Audio playback via vehicle-integrated megaphones

Abstract

The present disclosure provides a method (300) for audio playback, the method comprising: receiving (301), at a user computing device (104), an 5 input audio (212) via a microphone (208) of the user computing device (104); processing (304) the input audio (212) using a C++ library to obtain a processed audio (214); filtering (306) the processed audio (214) to obtain a noise-filtered audio; performing (308) voice modulation on the noise filtered audio to obtain a modulated audio; compressing (310) the 10 modulated audio (218) to obtain an output audio; and transmitting (312) the output audio (220) to a vehicle (102) for playback by a megaphone integrated with the vehicle (102).

Description

AUDIO PLAYBACK VIA VEHICLE-INTEGRATED MEGAPHONESTECHNICAL FIELD

[0001] The present invention, in general, relates to audio devices installed in a vehicle and, more specifically, to audio processing techniques for vehicle-integrated megaphones.BACKGROUND

[0002] In vehicles, speakers are primarily used for playing music, providing navigation instructions, and delivering important audio alerts to the driver. The speakers are typically a part of a vehicle's built-in audio system, allowing occupants to enjoy entertainment, receive information, and stay aware of vehicle status through audible cues.

[0003] The audio playback functionality in vehicles has become increasingly sophisticated over time, with modem audio systems offering high-quality sound reproduction, multiple speaker configurations, and integration with various media sources. These built-in audio systems significantly enhance the driving experience, providing both entertainment and practical auditory information to vehicle occupants.BRIEF DESCRIPTION OF DRAWINGS

[0004] The detailed description is provided with reference to the accompanying figures, wherein:

[0005] FIG. 1 illustrates an exemplary environment depicting a user computing device of a user in communication with a vehicle to playback audio from a megaphone, in accordance with one implementation of the present subject matter;

[0006] FIG. 2 illustrates a detailed block diagram depicting components comprised in a user computing device, in accordance with one implementation of the present subject matter; and

[0007] FIG. 3 illustrates an exemplary method for processing and transmitting an audio to a vehicle to be played back from a megaphone integrated within the vehicle, in accordance with one implementation of the present subject matter.

[0008] FIG. 4 illustrates a method for processing and transmitting an audio to a vehicle for playback by a megaphone integrated within the vehicle, in accordance with another implementation of the present subject matter.

[0009] Throughout the drawings, identical reference numbers designate similar, but not necessarily identical, elements. The figures are not necessarily to scale, and the size of some parts may be exaggerated to more clearly illustrate the example shown. Moreover, the drawings provide examples and / or implementations consistent with the description; however, the description is not limited to the examples and / or implementations provided in the drawings.DETAILED DESCRIPTION

[0010] Communication in noisy or crowded environments has long been a challenge, particularly in situations where clear and loud voice projection is crucial. This problem is especially relevant in the context of personal transportation vehicles like electric scooters, where riders often need to communicate with others in various outdoor settings. Currently, electric scooters are equipped with speakers primarily designed for playing music or providing audio notifications. While these speakers serve their intended purpose, they fall short when it comes to facilitating direct voice communication from the rider to the surrounding environment. This limitation becomes apparent in several scenarios, such as emergency situations, event management, tour guiding, and delivery services.

[0011] The existing speaker systems on electric scooters are not optimized for voice amplification and lack the necessary features to effectively project a rider's voice. Additionally, these systems do not offerany voice modulation capabilities, which could be useful for creating attention-grabbing announcements or adding an element of fun to the communication. Furthermore, traditional audio systems often suffer from lag and syncing issues, particularly when processing and transmitting audio in real-time, which can lead to disjointed or unclear communication.

[0012] Current solutions often involve carrying separate, bulky megaphone devices, which are inconvenient, require separate power sources, and detract from the sleek, minimalist design of modern electric scooters. There is a need for an integrated solution that can leverage the existing speaker hardware on electric scooters to provide effective voice amplification and modulation capabilities. Such a solution would need to address several technical challenges, including minimizing latency in audio processing and transmission, implementing effective noise cancellation, developing efficient voice modulation algorithms, and ensuring seamless integration with the scooter's existing Bluetooth audio system. By addressing these technical problems, a solution that turns an electric scooter into a mobile megaphone is required to significantly enhance the utility and versatility of these vehicles, for improving the overall user experience.

[0013] Approaches for audio playback via a vehicle-integrated megaphone through real-time processing and transmission of input audio from a user computing device are described. The processed audio may be used to enhance communication effectiveness while operating the vehicle. The voice-based communication between the user computer device and the vehicle may be implemented through the user computing device executing a communication application, such as a voice processing and transmission application. Examples of such user computing devices include, but are not limited to, smartphones, tablet PCs, and wearable computing devices. The user computing device may be further communicatively coupled to a vehicle-integrated human machine interface and / or the megaphone.

[0014] The user computing device, in one example, may enhance the input audio based on processing techniques. In operation, during a voicebased communication session, e.g., during vehicle operation or public address, the driver may be operating the vehicle equipped with the integrated megaphone. The user computing device may be wirelessly coupled to the vehicle's human machine interface of the vehicle on which the audio processing and transmission may occur. The user computing device captures the audio input through its microphone and processes it in real-time.

[0015] In an example, the user computing device may process the input audio using a C++ library for efficient audio handling. This library is chosen for its efficiency in handling audio data with minimal latency. The processing may include initial audio format conversion, sample rate adjustment, and preliminary noise reduction. The C++ library likely employs fast Fourier transforms (FFTs) and other digital signal processing algorithms to manipulate the audio data efficiently.

[0016] Thereafter, building on the initial processing, the processed audio is filtered to reduce background noise, or it may be called as noise cancellation. In an example, noise cancellation methods such as spectral subtraction may be employed, where the estimated frequency spectrum of background noise is subtracted from the input audio. In another example, adaptive noise cancellation algorithms may be used to dynamically adjust to changing noise conditions as the vehicle moves. Further, multi-band noise gating may be applied, dividing the audio spectrum into frequency bands and selectively reducing noise in each band. The result is filtered audio, with significantly reduced background noise and improved clarity.

[0017] Continued further, the user computing device performs voice modulation onto the filtered audio to obtain a modulated audio. In an example, the user computing device applies various voice modulation effects to the filtered audio. For example, pitch shifting may be carried out for effect like “CHIPMUNK” (increasing pitch) or “DEEP” (decreasing pitch)voices. In another example, frequency modulation may be performed for the “HELIUM” effect, altering the frequency components of the audio. Further, harmonica enhancement may be performed for the “DEVIL” voice, adding or amplifying specific harmonics. These modulations are achieved through digital signal processing techniques, such as phase vocoding and waveform manipulation, resulting in modulated audio.

[0018] Once the audio is processed or the modulated audio is obtained, the user's computing device compresses the audio data. This compression is crucial for reducing latency and ensuring real-time audio playback, which is essential for effective communication in moving vehicles. The compressed, processed audio is then transmitted to the vehicle's human machine interface (HMI).

[0019] The HMI, upon receiving the compressed audio, performs additional processing. This includes decompression of the received audio and any necessary adjustments to optimize the sound for the specific megaphone hardware installed on the vehicle. In an example, the HMI acts as an intermediary between the user's computing device and the megaphone. After the HMI processes the audio, it transmits the fully processed audio to the megaphone for playback. The megaphone, which is mounted on the vehicle, then amplifies and broadcasts the audio, projecting the user's voice or chosen audio effect into the surrounding environment.

[0020] The present subject matter is designed to be versatile and may be integrated into various types of vehicles, from personal transportation devices like scooters to larger vehicles. It provides users with a powerful tool for communication, whether it's for making announcements, communicating with pedestrians, or interacting with other vehicles on the road.

[0021] The present disclosure provides an advancement over the existing technology by introducing a real-time audio processing and transmission system that integrates seamlessly with a vehicle-mounted megaphone. This approach enables clear, lag-free voice amplification andcustomization in various environments. By processing input audio on a user computing device before transmission, the system can apply noise filtering, voice modulation, and compression techniques, offering a more versatile and responsive communication experience. The continuous processing and real-time transmission of audio data allow for rapid adaptation to changing acoustic conditions, enhancing both clarity and range of communication.

[0022] The manner in which the user computing device is implemented to communicate with other parts of the vehicle to play back an input audio via a megaphone is explained in detail with respect to FIGS. 1 -3. While aspects of the described user computing device may be implemented in any number of different electronic devices, environments, and / or implementation, the examples are described in the context of the following example device(s). It may be noted that drawings of the present subject matter shown here are for illustrative purposes and are not to be construed as limiting the scope of the subject matter claimed.

[0023] FIG. 1 illustrates an environment 100 depicting a vehicle 102 that may be moving on a road while traveling from location 1 to location 2. In such traveling situations, circumstances may arise where the user may want to communicate messages to other drivers or pedestrians. For example, the user may need to alert pedestrians of the vehicle's approach in a crowded area, inform other drivers of a hazard on the road, request right-of-way in an emergency situation, or provide directions to passengers or bystanders. Such circumstances may arise not only when the vehicle is operating in a drive mode but also when it may be operating in a park mode. For instance, the user may need to communicate during certain other circumstances, such as when making deliveries, during public events, or in emergency response scenarios. A megaphone system integrated with the vehicle 102, also referred to as an integrated megaphone system, in accordance with example embodiments of the present subject matter allows for clear, amplified communication in these various situations while the user remains focused on operating the vehicle.

[0024] In one such scenario, the user interacts with a user computing device 104 which is accessible by the user while operating the vehicle 102. In an example, the driver uses a user interface 106 to interact with the user computing device 104. For example, the user taps on a megaphone icon displayed on the user interface 106 to initiate the megaphone-related user interface as depicted in FIG. 1 . This action brings up a screen with various voice filter options such as "CHIPMUNK," "DEVIL," "HELIUM," and "DEEP." Once the megaphone feature is activated and a voice filter option is selected, the user provides an input audio via a microphone integrated into the user's computing device 104. This input audio may be the user's voice or any other sound the driver wishes to amplify through the megaphone.

[0025] Once the audio is received, the user computing device 104 then processes the input audio using various techniques to obtain output audio. These may include processing based on a C++ library to reduce lag / increase syncing of the audio, noise filtering to remove background noise, voice modulation to apply the selected voice filter effect, and compression of the audio data. These processing steps are performed to reduce lag in the audio transmission and ensure that the audio may be played back in real-time through the megaphone. These processing techniques are explained in detail in conjunction with FIG. 2.

[0026] The user computing device 104 then transmits the output audio to the vehicle 102 for playback. In an example, a vehicle integrated human machine interface (HMI) 108 of the vehicle 102 receives the processed output audio from the user computing device 104. Upon receiving the output audio, the HMI 108 further processes the audio. This processing may include decompressing the output audio and preparing it for playback through a megaphone 110 of the megaphone system integrated with vehicle 102. The HMI 108 may also adjust various parameters of the megaphone 110 before playback to optimize the audio for the specific megaphone hardware installed on the vehicle 102.

[0027] In an example, the HMI 108 of vehicle 102 may be understood as the electronic dashboard of vehicle 102, such as an electric vehicle. The electric vehicle's electronic dashboard may be any central digital system that controls the functions of the electric vehicle. The electric vehicle's electronic dashboard integrates a range of components such as touch screens and dashboards, audio systems, voice recognition technologies, and connectivity features like Bluetooth and Wi-Fi. As will be apparent to one skilled in the art, primary components of an electronic dashboard in electric vehicles include both hardware and software elements that provide information, entertainment, and vehicle management. Such components are hardware components, such as input / output devices, display units, and processing units. Input devices like touchscreens, keyboards, and buttons allow users to interact with the HMI by providing commands or making selections. Output devices such as monitors, LED displays, and speakers provide visual or auditory feedback to the user. The processing unit, which can be an embedded processor, is responsible for processing user inputs, executing software applications, and managing communication with the dashboard.

[0028] In an example implementation of the present subject matter, the human machine interface referred to herein as HMI, comprises a user interface that allows the user computing device 104 to communicate with the electric vehicle 102 via its graphical interface (typically a touchscreen). It facilitates communication and interaction between the user computing device 104 and the electric vehicle 102 and may monitor, control, and manipulate various aspects of the megaphone 110 installed on the vehicle 102 through graphical representations, buttons, switches, and other input / output devices. In accordance with example embodiments of the present subject matter, HMI 108 consists of various components for facilitating post-processing operations (as explained below in reference to Figures 3 and 4) on the output audio.

[0029] In an example, the megaphone 110 may include one or more speakers capable of projecting audio at high volumes over long distances. The speaker(s) may utilize various technologies such as compression drivers, horn-loaded tweeters, or piezoelectric transducers to efficiently convert electrical signals into sound waves. The megaphone 110 may also incorporate a power amplifier to boost the audio signal, ensuring sufficient volume output. It may feature adjustable components like a rotatable horn or adjustable mouth for directing sound and could include built-in digital signal processing (DSP) capabilities for real-time audio enhancement. The megaphone 110 may be designed with weather-resistant materials to withstand various environmental conditions encountered during vehicle operation. Additionally, it may include interface components for receiving audio and control signals from the HMI 108, such as wired or wireless connectivity options, allowing seamless integration with the vehicle's audio system.

[0030] In operation, the HMI 108 transmits the prepared audio to the megaphone 110 for playback. The megaphone 110, mounted on the vehicle 102, then amplifies and broadcasts the audio, allowing the users processed voice or chosen audio to be heard in the surrounding environment 100 (The manner in which the user computing device 104 process input audio and transmit it to the megaphone 110 for playback is further described in conjunction with FIG. 2).

[0031] FIG. 2 illustrates a block diagram depicting various components of a user computing device, such as user computing device 104, which is in communication with a human machine interface of a vehicle, such as vehicle 102, for processing and transmitting driver’s audio for playback via a megaphone. The user computing device 104 may include a processor 202, interface(s) 204, a memory(s) 206, a microphone(s) 208, and a data 210. The processor 202 may be implemented as microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and / or other devices thatmanipulate signals based on operational instructions. The interface(s) 204 may allow the connection or coupling of the user computing device 104 with one or more other devices, through a wired (e.g., Local Area Network, i.e. , LAN) connection or through a wireless connection (e.g., Bluetooth®, Wi-Fi). The interface(s) 204 may also enable intercommunication between different logical as well as hardware components of the user computing device 104.

[0032] The memory(s) 206 may be a computer-readable medium, examples of which include volatile memory (e.g., RAM), and / or non-volatile memory (e.g., Erasable Programmable read-only memory, i.e., EPROM, flash memory, etc.). The memory(s) 206 may be an external memory, or internal memory, such as a flash drive, a compact disk drive, an external hard disk drive, or the like. The memory(s) 206 may further include data which either may be utilized or generated during the operation of the user computing device 104.

[0033] The microphone(s) 208 may be an audio input device capable of converting sound waves into electrical signals. Examples of microphone types may include dynamic microphones, condenser microphones, MEMS (Micro-Electro-Mechanical Systems) microphones, or piezoelectric microphones. The microphone(s) 208 may be an external microphone connected via an audio jack, a USB port, or wirelessly through Bluetooth, or an internal microphone integrated into the user computing device 104. The microphone(s) 208 may feature various pickup patterns such as omnidirectional, cardioid, or bidirectional to optimize voice capture in different environments. It may incorporate noise-cancellation technology or wind screens to improve audio quality in vehicle settings. The microphone(s) 208 may further include pre-amplification circuitry and analog-to-digital converters to prepare the audio signal for processing by the user computing device 104.

[0034] It may be noted that the user computing device 104 may further include specific engines, such as processing engine 226, transmission engine 228, or any other engines 230 for performing operations which havebeen described as being performed by the processor 102 in the below description without deviating from the scope of the present subject matter.

[0035] The engine(s) 224 may be implemented as a combination of hardware and programming, for example, programmable instructions to implement a variety of functionalities of the engine(s) 224. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the engine(s) 224 may be executable instructions. Such instructions may be stored on a non-transitory machine-readable storage medium, which may be coupled either directly with the user computing device 104 or indirectly (for example, through networked means). In an example, the engine(s) 224 may include a processing resource, for example, either a single processor or a combination of multiple processors, to execute such instructions. In the present examples, the non-transitory machine-readable storage medium may store instructions that, when executed by the processing resource, implement engine(s) 224. In other examples, the engine(s) 224 may be implemented as electronic circuitry.

[0036] The engine(s) 224 includes a processing engine 226, transmission engine(s) 228, and other engine(s) 230. The other engine(s) 230 may further implement functionalities that supplement functions performed by the user computing device 104 or any of the engine(s) 224. The data 210, on the other hand, includes data that is either stored or generated as a result of functions implemented by any of the engine(s) 224 or the user computing device 104. It may be further noted that information stored and available in data 210 may be utilized by the engine(s) 224 for performing various functions to be implemented by the user computing device 104. In an example, data 210 may include an input audio 212, a processed audio 214, a filtered audio 216, a modulated audio 218, an output audio 220, and other data 222. It may be noted that such examples of the various functional blocks as depicted in FIG. 2 are indicative. The presentapproaches may be applicable to other examples without deviating from the scope of the present subject matter.

[0037] In operation, when the user activates the megaphone function via the user interface 108 (as depicted in FIG. 1 ), the processing engine 226, via microphone(s) 208, starts receiving input audio 212 from the user.

[0038] The megaphone function may be understood as a mobile application or a built-in functionality, or a program that is integrated within a vehicle app installed on a user computing device 104. As will be known to one skilled in the art, several smartphone applications integrate with twowheeled vehicles’ dashboards to provide enhanced connectivity, navigation, and control, allowing riders to interact with their vehicle safely and conveniently while riding. These apps typically use Bluetooth Low Energy (BLE) or other wireless protocols to integrate the smartphone with the vehicle's onboard systems, showing data directly on the dashboard display and enabling hands-free control for navigation, calls, messages, and media. The vehicle app may be understood to be such an application.

[0039] The megaphone function may be available when the user navigates or accesses the vehicle app installed on the user's computing device. The megaphone function may be activated when the user taps on the megaphone function during execution of the vehicle app on the user computing device 104. The megaphone functionality, which is part of a vehicle app, may be designed to allow a user — typically the driver or passenger — to broadcast audio through the vehicle’s external speakers, typically a megaphone speaker, in real time. The megaphone function allows the microphone of the user's computing device 104 to pick up sound and play it loudly through the connected external speakers, such as the megaphone speaker 110 integrated in the vehicle. The megaphone function of the vehicle app also allows streaming a user’s voice to Bluetooth speakers or external wired speakers connected to the vehicle for louder, clearer sound, as will be elaborated subsequently.

[0040] In an example, once the megaphone function of the vehicle apps may be activated, the microphone(s) 208 begin capturing audio in real-time, converting the user’s voice or audio into electrical signals. The microphone(s) 208 may utilize advanced technologies like MEMS or electret condenser microphones, optimized for noisy vehicle environments. It may also incorporate features such as directional pickup patterns, automatic gain control, wind noise reduction, and shock mounting to enhance initial audio quality. For example, a food delivery scooter driver might activate the megaphone function via user interface 108 and say, "Hello, your food delivery has arrived. I'm parked outside your building." This audio input is then captured by the microphone(s) 208.

[0041] Once the input audio 212 is captured by the microphone(s) 208, the processing engine 226 processes the input audio 212 using a C++ library to obtain the processed audio 214. In an example, the processor 202 employs a specialized C++ library optimized for real-time audio processing. This library utilizes efficient algorithms such as Fast Fourier Transforms (FFTs) and other digital signal processing techniques to manipulate the audio data with minimal latency. Additionally, the implementation includes OpenMP optimizations, which parallelize computational tasks across multiple CPU cores, significantly reducing processing time and ensuring seamless real-time audio transmission.

[0042] This processing may include initial audio format conversion, adjusting the sample rate to match system requirements, and applying preliminary noise reduction. The C++ library may also perform audio normalization to ensure consistent volume levels and implement basic equalization to enhance voice clarity. This initial processing stage prepares the audio for more advanced filtering and modulation in subsequent steps, striking a balance between audio quality improvement and computational efficiency to maintain real-time performance.

[0043] Continuing further, the processing engine 226 filters the processed audio 214 to obtain filtered audio 216. In an example, theprocessor 202 applies advanced noise reduction algorithms to the processed audio 214 to produce filtered audio 216. These algorithms may employ techniques such as spectral subtraction, adaptive filtering, or machine learning-based noise suppression to isolate and enhance the driver's voice while minimizing unwanted background noise. The filtering process likely targets common vehicle-related noises such as wind, engine sounds, road noise, and ambient urban environments. It may utilize realtime analysis of the audio spectrum to identify and suppress non-voice frequencies, while preserving the clarity and intelligibility of the driver's speech. The processor 202 may also adapt its filtering parameters based on the current vehicle speed, detected ambient noise levels, or user-defined settings.

[0044] Once the noise filtering is done, the processing engine 226 performs voice modulation of the filtered audio 216 to obtain modulated audio 218. In an example, the processor 202 applies various audio effects to the filtered audio 216 to create modulated audio 218. The modulation may include pitch shifting, formant adjustment, or application of audio filters to alter the characteristics of the driver's voice. For example, the processor 202 may offer preset voice effects like "chipmunk," "robot," or "deep voice," which modify the audio's frequency components in real-time. In an example, the desired modulation effect to be performed is provided by the user by tapping on one of the options displayed on the user interface 108. More advanced modulation may involve dynamic effects that respond to the audio input's characteristics, such as auto-tune or harmonization. The resulting modulated audio 218 provides an enhanced or altered version of the user's voice, potentially improving audibility, adding entertainment value, or creating a specific auditory persona for the vehicle operator.

[0045] In an example, thereafter, the processing engine 226 compresses the modulated audio 218 to obtain an output audio 220 to be transmitted to the HM1 108 of the vehicle 102. In an example, the processing engine 226 applies audio compression algorithms to the modulated audio218 to create output audio 220. The compression process likely utilizes codecs optimized for voice transmission, such as Opus, AMR-WB, or a proprietary algorithm tailored for this application. The goal is to reduce the data size of the audio stream while maintaining voice quality and minimizing latency. This compression may involve techniques like perceptual coding, which removes audio information less perceptible to human ears, or lossy compression that balances audio fidelity with data reduction.

[0046] Once the output audio 220 is obtained, the transmission engine 228 transmits the output audio 220 to the HMI 108 of the vehicle 102 for further processing and playback via the megaphone 110. In an example, the user computing device 104 sends the compressed output audio 220 to the HM1 108 of the vehicle 102 through the interface 204. This transmission likely utilizes a wireless communication protocol such as Bluetooth, Wi-Fi, or a proprietary short-range wireless technology optimized for low-latency audio streaming. The user computing device 104 may employ error correction and packet loss concealment techniques to ensure reliable audio delivery, even in environments with potential electromagnetic interference. This step may also involve handshaking between the user computing device 104 and the HMI 108 to confirm successful receipt of the audio data, ensuring seamless integration between the two components.

[0047] Once the output audio 220 is received, the HMI 108 decompresses the received output audio 220 to obtain an unpacked audio. In an example, a processor or a control unit (not shown in FIG. 2) integrated within the HMI 108 applies decompression algorithms to the output audio 220, reversing the compression process performed earlier by the user computing device 104 to produce unpacked audio. The decompression likely utilizes the same codec used for compression, such as Opus or AMR- WB, to accurately reconstruct the audio signal. This process may involve techniques like entropy decoding, inverse quantization, and spectral reconstruction to restore the full frequency range and dynamic characteristics of the original modulated audio. The decompressionalgorithm may also incorporate error concealment techniques to mitigate any data loss or corruption that occurred during transmission. Additionally, the HMI 108 may perform a quick analysis of the unpacked audio to verify its integrity and make any necessary adjustments to volume levels or equalization to optimize it for the specific megaphone hardware.

[0048] Thereafter, the HMI 108 adjusts the parameters of the megaphone 110 to play back the unpacked audio. In an example, the HMI 108 configures the megaphone 110 for optimal audio output based on the characteristics of the unpacked audio. This may include setting the appropriate gain levels to ensure the audio is loud enough without causing distortion or feedback. The HMI 108 via its control unit may analyze the frequency content of the unpacked audio and adjust the megaphone's equalization settings to enhance clarity and intelligibility, especially for voice frequencies. It may also apply dynamic range compression to maintain consistent volume levels across varying input signals. In one example, the HMI adjusts parameters such as directionality, beamforming, or coverage angle of the megaphone 110 based on the vehicle's current speed, ambient noise levels, or user preferences. Additionally, the HMI 108 may synchronize the audio playback with other vehicle systems, such as lights or displays, for coordinated messaging.

[0049] Once the megaphone configuration is done, the HMI 108 transmits the unpacked audio to the megaphone 110 for playback. In an example, the HMI 108 sends the processed and optimized unpacked audio to the megaphone 110 through an interface (not shown in FIG. 2). This transmission likely occurs via a digital audio interface such as I2S (Inter-IC Sound) or a high-speed serial connection, ensuring minimal latency and high-quality audio transfer. The HMI 108 may synchronize the audio transmission with a clock signal to maintain precise timing and prevent audio artifacts. As the audio is streamed to the megaphone 110, the HMI may continuously monitor the audio output for any issues like clipping or distortion, making real-time adjustments as necessary.

[0050] FIG. 3 illustrates an example method 300 for processing and transmitting an audio to a vehicle to be played back from a megaphone integrated within the vehicle, in accordance with examples of the present subject matter. The order in which the above-mentioned methods are described is not intended to be construed as a limitation, and some of the described method blocks may be combined in a different order to implement the methods, or an alternative method.

[0051] Furthermore, the above-mentioned methods may be implemented in suitable hardware, computer-readable instructions, or a combination thereof. The steps of such methods may be performed by either a system under the instruction of machine executable instructions stored on a non-transitory computer-readable medium or by dedicated hardware circuits, microcontrollers, or logic circuits. For example, the methods may be performed by a user computing device, such as user computing device 104, and a human machine interface, such as HMI 108 of the vehicle 102. Herein, some examples are also intended to cover non- transitory computer-readable medium, for example, digital data storage media, which are computer-readable and encode computer-executable instructions, where said instructions perform some or all the steps of the above-mentioned methods.

[0052] In an example, the method 300 may be implemented by the user computing device 104 till step 312 for capturing the user's audio and processing it to generate output audio, and then by the HMI 108 from step 314 to 318 for playback of the output audio via the megaphone 110. At block 302, an input audio generated by a user is received by a user computing device via a microphone. In an example, the processor 202, via microphone(s) 208, starts receiving input audio 212 from the user. In an example, the microphone(s) 208 begin capturing audio in real-time, converting the driver’s voice into electrical signals. The microphone(s) 208 may utilize advanced technologies like MEMS or electret condenser microphones, optimized for noisy vehicle environments. It may alsoincorporate features such as directional pickup patterns, automatic gain control, wind noise reduction, and shock mounting to enhance initial audio quality. For example, a food delivery scooter driver might activate the megaphone function via user interface 108 and say, "Hello, your food delivery has arrived. I'm parked outside your building." This audio input is then captured by the microphone(s) 208.

[0053] At block 304, the input audio is processed using a C++ library to obtain processed audio. In an example, the processor 202 employs a specialized C++ library optimized for real-time audio processing. This library utilizes efficient algorithms such as Fast Fourier Transforms (FFTs) and other digital signal processing techniques to manipulate the audio data with minimal latency. The processing may include initial audio format conversion, adjusting the sample rate to match system requirements, and applying preliminary noise reduction. The C++ library may also perform audio normalization to ensure consistent volume levels and implement basic equalization to enhance voice clarity. This initial processing stage prepares the audio for more advanced filtering and modulation in subsequent steps, striking a balance between audio quality improvement and computational efficiency to maintain real-time performance.

[0054] At block 306, the processed audio is filtered to obtain a noise- filtered audio. In an example, the processor 202 applies advanced noise reduction algorithms to the processed audio 214 to produce filtered audio 216. These algorithms may employ techniques such as spectral subtraction, adaptive filtering, or machine learning-based noise suppression to isolate and enhance the user’s voice while minimizing unwanted background noise. The filtering process likely targets common vehicle-related noises such as wind, engine sounds, road noise, and ambient urban environments. It may utilize real-time analysis of the audio spectrum to identify and suppress nonvoice frequencies, while preserving the clarity and intelligibility of the driver's speech. The processor 202 may also adapt its filtering parameters basedon the current vehicle speed, detected ambient noise levels, or user-defined settings.

[0055] At block 308, voice modulation is performed on the filtered audio to obtain a modulated audio. In an example, processor 202 applies various audio effects to the filtered audio 216 to create modulated audio 218. The modulation may include pitch shifting, formant adjustment, or application of audio filters to alter the characteristics of the user's voice. For example, the processor 202 may offer preset voice effects like "chipmunk," "robot," or "deep voice," which modify the audio's frequency components in real-time. In an example, the desired modulation effect to be performed is provided by the driver by tapping on one of the options displayed on the user interface 108. More advanced modulation may involve dynamic effects that respond to the audio input's characteristics, such as auto-tune or harmonization. The resulting modulated audio 218 provides an enhanced or altered version of the driver's voice, potentially improving audibility, adding entertainment value, or creating a specific auditory persona for the vehicle operator.

[0056] At block 310, the modulated audio is then compressed to obtain an output audio which is to be transmitted to a human machine interface of a vehicle for playback. In an example, processor 202 applies audio compression algorithms to the modulated audio 218 to create output audio 220. The compression process likely utilizes codecs optimized for voice transmission, such as Opus, AMR-WB, or a proprietary algorithm tailored for this application. The goal is to reduce the data size of the audio stream while maintaining voice quality and minimizing latency. This compression may involve techniques like perceptual coding, which removes audio information less perceptible to human ears, or lossy compression that balances audio fidelity with data reduction.

[0057] At block 312, the output audio is transmitted to the human machine interface for playback via a megaphone integrated onto a vehicle. In an example, the processor 202 transmits the output audio 220 to the HMI 108 of the vehicle 102 for further processing and playback via themegaphone 110. In an example, the user computing device 104 sends the compressed output audio 220 to the HMI 108 of the vehicle 102 through the interface 204. This transmission likely utilizes a wireless communication protocol such as Bluetooth, Wi-Fi, or a proprietary short-range wireless technology optimized for low-latency audio streaming. The user computing device 104 may employ error correction and packet loss concealment techniques to ensure reliable audio delivery, even in environments with potential electromagnetic interference. This step may also involve handshaking between the user computing device 104 and the HMI 108 to confirm successful receipt of the audio data, ensuring seamless integration between the two components. The method steps from 314 to 318 will be performed by the HMI 108.

[0058] At block 314, the output audio is decompressed by the HMI to obtain unpacked audio. In an example, a processor or a control unit (not shown in FIG. 2) integrated within the HMI 108 applies decompression algorithms to the output audio 220, reversing the compression process performed earlier by the user computing device 104 to produce unpacked audio. The decompression likely utilizes the same codec used for compression, such as Opus or AMR-WB, to accurately reconstruct the audio signal.,

[0059] At block 316, a plurality of parameters of the megaphone are adjusted for efficient playback of the audio. In an example, the HMI 108 configures the megaphone 110 for optimal audio output based on the characteristics of the unpacked audio. This may include setting the appropriate gain levels to ensure the audio is loud enough without causing distortion or feedback. The HMI 108 via its control unit may analyze the frequency content of the unpacked audio and adjust the megaphone's equalization settings to enhance clarity and intelligibility, especially for voice frequencies. It may also apply dynamic range compression to maintain consistent volume levels across varying input signals. In one example, the HMI adjusts parameters such as directionality, beamforming, or coverageangle of the megaphone 110 based on the vehicle's current speed, ambient noise levels, or user preferences. Additionally, the HMI 108 may synchronize the audio playback with other vehicle systems, such as lights or displays, for coordinated messaging.

[0060] At block 318, the unpacked audio is transmitted to the megaphone for playback. In an example, the HMI 108 sends the processed and optimized unpacked audio to the megaphone 110 through an interface (not shown in FIG. 2). This transmission likely occurs via a digital audio interface such as I2S (Inter-IC Sound) or a high-speed serial connection, ensuring minimal latency and high-quality audio transfer. The HMI 108 may synchronize the audio transmission with a clock signal to maintain precise timing and prevent audio artifacts. As the audio is streamed to the megaphone 110, the HMI may continuously monitor the audio output for any issues like clipping or distortion, making real-time adjustments as necessary.

[0061] FIG. 4 illustrates detailed specifics of method 300 for audio playback that further illustrates processing and transmitting an audio to a vehicle to be played back from a megaphone integrated within the vehicle, in accordance with examples of the present subject matter. The order in which the above-mentioned methods are described is not intended to be construed as a limitation, and some of the described method blocks may be combined in a different order to implement the methods, or an alternative method.

[0062] In an example, the method 300 may be implemented by the user computing device 104 and the HMI 108 working in conjunction. As will be apparent from the foregoing description, the user computing device 104 may be operable for capturing input audio from a user and processing it to obtain processed audio, which is then provided to the HMI 108 for postprocessing and for playing over the vehicle-integrated megaphone.

[0063] Referring to Fig. 4, at block 402, input audio 212 from the user is captured by initiating recording of the input audio 212 via a microphone 208of the user computing device 104. This is the initial step where the user interacts with the megaphone function of the vehicle app installed on the user's computing device 104 to activate the megaphone feature and choose a voice filter. To initiate the recording of the input audio, start the execution of the vehicle app on the user computing device 104 and activate the megaphone function thereof to trigger the start of audio recording, and raw audio signals from the user in the form of audio input are captured by the microphone. The microphone may be a Bluetooth microphone in an example. The filters are then selected by the user based on user input at block 404.

[0064] The native C++ audio library is then initialized to process the input audio captured from the microphone with minimal delay at block 406. C++ libraries used herein may offer a wide-ranging, ready-built collection of audio classes, from decoders to players to audio filters, and may be understood as any collection of pre-written code that provides functionalities for working with audio in C++ applications. In other aspects, the C++ libraries may offer various tools and abstractions to handle tasks related to audio input, output, processing, analysis, and manipulation. For instance, in the present subject matter, the C++ library facilitates the recording of audio from microphones for playback of the audio through a vehicle-integrated megaphone.

[0065] In an example implementation of the present subject matter, the C++ library that may be configured for capturing audio from the microphone with minimal delay and for recording of audio input and processing of audio input is the Oboe library. Oboe may be understood as any open-source C++ library that is designed specifically for building high-performance, low- latency audio apps on Android. The Oboe is a C++ library designed to achieve low-latency audio recording and playback on Android devices. It works by providing a consistent API for interacting with the underlying audio hardware, abstracting away the complexities of different Android versions and audio hardware implementations. Oboe prioritizes low latency by usingoptimized settings for audio streams, allowing for faster response times between user audio input and audio output. In the present subject matter, the Oboe library facilitates simultaneous audio recording and playback by allowing the vehicle app to interact with audio streams. The Oboe library handles audio streams by facilitating data flow between vehicle apps and the audio hardware (like a microphone or speaker) of the user computing device 104. It achieves this through AudioStream objects, which act as conduits for audio data. Apps read from or write to these streams, and Oboe manages the underlying audio driver interactions, providing low-latency performance. Oboe may handle both audio input and output streams, support various sample rates and buffer sizes, and can automatically adjust audio parameters to achieve optimal performance on the specific device hardware, making it suitable for applications requiring precise timing and minimal audio delay.

[0066] At block 408, the method further proceeds to core processing steps for processing of input audio for echo cancellation and feedback prevention. The processing of input audio involves implementing a series of digital signal processing techniques to enhance audio quality and prevent feedback. In some embodiments, the method utilizes a custom C++ library to perform real-time audio processing operations. In an example, audio processing is implemented using filters that involve selectively allowing or attenuating certain frequency components of an audio signal to shape its sound or remove unwanted noise. Various types of filters are used to achieve this, each with distinct frequency response characteristics. In an example implementation of the present subject matter, a biquad high-pass filter may be configured to remove unwanted low-frequency sounds like rumble, wind noise, or handling noise that may degrade audio quality and to focus on higher-frequency content like vocals. The biquad implementation may provide efficient computation with minimal latency while maintaining stable filter characteristics. The biquad high-pass filter may be understood as any type of second order (two poles, two zeros)recursive linear digital filter characterized by a biquadratic transfer function. Such filters may be commonly implemented in digital signal processing to allow frequencies above a cutoff frequency to pass while attenuating lower frequencies. The biquad high-pass filter may provide several advantages in audio processing, including computational efficiency, numerical stability, and the ability to cascade multiple sections for higher-order filtering. The filter may be particularly useful for removing low-frequency noise, DC offset, or unwanted bass components from audio signals while preserving the clarity of higher frequency content such as vocals.

[0067] In an example, a biquad high self-filter is configured for the processing of input audio for echo cancellation and feedback prevention. The biquad high self-filter shapes the high-frequency content of the audio, potentially reducing harshness or echo on high-pitched sounds. The biquad high self-filter, in general, may be employed to adjust the amplitude of high- frequency content above a specified frequency threshold. In some embodiments, this filter may shape the high-frequency response to reduce harshness, sibilance, or echo artifacts that may occur in high-pitched sounds. The biquad high self-filter may provide either boost or attenuation of the high-frequency range, depending on the desired audio characteristics. The biquad high self-filter may be employed to shape the high-frequency content of the audio signal. The filter may attenuate or boost frequencies above a specified cutoff frequency, which may help reduce harshness or echo artifacts that can occur with high-pitched sounds. In some implementations, the biquad high self-filter may use a second-order infinite impulse response (HR) structure that provides smooth frequency response characteristics. The biquad high self-filter may be configured with adjustable parameters, including cutoff frequency, gain, and quality factor to optimize the high-frequency response for different audio conditions. In some cases, the high shelf filter may be particularly effective at reducing echo components that tend to be more prominent in higher frequency ranges, thereby improving overall audio clarity and reducing listener fatigue.

[0068] In an example, a biquad low-pass filter may be configured to eliminate unwanted high-frequency sounds, like noise or artifacts. The biquad low-pass filter may be employed to attenuate unwanted high- frequency components in the audio signal, such as noise or artifacts. The biquad low-pass filter may provide efficient digital filtering with controllable cutoff frequency and quality factor parameters.

[0069] In an example, noise gates and expanders may be implemented to cut off audio signals below a certain amplitude threshold. The term "noise gate" may refer to an audio processing component that attenuates or eliminates audio signals when the signal level falls below a predetermined threshold. A noise gate may also be referred to as an expander and may operate by monitoring the amplitude of an incoming audio signal and comparing it to a configurable threshold value. When the signal amplitude is below the threshold, the noise gate may reduce the signal gain or completely mute the audio output, thereby minimizing unwanted background noise, hum, or other low-level interference.

[0070] In some aspects of the present subject matter, the processing of input audio for echo cancellation and feedback prevention may include adaptive echo cancellation algorithms that may identify and suppress acoustic echo or feedback. The echo cancellation may utilize techniques such as adaptive filtering, spectral subtraction, or machine learning-based approaches to distinguish between desired audio content and unwanted echo or feedback signals.

[0071] In some implementations, the audio processing may be optimized for low-latency operation to maintain real-time performance. In some embodiments, the system may utilize efficient algorithms, optimized memory management, and parallel processing techniques to minimize processing delay while maintaining audio quality.

[0072] At block 410, once the processing steps are performed on the input audio, voice modulation is performed on the processed input audio to obtain the output audio. The voice modulation on processed audio hereinrefers to performing processing techniques that include several audio processing techniques to modify voice characteristics. In some aspects, the method may implement pitch shifting functionality that alters the perceived highness or lowness of the voice by modifying the fundamental frequency and its harmonics. The pitch shifting may be accomplished through various digital signal processing algorithms that maintain audio quality while changing the tonal characteristics of the input voice signal. In some embodiments, voice tempo modification capabilities may be provided on the processed audio that adjust the speed of voice playback without necessarily affecting the pitch. This tempo-changing functionality may allow users to accelerate or decelerate audio while preserving the natural characteristics of the voice. The tempo modification may be implemented independently of pitch changes, providing flexible voice manipulation options.

[0073] The voice modulation method may further incorporate transformation techniques via time-stretching algorithms. In some cases, these algorithms may adjust the duration of audio segments to create various voice effects. The voice may utilize Time Domain Harmonic Scaler (TDHS) algorithms, which may provide high-quality time stretching by analyzing and manipulating harmonic components in the time domain. Additionally, the method may implement Waveform Similarity Overlap-Add (WSOLA) algorithms, which may achieve time stretching by identifying similar waveform segments and overlapping them to maintain audio continuity during temporal modifications.

[0074] In some aspects, the voice modulation techniques may include frequency band manipulation capabilities that selectively adjust the levels of different frequency ranges within the voice signal. This frequency manipulation may involve applying equalization techniques to emphasize or attenuate specific frequency bands, thereby altering the tonal characteristics and perceived quality of the voice. The frequency band manipulation may be implemented.

[0075] Once voice modulation is performed on the processed input audio to obtain output audio, the post-processing of the output audio is performed at block 412. The post-processing of output audio, in an example implementation of the present subject matter, refers to the set of techniques and steps applied to processed output audio after the initial recording and processing of audio input, aiming to improve, refine, and tailor the sound quality for the final output audio for playing over a vehicle-integrated megaphone. In an example, for post-processing of output audio, the method uses the Added Reverb Effect. The term "Added Reverb Effect" may refer to an audio processing technique that simulates the acoustic characteristics of a physical space by adding reverberation to an audio signal. The reverb effect may recreate the natural sound reflections that occur when audio is produced in an enclosed environment, such as a room, hall, or other acoustic space. This effect may be achieved through various methods, including convolution with recorded impulse responses of real spaces or through algorithmic processing using delay networks, filters, and feedback mechanisms. The added reverb effect may modify the perceived spatial characteristics of the audio, creating an impression that the sound originates from or is being heard within a particular acoustic environment.

[0076] In an implementation, a peaking filter may be employed to selectively amplify specific frequency ranges within the audio signal. In some aspects, the peaking filter may boost predetermined frequency bands to enhance particular characteristics of the sound, such as vocal clarity or tonal balance. The peaking filter may operate by applying gain to a narrow or broad frequency range centered around a specified frequency, while leaving adjacent frequencies relatively unaffected. A peaking filter (also called a bell filter or peak filter) may be understood as an audio equalization filter that boosts or cuts the amplitude of a narrow specific range of frequencies centered around a chosen frequency.

[0077] The technique of the present invention may also implement "looping avoiding," which may refer to a mechanism or process thatmanages the recording and playback flow based on audio input detection to prevent audio feedback loops. In some aspects, looping avoiding may include detecting when audio input is present and controlling the timing of recording and playback operations accordingly. The looping-avoiding functionality may help prevent situations where output audio is inadvertently captured as input, which could create unwanted feedback or echo effects in the audio processing system.

[0078] In some implementations of the present subject matter, parallel processing may be implemented using OpenMP optimizations within a C++ library to achieve real-time performance and minimize processing latency. In some aspects, the method may leverage parallel computing techniques to improve processing speed and reduce delay in audio signal processing operations. The parallel processing may be applied to various audio processing operations, including but not limited to filtering, echo cancellation, noise reduction, and voice modulation.

[0079] At block 414 as shown in Fig 4, the method may include transmitting post-processed output audio for playing over a vehicle- integrated megaphone. The steps of block 414 may be implemented using low-latency real-time audio transmission techniques, further utilizing Bluetooth communication protocols and C++ libraries for enhanced audio processing and modulation. The HMI 108 is configured to implement steps 410 to 412 for post-processing of the output audio and transmitting of the post-processed output audio for playing over a vehicle-integrated megaphone, which is elaborated above with respect to Fig. 1 .

[0080] At block 414, the processed digital audio stream is enqueued into the Oboe output stream for transmission. The Oboe framework may provide low-latency audio output capabilities by interfacing directly with the Android Audio HAL (Hardware Abstraction Layer). In some aspects, the processed audio data may be buffered in circular buffers to maintain continuous playback while minimizing latency. The Oboe stream may be configured with specific parameters, including sample rate, buffer size, andaudio format to optimize performance for real-time audio transmission. The final conditioned audio signal from the post-processing steps may be prepared for wireless transfer via the Oboe output stream. In some embodiments, the integrated human machine (HMI) of the vehicle may receive the processed audio data and format it appropriately for transmission through the Oboe streaming framework.

[0081] The digital audio stream may be serialized into packets and transmitted wirelessly to the vehicle utilizing a Bluetooth protocol. In some embodiments, the vehicle’s embedded control unit receives the transmitted audio packets and may process them for further audio output or system integration. In some aspects, the HMI may include processing capabilities to handle the incoming audio data stream. The received packets may be buffered, decoded, or routed to appropriate audio output components within the vehicle-integrated megaphone. In some cases, the vehicle-integrated megaphone may perform additional processing such as volume adjustment, audio format conversion, or synchronization with other system functions. The vehicle-integrated megaphone may also provide feedback or acknowledgment signals to confirm successful packet reception and maintain communication integrity with the transmitting device. The received post-processed output data that is transmitted to the vehicle integrated megaphone is rendered as an acoustic signal via the vehicle’s electroacoustic transducer. A "transducer" may include any device capable of converting electrical signals into acoustic signals, such as vehicle- integrated megaphone speakers or audio output devices or converting acoustic signals into electrical signals (such as microphones or audio input devices). The encoded audio data, if compression is employed, is decoded by the vehicle-integrated megaphone prior to audio rendering. In some embodiments, vehicle-integrated megaphone may include dedicated audio processing hardware or software-based decoders capable of handling multiple compression formats. In some cases, the decoding process maybe performed in real-time to minimize latency between audio transmission and playback.

[0082] Although implementations of the present subject matter have been described in language specific to structural features and / or methods, it is to be noted that the present subject matter is not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed and explained in the context of a few implementations for the present subject matter.

Claims

l / We Claim:1 . A method (300) for audio playback, the method comprising: receiving (301 ), at a user computing device (104), an input audio (212) via a microphone (208) of the user computing device (104); processing (304) the input audio (212) using a C++ library to obtain a processed audio (214); filtering (306) the processed audio (214) to obtain a noise-filtered audio; performing (308) voice modulation on the noise filtered audio to obtain a modulated audio; compressing (310) the modulated audio (218) to obtain an output audio; and transmitting (312) the output audio (220) to a vehicle (102) for playback by a megaphone integrated with the vehicle (102).

2. The method (300) as claimed in claim 1 , wherein the method (300) further comprises activating a megaphone function of an application execution in the user computing device (104), and wherein the input audio (212) is processed by execution of the application.

3. The method (300) as claimed in claim 1 , wherein processing the input audio (212) using the C++ library to obtain the processed audio (214) comprises converting an initial audio format of the input audio (212) and adjusting a sample rate of the input audio (212) to match requirements of the integrated megaphone.

4. The method (300) as claimed in claim 1 , wherein performing (308) voice modulation on the noise-filtered audio to obtain the modulated audio (218) comprises applying audio modulation effects selected from amongst chipmunk, robot, and deep voice to modify the filtered audio.

5. A method (300) for audio playback, the method comprising: receiving (314), an output audio (220) of a user computing device(104) by an integrated human machine interface (HMI) (108) of a vehicle (102); processing (316), by the HMI, the output audio (220) for playback by a megaphone of the vehicle (102), wherein processing of the output audio (220) comprises: performing decompression on the received output audio (220) to obtain an unpacked audio; analyzing the unpacked audio and optimizing parameters of the megaphone based on the analyzing 110; and transmitting 318 the unpacked audio to the megaphone for playback.

6. The method (300) as claimed in claim 5, wherein optimizing the parameters of the megaphone based on the analyzing comprises: analysing the frequency content of the unpacked audio and adjusting the megaphone’s 110 equalization settings; and adjusting settings of the megaphone for setting gain levels without distortion or feedback.

7. The method (300) as claimed in claim 5, wherein the processing by the HMI (108) comprises applying dynamic range compression to maintain consistent volume levels across varying input signals of the received output audio (220).

8. The method (300) as claimed in claim 5, wherein optimizing parameters of the megaphone comprises adjusting the parameters comprising directionality, beamforming, or coverage angle of themegaphone based on a current speed of the vehicle (102), ambient noise levels, or user preferences.

9. The method (300) as claimed in claim 8, further comprising performing a handshaking process between the user computing device (104) and the HMI (108) to initiate delivery of the output data from the user computing device (104) to the HMI (108).

10. A user computing device (104) for audio playback, comprising: a microphone(s) 208, a processing engine (226) to: receive an input audio (212) via the microphone (208); process the input audio (212) using a C++ library to obtain a processed audio (214); filter the processed audio (214) to obtain a noise-filtered audio; perform voice modulation on the noise filtered audio to obtain a modulated audio (218); compress the modulated audio (218) to obtain an output audio; and a transmission engine (228) to: transmit the output audio (220) to a vehicle (102) for playback by a megaphone integrated with the vehicle (102).

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