors and to a display component, the graphical user interface.

8. The method of claim 7, further comprising: receiving, by the one or more processors, an indication of user input altering a first aspect of the first lighting effect; and updating, by the one or more processors, the first lighting effect to include the altered first aspect of the first lighting effect.

9. The method of claim 8, wherein the indication of user input comprises one or more of: a natural language descriptor of an alteration for the first aspect of the first lighting effect, and a specific alteration at a graphical indication of the first aspect of the first lighting effect.Docket No.: 87924.

62. WOU110. The method of claim 1, further comprising: controlling, by the one or more processors, the plurality of lighting elements at the venue according to the lighting effect for each of the plurality of music segments, wherein the groups of one or more lighting elements each comprise a subset of the plurality of lighting elements with one or more of a similar origination location and a similar focus location.

11. The method of claim 1, further comprising: receiving, by the one or more processors, a natural language input describing one or more details of the lighting effect; and determining, by the one or more processors, the lighting effect based at least in part on the natural language input.

12. The method of claim 1 , wherein assigning the lighting effect to one or more of the groups of one or more lighting elements comprises: analyzing, by the one or more processors, one or more musical characteristics of the respective segment; and creating, by the one or more processors, the lighting effect for the respective segment based at least in part on the one or more musical characteristics of the respective segment.

13. A method comprising: receiving, by one or more processors, data descriptive of a plurality of lighting elements in a venue, the data including originating location for each of the plurality of lighting elements and focus location for each of the plurality of lighting elements; creating, by one or more processors, a plurality of groups of one or more lighting elements, wherein each group of one or more lighting elements has a unique common feature; and assigning, by one or more processors, a lighting effect to a first group one or more lighting elements from the plurality of groups of one or more lighting elements.Docket No.: 87924.

62. WOU114. The method of claim 13, wherein the unique common feature comprises one or more of: a similar origination location, and a similar focus location.

15. The method of claim 14, wherein the similar origination location comprises one or more of: being on a same lighting fixture, being consecutive lighting elements in the venue, being on a same layer, being at a similar height in the venue, being on a same pole, being on a same mounting, being a same color light, and being at a similar x-y coordinate in the venue.

16. The method of claim 14, wherein the similar focus location comprises a lighting element being directed at a same area within the venue.

17. The method of claim 13, further comprising: generating, by the one or more processors, a graphical user interface including a graphical representation of the venue and a graphical representation of each lighting element in the venue; outputting, by the one or more processors and to a display component, the graphical user interface. receiving, by the one or more processors, a selection of the first group of one or more lighting elements; updating, by the one or more processors, the graphical user interface to include a visual highlight of each graphical representation of a lighting element in the first group of one or more lighting elements; and outputting, by the one or more processors and to the display component, the updated graphical user interface.Docket No.: 87924.

62. WOU118. The method claim 17, further comprising: receiving, by the one or more processors, an indication of user input selecting one or more lighting elements from the plurality of lighting elements; creating, by the one or more processors, a custom group of lighting elements based on the selected one or more lighting elements; and including, by the one or more processors, the custom group of lighting elements in the plurality of groups of one or more lighting elements.

19. The method of claim 17, further comprising: generating, by the one or more processors, the graphical representation of each lighting element in the venue to include both a graphical representation of an origination location for each respective lighting element and a graphical representation of a focus location for each respective lighting element.

20. The method of claim 13, further comprising: controlling, by the one or more processors, the plurality of lighting elements at the venue according to the lighting effect for the first group of one or more lighting elements.

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