WO2023101671A1

WO2023101671A1 - White noise generators

Info

Publication number: WO2023101671A1
Application number: PCT/US2021/061554
Authority: WO
Inventors: Anthony KAPLANIS; Alexander Williams; John W. FREDERICK
Original assignee: Hewlett-Packard Development Company, L.P.
Priority date: 2021-12-02
Filing date: 2021-12-02
Publication date: 2023-06-08

Abstract

In some examples, the disclosure describes a device that includes a microphone, a white noise generator, and a processor to: monitor a level of ambient noise around the device utilizing the microphone, determine a level of white noise generated by the white noise generator in response to the level of ambient noise, and transmit the level of ambient noise and the level of white noise generated to a remote device with a corresponding white noise generator.

Description

WHITE NOISE GENERATORS

Background

[0001] Computing devices are utilized to perform particular functions. In some examples, computing devices utilize microphones in order for a user to communicate through the computing device. In some examples, the computing device microphone may pick up surrounding ambient noise. In some examples, white noise generators may diffuse or block out ambient noise detected by the computing device microphone.

Brief Description of the Drawings

[0002] Figure 1 illustrates an example of a device for generating a level of white noise based on a level of ambient noise around the device.

[0003] Figure 2 illustrates an example of a memory resource for generating a level of white noise based on a privacy level within threshold areas.

[0004] Figure 3 illustrates an example of a system for generating a level of white noise based on a privacy level determined by distances between devices. [0005] Figure 4 illustrates an example of a system for managing the level of white noise generated by a plurality of devices.

[0006] Figure 5 illustrates an example of a system for generating a map of devices within a threshold area utilized for managing the level of white noise generated by a plurality of devices.

Detailed Description

[0007] A user may utilize a computing device for various proposes, such as for business and/or recreational use. As used herein, the term computing device refers to an electronic device having a processor and a memory resource. Examples of computing devices include, for instance, a laptop computer, a notebook computer, a desktop computer, and/or a mobile device (e.g., a smart phone, a tablet, a personal digital assistant, smart glasses, a wrist-worn device, etc.), among other types of computing devices.

[0008] In some examples, the computing device includes a display device to display images generated by the computing device and/or to allow a user to interact with the computing device. In some examples, the display device is utilized to display a user interface that allows a user to interact with the computing device and/or instruct the computing device to perform particular functions.

[0009] In some examples, the computing device may be used in a work environment. In some examples, when using the computing device, the user may interact with entities outside the business (e.g., through phone calls, zoom meetings, etc.). In some examples, confidentiality of the work environment in the business may be compromised by external entities overhearing surrounding employee conversations (e.g., employees on phone calls, in conference calls, discussing work strategies, on zoom meetings, etc.). For example, a conversation occurring in close proximity to the computing device, when the user interacts with an external entity, may be overheard by the external entity. In some examples, the work environment may be an open work environment contributing to a higher risk of compromised confidentiality.

[0010] In some examples, a noise generator may be utilized to diffuse or block out ambient noise in a work environment. For example, a white noise generator may be integrated into a building infrastructure. In such an example, a white noise generation system hardwired into the infrastructure may be expensive and/or cost prohibitive. In some examples, the white noise generator integrated into the building infrastructure may transmit a level of noise throughout the work environment. The level of noise may include various characteristics (e.g., an increase or decrease in volume, change in tone, change in frequency, etc.) These white noise generators may have minimal intelligence and basic programming (e.g., time of operation, volume level, PA messaging system selection, etc.). In such an example, the white noise generators may lack feedback for adjusting a volume of white noise generated based on ambient noise. Ambient noise may be based on a level of noise that is adjustable within the work environment (e.g., a network of noise generators, etc.) or a level of noise that is not adjustable within the work environment (e.g., system noise, external noise, etc.). In such an example, the white noise generators may provide too little white noise to adequately diffuse or block out ambient noise in the work environment or an uncomfortably high level of white noise for the user (e.g., noise pollution). In such an example, a higher level of white noise may interfere with internal and external communications (e.g., phone calls, zoom meetings, conference calls, employee to employee conversations, etc.).

[0011] The present disclosure relates to a white noise generator integrated into a computing device to generate a level of white noise, eliminating the need for a hardwired system. In some examples, the white noise generator may be integrated into a display device to provide a white noise field around the display device. In some examples, a microphone may be integrated into the display device to monitor surrounding ambient noise level. In some examples, the white noise generator may generate a level of white noise in response to the level of ambient noise detected. In some examples, the white noise generator may be a dynamic white noise generator. In some examples, the display device may be a mobile or remote display device. In some examples, the capability of the system is scalable by adding or removing display devices within the work environment. In this way, installation of an integrated white noise generation system may be a time efficient and economically viable alternative.

[0012] In some examples, the computing device includes a speaker to output sound generated by the white noise generator. In some examples, the speaker may be a speaker integrated into the display. In some examples, the speaker may be connected to a sound output on the display monitor’s main board. For example, the speaker may be connected to a separate sound output on the display monitor’s main board. In some examples, the sound output may be controlled by an audio clip. For example, the audio clip may be pre-loaded on a separate storage within the flash memory of the computing device. In some examples, the user may select between a pre-loaded audio clip and source audio. In some examples, the selection of a pre- loaded audio clip may be controlled by a display monitor (e.g., on-screen display, virtual control panel, universal serial bus, etc.) command and may include different selections of audio clip types (e.g., selection of running water, etc.). In some examples, the user may be able to install and download a white noise generation pattern for customized white noise settings. In such an example, the custom white noise setting may be uploaded to the display monitor via a firmware update.

[0013] In some examples, the computing device may include a display monitor onboard speaker. In another example, the computing device may include both a speaker connected to the display monitor and a display monitor onboard speaker. Further, the computing device may include an option for a user to select the speaker connected to the display or the display monitor onboard speaker. In these examples, the sound output may be controlled by an audio clip. For example, the audio clip may be pre-loaded on a separate storage within the flash memory of the computing device. In some examples, the user may select between a pre-loaded audio clip and source audio. In some examples, the selection of a pre-loaded audio clip may be controlled by a display monitor (e.g., on-screen display, virtual control panel, universal serial bus, etc.) command and may include different selections of audio clip types (e.g., selection of running water, etc.). In some examples, the user may be able to install and download a white noise generation pattern for customized white noise settings. In such an example, the custom white noise setting may be uploaded to the display monitor via a firmware update.

[0014] In some examples, the computing device may include a microphone to monitor ambient noise level around the computing device. In some examples, the microphone may be an onboard microphone. For example, the microphone may be a separate onboard microphone. In some examples, the microphone may be connected to the display monitor’s data input. In these examples, the microphone may be utilized to measure an ambient noise level surrounding the computing device.

[0015] Figure 1 illustrates an example of device 100 for noise generation (e.g., white noise generator) based on ambient noise surrounding the device. In some examples, the device 100 is a computing device that includes a microphone 102, a white noise generator 104 and a processor 106 that can utilize the microphone 102 to monitor the ambient noise level surrounding the device 100.

[0016] The device 100 includes instructions 116 that are executed by the processor 106 to monitor a level of ambient noise around the device 100. In some examples, the instructions 116 are executed by the processor 106 to monitor a level of ambient noise around the device 100 utilizing the microphone 102.

[0017] The device 100 includes instructions 118 that are executed by the processor 106 to determine a level of white noise generated by the white noise generator 104. In some examples, the instructions 118 are executed by the processor 106 to determine a level of white noise generated by the white noise generator 104 in response to the level of ambient noise. As described herein, the level of white noise generated may include a frequency of the white noise generated, an amplitude of the white noise generated, and/or a type of white noise generated. [0018] The device 100 includes instructions 120 that are executed by the processor 106 to transmit the level of ambient noise and the level of white noise generated to a remote device 112. In some examples, the instructions 120 are executed by the processor 106 to transmit the level of ambient noise and the level of white noise generated to a remote device 112 with a corresponding white noise generator 114. As described herein, the level of ambient noise and the level of white noise generated are transmitted to the remote device 112 utilizing the communication path 110. In some examples, the level of white noise generated by the corresponding white noise generator 114 of the remote device 112 is altered in response to the level of ambient noise and the level of white noise generation the device 100 transmits to the remote device 112. For example, when the level of white noise generated by the white noise generator 104 changes (e.g., is reduced, increased, or the white noise generator 104 is turned off), the remote device 112 may alter the level of white noise generated from the corresponding white noise generator 114 to compensate for the change. In this way, the remote device 112 may generate a level of white noise to diffuse and/or block out ambient noise surrounding the remote device 112.

[0019] In some examples, the processor 106 of the device 100 receives the level of white noise generated by the corresponding white noise generator 114 of the remote device 112. In such an example, the processor 106 may determine a level of white noise generated by the white noise generator 104 in response to the level of ambient noise detected by the microphone 102 and the level of corresponding white noise generated by the remote device 112.

[0020] In some examples, the device 100 includes a processor 106 communicatively coupled to a memory resource 108. As described further herein, the memory resource 108 includes instructions 116, 118, 120 that are executed by the processor 106 to perform particular functions.

[0021] The device 100 includes components such as a processor 106. As used herein, the processor 106 includes, but is not limited to: a central processing unit (CPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a metal-programmable cell array (MPCA), a semiconductorbased microprocessor, or other combination of circuitry and/or logic to orchestrate execution of instructions 116, 118, 120. In other examples, the device 100 includes instructions 116, 118, 120 stored on a machine-readable medium (e.g., memory resource 108, non-transitory computer-readable medium, etc.) and executable by a processor 106. In a specific example, the device 100 utilizes a non-transitory computer-readable medium storing instructions 116, 118, 120 that, when executed, cause the processor 106 to perform corresponding functions.

[0022] Figure 2 illustrates an example of a memory resource 208 for a level of white noise generation based on privacy level and ambient noise. In some examples, the memory resource 208 is part of a computing device or controller that can be communicatively coupled to a computing system. For example, the memory resource 208 is part of a device 100 as referenced in Figure 1. In some examples, the memory resource 208 is communicatively coupled to a processor 206 that executes instructions 222, 224, 226, 228, stored on the memory resource 208. For example, the memory resource 208 is communicatively coupled to the processor 206 through a communication path 210. In some examples, a communication path 210 includes a wired or wireless connection that allows communication between devices and/or components within a single device.

[0023] The memory resource 208 may be electronic, magnetic, optical, or other physical storage device that stores executable instructions. Thus, a non- transitory machine-readable medium (MRM) (e.g., a memory resource 208) may be, for example, a non-transitory MRM comprising Random-Access Memory (RAM), read-only memory (ROM), an Electrically-Erasable Programmable ROM (EEPROM), a storage drive, an optical disc, and the like. The non-transitory machine-readable medium (e.g., a memory resource 208) may be disposed within a controller and/or computing device. In this example, the executable instructions 222, 224, 226, 228, can be “installed” on the device. Additionally, and/or alternatively, the non-transitory machine-readable medium (e.g., a memory resource 208) can be a portable, external or remote storage medium, for example, that allows a computing system to download the instructions 222, 224, 226, 228, from the portable/external/remote storage medium. In this situation, the executable instructions may be part of an “installation package”. As described herein, the non-transitory machine-readable medium (e.g., a memory resource 208) can be encoded with executable instructions for establishing transfer locations. [0024] In some examples, the memory resource 208 includes instructions 222 to determine a level of ambient noise. In some examples, the memory resource 208 includes instructions 222 to determine a level of ambient noise within a first threshold area of the device 200. In some examples, the first threshold area may be an area surrounding the device 200 that the processor 206 monitors utilizing the microphone. As described herein, the first threshold area may be the area in which, due to the proximity of internal business conversations to the device, external entities may overhear confidential communications.

[0025] In some examples, the memory resource 208 may include instructions to determine an ambient noise type (e.g., employee conversations, other white noise generators, environmental sounds, etc.) of the ambient noise. For example, the ambient noise type may be the voice of an employee. In such an example, employee voices may be recorded and stored in the memory resource 208. In such an example, the memory resource 208 may include instructions to determine ambient noise to be the voice of an employee and compare the voice with a database of vocal recordings associated with employees. In some examples, the device may have a user designated to that device. In some examples, the memory resource 208 may include instructions to determine from the vocal database whether the ambient noise is the voice of the user of the device or the voice of another employee.

[0026] In some examples, the memory resource 208 includes instructions 224 to determine a level of privacy. In some examples, the level of privacy may be determined automatically from the memory resource 208 as described herein or determined manually by the user. In some examples, the memory resource 208 includes instructions 224 to determine a level of privacy for the first threshold area. In some examples, the memory resource 208 includes instructions 224 to determine a level of privacy based on the ambient noise type. In some examples, the ambient noise type may be a voice. In such an example, the memory resource 208 may include instructions 224 to determine who is talking (e.g., by utilizing a camera, a time of flight sensor, voice recognition, etc.). In some examples, the memory resource 208 includes instructions 224 to compare the voice to the vocal database. In some examples, the memory resource 208 includes instructions 224 to determine the level of privacy based on the vocal database comparison. In such an example, the memory resource 208 may include instructions 224 to determine whether the voice is the voice of the device user. In some examples, the memory resource 208 includes instructions 224 to disregard the voice of the user when determining the level of privacy. In some examples, the memory source 208 includes instructions 224 to monitor the conversation of the user and compare the conversation to a database of keywords. In such an example, the memory resource 208 may include instructions 224 to determine a level of privacy based on a keyword comparison (e.g., proprietary information, etc.). In some examples, the memory resource 208 includes instructions 224 to determine whether the voice is a voice of another employee. In such an example, the memory resource 208 may include instructions 224 to determine the level of privacy to be high.

[0027] In some examples, the ambient noise may be a type of noise other than a voice. In such an example, the memory resource 208 may include instructions 224 to determine the level of privacy to be a lower level of privacy or may disregard the ambient noise detected when determining the level of privacy. [0028] In some examples, the memory resource 208 includes instructions 226 to instruct a white noise generator to generate a level of white noise. In some examples, the instructions 226 instruct a white noise generator to generate a level of white noise in response to the level of ambient noise. In some examples, the instructions 226 instruct a white noise generator to generate a level of white noise in response to the level of privacy of the first threshold area. In some examples, the instructions 226 instruct a white noise generator to generate a level of white noise in response to the level of ambient noise and the level of privacy of the first threshold area. In some examples, the level of privacy may be determined by the type of ambient noise detected. In such examples, the memory resource 208 may include instructions 226 to instruct a white noise generator to generate a level of white noise based on the ambient noise type. For example, the ambient noise may be a voice and the memory resource 208 may compare the voice to a vocal database. In such an example, the memory resource 208 may include instructions 226 to calibrate the white noise generator based on the comparison. In some examples, the ambient noise may be a type of noise other than a voice. In such an example, the ambient noise may have a high or a low pitch. In such an example, the memory resource 208 may include instructions 226 to determine a frequency of the white noise generated, amplitude of the white noise generated, and/or type of white noise generated based on the ambient noise pitch, in order to adequately diffuse or block out the ambient noise.

[0029] In some examples, the memory resource 208 includes instructions 228 to transmit to a plurality of white noise generators corresponding to a plurality of devices within a threshold area, the level of privacy and the corresponding level of white noise for the plurality of white noise generators. In some examples, the memory resource 208 includes instructions 228 to transmit to a plurality of white noise generators corresponding to a plurality of devices within a second threshold area, the level of privacy and the corresponding level of white noise for the plurality of white noise generators. In some examples, the first threshold area and the second threshold area are different sizes. In some examples, the second threshold area is larger than the first threshold area. In some examples, the first threshold area is located within the second threshold area.

[0030] Figure 3 illustrates an example of a system 300 for white noise generation based on privacy level and ambient noise level. In some examples, the system 300 includes the same elements as device 100 as referenced in Figure 1 and memory resource 208 as referenced in Figure 2. For example, the system 300 include a processor 306, a memory resource 308, and communication paths 310-1 and 310-2 (collectively referred to as communication paths 310), such that the processor 306 is capable of transmitting to a plurality of remote devices 330-1 and 330-2 (collectively referred to as remote devices 330) utilizing the communication paths 310.

[0031] In some examples, the processor 306 is a device that includes hardware, such as an ASIC, central processing unit (CPU) or other processing resource to execute particular instructions 336, 338, 340, 342, 344, 346. In some examples, the instructions 336, 338, 340, 342, 344, 346, are stored on a non- transitory computer readable medium (e.g., memory resource 308, etc.) and executed by the processor 306 to perform the corresponding functions.

[0032] In some examples, the system 300 includes a plurality of devices 330. In some examples, the system 300 includes a plurality of white noise generators 332-1 and 332-2 (collectively referred to as white noise generators 332) integrated into the plurality of devices 330. In some examples, the system 300 includes a plurality of microphones 334-1 and 334-2 (collectively referred to as microphones 334) integrated into the plurality of devices 330. [0033] The system 300 includes instructions 336 that are executed by the processor 306 to identify a first device 330-1. In some examples, the instructions 336 include a scan of the work environment area utilizing the communication paths 310. In some examples, the processor 306 identifies a first device 330-1 from a plurality of devices 330 within the work environment. In some examples, the processor 306 identifies the first device utilizing the communication path 310-1. [0034] The system 300 includes instructions 338 that are executed by the processor 306 to identify a second device 330-2. In some examples, the instructions 338 include a scan of the work environment area utilizing the communication paths 310. In some examples, the processor 306 identifies a second device 330-2 from a plurality of devices 330 within the work environment. In some examples, the processor 306 identifies the second device utilizing the communication path 310-2. [0035] The system 300 includes instructions 340 that are executed by the processor 306 to determine a signal strength between the first device 330-1 and the second device 330-2. In some examples, the first device 330-1 may transmit a signal (e.g., a tone transmitted via Bluetooth, etc.), utilizing the communication path 310-3, to the second device 330-2 and the second device 330-2 may receive the signal from the first device 330-1. In some examples, the second device 330-2 may transmit a signal, utilizing the communication path 310-3, to the first device 330-1 and the first device 330-1 may receive the signal from the second device 330-2. As described herein, the processor 306 may utilize the communication paths 310 to determine the strength of the signal between the first device 330-1 and the second device 330-2.

[0036] The system 300 includes instructions 342 that are executed by the processor 306 to determine a distance between the first device 330-1 and the second device 330-2. In some examples, the instructions 342 instruct the processor to determine a distance between the first device 330-1 and the second device 330-2 based on the signal strength between the first device 330-1 and the second device 330-2. In such an example, the stronger the signal strength between the first device 330-1 and the second device 330-2, the closer in proximity the first device 330-1 is to the second device 330-2.

[0037] The system 300 includes instructions 344 that are executed by the processor 306 to determine a level of privacy for the first device 330-1. In some examples, the instructions 344 instruct the processor to determine a level of privacy for the first device 330-1 based on the distance between the first device 330-1 and the second device 330-2. In such an example, the closer the first device 330-1 is in proximity to the second device 330-2, the higher the level of privacy for the first device 330-1.

[0038] In some examples, the level of privacy may be based on the operational content of the first device 330-1 and the second device 330-2 (e.g., first device 330-1 is associated with host 1 and host 1 is on a private phone call corresponding to a high level of privacy, second device 330-2 is associated with host 2 and host 2 is reading a web article corresponding to a low level of privacy.) In some examples, the level of privacy may change (e.g., host 1 associated with the first device 330-1 completes the private call corresponding to a reduced level of privacy, host 2 associated with the second device 330-2 enters a conference call with a client corresponding to an increased level of privacy, etc.) resulting in a corresponding change in level of white noise generated. In some examples, the first device 330-1 and the second device 330-2 may share a privacy session (e.g., first device 330-1 is associated with host 1 and host 1 is on a private call and second device 330-2 is associated with host 2 and host 2 is on the same private call as host 1). In such an example, the level of privacy may be minimized between the first device 330-1 and the second device 330-2 and the white noise generated may be reduced or eliminated corresponding to the minimized level of privacy.

[0039] The system 300 includes instructions 346 that are executed by the processor 306 to instruct a white noise generator 332-1 of the first device 330-1 to generate a level of white noise. In some examples, the instructions 346 instruct a white noise generator 332-1 of the first device 330-1 to generate a level of white noise based on the level of privacy. In such an example, the level of white noise generated increases with a level of privacy increase and the level of white noise generated decreases with a level of privacy decrease. In such an example, the closer the first device 330-1 is in proximity to the second device 330-2, the higher the level of privacy and the higher the level of white noise generated. In addition, the farther the first device 330-1 is in proximity to the second device 330-2, the lower the level of privacy and the lower the level of white noise generated.

[0040] In some examples, the processor 306 may generate a map of the work environment depicting the location of the first device 330-1 and the location of the second device 330-2 based on the distance determined between the first device 330-1 and the second device 330-2. In some examples, the first device 330-1 and the second device 330-2 may detect the distance between each other. In some examples, a map of the plurality of devices 330 may be manually created and programmed into the processor 306. In some examples, the processor 306 may include instructions to instruct the plurality of white noise generators 332 to generate a level of white noise based on the map of the plurality of devices 330. For example, the processor 306 may instruct the plurality of white noise generators 332 to increase the level of white noise generated when the plurality of devices 330 are closer in proximity, in order to diffuse and/or block the ambient noise generated by users of the plurality of devices 330.

[0041] In some examples, a particular user may be assigned to the first device 330-1 and another particular user may be assigned to the second device 330-2. In some examples, the user assigned to the first device 330-1 and the user assigned to the second device 330-2 may be stored in the processor database and included in the map of the work environment. In some examples, the voice of the first device user and the voice of the second device user may be stored in the processor vocal database. In such an example, the processor 306 may instruct the plurality of white noise generators 332 to generate a level of white noise based on the voice (e.g., pitch, volume etc.) of the users assigned to the plurality of devices 330 and the proximity of the first device 330-1 to the second device 330-2. In this way, ambient noise generated by the first device user may be sufficiently diffused or blocked from the second device user and ambient noise generated by the second device user may be sufficiently diffused or blocked from the first device user. In some examples, the level of white noise generated by the first device 330-1 is a different level than the level of white noise generated by the second device 330-2.

[0042] In some examples, the system 300 may include instructions that are executed by the processor 306 to scan of the work environment area. In some examples, the instructions include identifying a third device from a plurality of devices. In some examples, the system 300 may include instructions that are executed by the processor 306 to determine a signal strength (e.g., a tone transmitted via Bluetooth, etc.) between the third device and the second device and a signal strength (e.g., a tone transmitted via Bluetooth, etc.) between the third device and the first device. In some examples, the system 300 may include instructions that are executed by the processor 306 to determine a distance between the third device and the first device based on the signal strength between the third device and the first device and to determine the distance between the third device and the second device based on the signal strength between the third device and the second device. In some examples, the processor 306 may update the map of the work environment depicting the location of the third device based on the distance determined between the third device and the first device and the distance determined between the third device and the second device.

[0043] Figure 4 illustrates an example system 400 for a remote management device 450 (e.g., a cloud resource, etc.) for control and/or communication management of remote devices 430-1, 430-2, 430-3, 430-n (collectively referred to as remote devices 430). The remote devices 430 include the same components as device 100 as reference in Figure 1 and system 300 in Figure 3. In some examples, remote devices 430 transmit to the remote management device 450, through communication paths 410-1, 410-2, 410-3, 410-n (collectively referred to as communication paths 410), (e.g., through a cloud connection, etc.), the level of white noise generated by a plurality of white noise generators 432-1, 432-2, 432-3, 432-n (collectively referred to as white noise generators 432). In some examples, the remote devices 430 transmit to the remote management device 450, through the communication paths 410, the level of ambient noise detected by the plurality of microphones 434-1, 434-2, 434-3, 434-n (collectively referred to as microphones 434). In some examples, the remote devices 430 transmit to the remote management device 450, through the communication paths 410, the level of white noise generated by the plurality of white noise generators 432 and the level ambient noise detected by the plurality of microphones 434.

[0044] In some examples, the remote devices 430 may be controlled and/or activated by the remote management device 450. Although Figure 4 shows four remote devices (e.g., the first device, the second device, the third device, and the n device 430-1 , 430-2, 430-3, 430-n) other examples may provide for fewer than four remote devices or more than four remote devices. Although Figure 4 shows one remote management device (e.g., remote management device 450) other examples may provide for more than one remote management device.

[0045] In some examples, the plurality of remote devices 430 may receive, through the communication paths 410, instructions from the remote management device 450. For example, the plurality of remote devices 430 may receive instructions to generate a level of white noise. In such an example, the level of white noise may be based on the level of ambient noise detected by the plurality of microphones 434. In such an example, the remote management device 450 may instruct the plurality of devices 430 to alter the level of white noise generated based on a change in the level ambient noise detected.

[0046] In some examples, the level of white noise generated may increase in response to an increase in ambient noise detected. In such an example, an increase in white noise generated may defuse and/or block out the increased level of ambient noise detected. In some examples, the level of white noise generated may decrease in response to a decrease in ambient noise detected. In such an example, a decrease in white noise generated may reduce noise (e.g., noise pollution) in the work environment. As used herein, the level of white noise generated may include a frequency of the white noise generated, an amplitude of the white noise generated, and/or a type of white noise generated.

[0047] Figure 5 illustrates an example of a computing device 500 for white noise generation based on privacy level and ambient noise surrounding the device. The device 500 in Figure 5 illustrates the device 500 utilized by a user in a work environment. As used herein, the work environment includes the device 500 and a plurality of remote computing devices 530-1 , 530-2, ... 530-n (collectively referred to as remote devices 530). In such an example, the work environment may be an area designated as the second threshold area 560. As used herein, the area surrounding the device 500 where ambient noise is monitored through the microphone of the device 500 may be the first threshold area 555. In such an example, the first threshold area 555 may include any area surrounding the device 500 where confidential communication may be detected by the microphone and the second threshold area 560 may include the area in which the plurality of devices 530, including the device 500, may be utilized within the work environment. In some examples, the first threshold area 555 may be within the second threshold area 560.

[0048] In some examples, the device 500 and the plurality of devices 530 may transmit and receive a signal (e.g., a tone transmitted via Bluetooth, etc.). In such an example, a processor may monitor the signal strength between devices, and utilizing the signal strength, determine the distance between devices. In such an example, the processor may generate a map of the second threshold area 560 depicting the location of the device 500 and the plurality of devices 530. In some examples, a map of the device 500 and the plurality of devices 530 may be manually created and programmed into the processor. In some examples, the processor may utilize the map to determine the privacy levels of device 500 and another device of the plurality of devices 530 (e.g., remote device 530-1) based on the proximity of device 500 to the other device and the content of device 500 and/or the content of the other device (e.g., private phone call, conference call with customer, reading a web article, no activity of device, etc.).

[0049] In some examples, the device 500 and the plurality of devices 530 may be stationary and designated to a particular location within the second threshold area 560. In such an example, the map of the second threshold area 560 may be updated with the addition or removal of a device within the second threshold area 560.

[0050] In some examples, the device 500 and/or the plurality of devices 530 may be mobile or remote and may be moved throughout the second threshold area 560. In some examples, the processor may update the map based on the changing locations of the device 500 and/or the plurality of devices 530.

[0051] In some examples, a device 530-1 of the plurality of devices 530 may be moved into the first threshold area 555 of the device 500 (e.g., a proximity close enough to the device 500 that the microphone of device 500 detects the white noise generated by the device 530-1). In such an example, the processor may determine the proximity of device 530-1 to the device 500 and adjust the level of white noise generated by the device 530-1 and/or the device 500. For example, white noise generated by the device 500 diffuses or blocks ambient noise surrounding the device 500 and white noise generated by the device 530-1 diffuses or blocks ambient noise surrounding the device 530-1. In such an example, the level of white noise generated by the device 530-1 may partially diffuse ambient noise detected by the microphone of the device 500 and the device 500 may generate a reduced level of white noise to diffuse or block the ambient noise surrounding the device 500.

[0052] In some examples, the level of ambient noise detected by the device 530-1 may change resulting in a change in white noise generated by the device 530- 1 (e.g., level of white noise generated increases with an increase in ambient noise and level of white noise generated decreases with a decrease in ambient noise). In some examples, the white noise generator of the device 530-1 may be turned off or the device 530-1 may be moved outside the first threshold area 555 of the device 500. In some examples, the processor may detect the change in white noise generated by the device 530-1 or, utilizing the map, may detect the removal of the device 530-1 from the first threshold area 555 of the device 500. In such an example, the processor may instruct the white noise generator of the device 500 to increase the level of white noise generated when the device 530-1 generates a deceased level of white noise, is turned off, or is removed from the first threshold 555 of the device 500 or may instruct the white noise generator of the device 500 to decrease the level of white noise generated when the device 530-1 generates an increased level of white noise.

[0053] In some examples, the processor may instruct the level of white noise generated by any device located within the first threshold area 555 of the device 500 to a change based on a change in the level of white noise generated by the device 500. In some examples, the first threshold area 555 (e.g., the area surrounding the device 500 where ambient noise is monitored through the microphone of the device 500) of the device 500 may extend beyond the location of the device 530-1. In some examples, the remaining devices of the plurality of devices 530 may be located outside the first threshold area 555 of the device 500, but within the second threshold area 560 (e.g., the work area including a plurality of devices 530). In such an example, the level of white noise generated by the device 530-1 may change based on a change in the level of white noise generated by the device 500. However, the level of white noise generated by the remaining devices located outside the first threshold area 555 of the device 500 may be unaffected by the change in the level of white noise generated by the device 500. In this way, the change in the level of white noise generated by the device 500 may affect the level of white noise generated by a device located within the first threshold area 555 but may not affect the level of white noise generated by a device located within the second threshold area 560, but outside the first threshold area 555.

[0054] In some examples, the device 500 may detect ambient noise within the first threshold area 555. In some examples, the ambient noise may be a voice of another employee within the first threshold area 555. In such an example, the first threshold area 555 includes any ambient noise detected by the device 500. For example, an employee with a loud voice may be detected by the device 500, but an employee closer in proximity to the device 500 with a quieter voice may not be detected by the device 500. In such an example, the louder employee may be within the first threshold area 555, but the closer, quieter employee may be outside the first threshold area 555. In this way, the first threshold area 555 may not be a static area. [0055] In some examples, the user of the device 500 may communicate with another entity. In some examples, the device 500 may reduce the white noise generated or turn the white noise generator off to prevent interference with communication with the entity (e.g., feedback generated by a phone call, etc.). In such an example, other devices within the first threshold area 555 may be instructed to increase the white noise generated to compensate for the reduction in white noise generated by the device 500. In some examples, the device 500 may be able to determine the entity to be an external entity (e.g., phone call, zoom meeting, etc.). In such an example, the privacy level of the device 500 may be a high privacy level and the level of white noise generated by the devices within the first threshold area 555 may be increased to compensate for the level of privacy.

[0056] In some examples, the device 500 and the plurality of devices 530 transmit to a remote management device the levels of white noise generated and the levels of ambient noise detected. In such an example, the remote management device may manage the level of white noise generated by the device 500 and the plurality of devices 530 in response to the levels of white noise generated and the levels of ambient noise detected. In some examples, the device 500 and the plurality of devices 530 transmit and receive the levels of white noise generated and the levels of ambient noise detected. In this way, the device 500 and the plurality of devices 530 may manage the level of white noise generated absent the remote management device (e.g., management device failure). In some examples, the level of white noise generated by the device 500 and/or the plurality of devices 530 may be selected automatically based on a level determine by a processor (e.g., the management device processor, the device 500 processor, the plurality of devices 530 processors, etc.). In some examples, the level of white noise generated by the device 500 and/or the plurality of devices 530 may be manually selected by a user. In some examples, the processor may manage the rate of change in the level of white noise generated (e.g., timer included to prevent changing too often, minimizing disruption in the work environment).

[0057] In described herein, the device 500 and the plurality of devices 530 are centrally connected and synchronized. Thus, the device 500 and the plurality of devices 530 may be used as a PA system to provide information to the users of the devices.

[0058] In the foregoing detailed description of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which is shown by way of illustration how examples of the disclosure may be practiced. These examples are described in sufficient detail to enable those of ordinary skill in the art to practice the examples of this disclosure, and it is to be understood that other examples may be utilized and that process, electrical, and/or structural changes may be made without departing from the scope of the disclosure. Further, as used herein, “a” refers to one such thing or more than one such thing.

[0059] The figures herein follow a numbering convention in which the first digit corresponds to the drawing figure number and the remaining digits identify an element or component in the drawing. For example, reference numeral 102 may refer to element 102 in Figure 1 and an analogous element may be identified by reference numeral 302 in Figure 3. Elements shown in the various figures herein can be added, exchanged, and/or eliminated to provide additional examples of the disclosure. In addition, the proportion and the relative scale of the elements provided in the figures are intended to illustrate the examples of the disclosure and should not be taken in a limiting sense.

[0060] It can be understood that when an element is referred to as being "on," "connected to", “coupled to”, or "coupled with" another element, it can be directly on, connected, or coupled with the other element or intervening elements may be present. In contrast, when an object is “directly coupled to” or “directly coupled with” another element it is understood that are no intervening elements (adhesives, screws, other elements) etc.

[0061] The above specification, examples, and data provide a description of the system and methods of the disclosure. Since many examples can be made without departing from the spirit and scope of the system and method of the disclosure, this specification merely sets forth some of the many possible example configurations and implementations.

Claims

What is claimed is:

1. A device, comprising: a microphone; a white noise generator; and a processor to: monitor a level of ambient noise around the device utilizing the microphone; determine a level of white noise generated by the white noise generator in response to the level of ambient noise; and transmit the level of ambient noise and the level of white noise generated to a remote device with a corresponding white noise generator.

2. The device of claim 1 , wherein the processor is to: receive a level of white noise generated by the corresponding white noise generator of the remote device; and determine the level of white noise generated in response to the level of ambient noise and the level of corresponding white noise generated by the remote device.

3. The device of claim 2, wherein the processor is to: determine a signal strength between the device and the remote device; determine a distance between the device and the remote device based on the signal strength; and determine the level of white noise generated based on the distance.

4. The device of claim 2, wherein the processor is to receive the level of white noise generated by a plurality of additional remote devices from a remote management device.

5. The device of claim 1 , wherein the level of white noise generated includes a frequency of the white noise generated, an amplitude of the white noise generated, and a type of white noise generated.

6. A non-transitory memory resource storing machine-readable instructions stored thereon that, when executed, cause a processor of a computing device to: determine a level of ambient noise within a first threshold area of the computing device; determine a level of privacy for the first threshold area; instruct a white noise generator of the computing device to generate a level of white noise in response to the level of ambient noise and the level of privacy of the first threshold area; and transmit an instruction to a plurality of surrounding white noise generators corresponding to a plurality of devices within a second threshold area of the computing device, wherein the instruction includes the level of privacy and a corresponding level of white noise for the surrounding white noise generators.

7. The processor of claim 6, further comprising instructions to: determine an ambient noise type of the ambient noise; and instruct the white noise generator to generate a corresponding level of white noise based on the ambient noise type.

8. The processor of claim 6, further comprising instructions to: monitor a conversation of a user; compare the conversation of the user with a database of keywords; and determine the level of privacy based on the comparison of the conversation of the user to the keywords in the database.

9. The processor of claim 6, further comprising instructions to: monitor noise surrounding the first threshold area; compare the noise surrounding the first threshold area with a database of vocal data associated with a plurality of users; and calibrate the white noise generator based on the comparison.

10. A system, comprising: a plurality of devices; a plurality of white noise generators integrated into the plurality of devices; a plurality of microphones integrated into the plurality of devices; and a processor to: identify a first device of the plurality of devices; identify a second device of the plurality of devices; determine a signal strength between the first device and the second device; determine a distance between the first device and the second device based on the signal strength; determine a level of privacy for the first device based on the distance between the first device and the second device; and instruct a white noise generator of the first device to generate a level of white noise based on the level of privacy.

11. The system of claim 10, wherein the processor is to generate a map of an environment utilizing the distance determined between the first device and the second device.

12. The system of claim 11 , wherein the processor is to: identify a third device of the plurality of devices; and update the map utilizing a distance determined between the third device and the first device and a distance determined between the third device and the second device.

13. The system of claim 11, wherein the processor includes instructions to instruct the plurality of white noise generators to generate a level of white noise based on the map of the plurality of devices.

14. The system of claim 13, wherein the level of white noise generated by the plurality of white noise generators and ambient sound detected by the plurality of microphones is transmitted to a remote management device.

15. The system of claim 14, wherein the plurality of devices receive an instruction from the remote management device that indicates the level of white noise to be generated by the plurality of white noise generators based on the received level of ambient sound detected.