Abstract:
A wearable audio device having corresponding computer-readable media comprises: a processor; a microphone configured to provide first audio to the processor, wherein the first audio represents first sounds received by the microphone; and a loudspeaker configured to receive second audio from the processor, and to produce second sounds based on the second audio; wherein the processor is configured to generate a noise dose parameter based on the first audio.

Description:
FIELD 
       [0001]    The present disclosure relates generally to the field of audio processing. More particularly, the present disclosure relates to noise measurement in a wearable device. 
       BACKGROUND 
       [0002]    In a work environment, the accumulated amount of noise, or noise dose in terms of an average noise level, and the maximum level of noise to which an individual has been exposed during a workday, are important to occupational safety and to the health of the individual. Industry and governmental agencies in countries throughout the world, such as the Occupational Safety and Health Administration (OSHA) in the United States, require highly accurate noise data measurements. 
         [0003]    Noise dosimeters have been developed to obtain such noise data measurements. However, these dosimeters are expensive dedicated units that are purchased only for the purpose of obtaining highly accurate noise data measurements. Furthermore, these dosimeters must be calibrated on a regular basis, incurring further expense. 
       SUMMARY 
       [0004]    In general, in one aspect, an embodiment features a wearable audio device comprising: a processor; a microphone configured to provide first audio to the processor, wherein the first audio represents first sounds received by the microphone; and a loudspeaker configured to receive second audio from the processor, and to produce second sounds based on the second audio; wherein the processor is configured to generate a noise dose parameter based on the first audio. 
         [0005]    Embodiments of the apparatus can include one or more of the following features. Some embodiments comprise a don/doff sensor configured to provide don/doff information; wherein the processor determines whether the wearable audio device is being worn based on the don/doff information; and wherein the processor generates the noise dose parameter only responsive to determining the wearable audio device is being worn. In some embodiments, the noise dose parameter includes at least one of: a noise level; a noise dose; and a time-weighted average of a plurality of the noise doses. 
         [0006]    In some embodiments, the processor is further configured to cause the wearable audio device to generate a user-perceivable indication responsive to the noise dose parameter exceeding a selected threshold. Some embodiments comprise a transmitter; wherein the processor is further configured to cause the transmitter to transmit a signal representing the noise dose parameter. In some embodiments, the processor is further configured to determine a safe interval based on the noise dose parameter and a noise dose threshold, wherein the safe interval represents an interval during which further ones of the noise dose parameter will remain below the noise dose threshold; and the processor is further configured to cause the wearable audio device to generate a user-perceivable indication of the safe interval. Some embodiments comprise a location sensor configured to provide location information; and a transmitter; wherein the processor is further configured to determine a location associated with the noise dose parameter based on the location information; and wherein the processor is further configured to cause the transmitter to transmit a signal representing the noise dose parameter and the location associated with the noise dose parameter. Some embodiments comprise a monaural headset; and a detector configured to determine in which ear the monaural headset is being worn; wherein the processor is further configured to associate the noise dose parameter with the ear in which the monaural headset is not being worn. In some embodiments, the processor is further configured to determine a noise dose parameter for the ear in which the monaural headset is being worn based on i) the noise dose parameter for the ear in which the monaural headset is not being worn, and ii) an audio transfer function of the monaural headset. 
         [0007]    In general, in one aspect, an embodiment features computer-readable media embodying instructions executable by a computer in a wearable audio device to perform functions comprising: receiving first audio, wherein the first audio represents sounds received by a microphone of the wearable audio device; generating second audio, and providing the second audio to a loudspeaker of the wearable audio device; and generating a noise dose parameter based on the first audio. 
         [0008]    Embodiments of the computer-readable media can include one or more of the following features. In some embodiments, the functions further comprise: generating the noise dose parameter only responsive to the wearable audio device being worn. In some embodiments, the noise dose parameter includes at least one of: a noise level; a noise dose; and a time-weighted average of a plurality of the noise doses. In some embodiments, the functions further comprise: causing a user-perceivable indicator of the wearable audio device to generate a user-perceivable indication responsive to the noise dose parameter exceeding a selected threshold. In some embodiments, the functions further comprise: causing a transmitter of the wearable audio device to transmit a signal representing the noise dose parameter. In some embodiments, the functions further comprise: determining a safe interval based on the noise dose parameter and a noise dose threshold, wherein the safe interval represents an interval during which further ones of the noise dose parameter will remain below the noise dose threshold; and causing a user-perceivable indicator of the wearable audio device to generate a user-perceivable indication of the safe interval. In some embodiments, the functions further comprise: causing a transmitter of the wearable audio device to transmit a signal representing the noise dose parameter and a location associated with the noise dose parameter. In some embodiments, the wearable audio device is a monaural headset, and the functions further comprise: determining in which ear the monaural headset is being worn; and associating the noise dose parameter with the ear in which the monaural headset is not being worn. In some embodiments, the functions further comprise: determining a noise dose parameter for the ear in which the monaural headset is being worn based on i) the noise dose parameter for the ear in which the monaural headset is not being worn, and ii) an audio transfer function of the monaural headset. 
         [0009]    In general, in one aspect, an embodiment features computer-readable media embodying instructions executable by a computer in a portable audio device to perform functions comprising: providing a noise level map, wherein the noise level map comprises a respective noise level for each of a plurality of locations; generating a predicted noise parameter based on a location of the portable audio device and the noise level map; and causing a user-perceivable indication of the predicted noise parameter to be generated by a wearable audio device in communication with the portable device. 
         [0010]    Embodiments of the computer-readable media can include one or more of the following features. In some embodiments, the functions further comprise: generating navigation instructions based on a location of the portable device and the noise level map; and providing the instructions to a user by at least one of i) the wearable audio device, and ii) the portable device. 
         [0011]    The details of one or more implementations are set forth in the accompanying drawings and the description below. Other features will be apparent from the description and drawings, and from the claims. 
     
    
     
       DESCRIPTION OF DRAWINGS 
         [0012]      FIG. 1  illustrates a communication system according to one embodiment. 
           [0013]      FIG. 2  shows elements of the headset according to one embodiment. 
           [0014]      FIG. 3  shows elements of the smartphone of  FIG. 1  according to one embodiment. 
           [0015]      FIG. 4  shows a process for the headset of  FIGS. 1 and 2  according to one embodiment. 
           [0016]      FIG. 5  shows a noise level mapping process for the server of  FIG. 1  according to one embodiment. 
           [0017]      FIG. 6  shows an example noise level map according to one embodiment. 
           [0018]      FIG. 7  shows a noise level map utilization process for the smartphone of  FIG. 3  according to one embodiment. 
       
    
    
       [0019]    The leading digit(s) of each reference numeral used in this specification indicates the number of the drawing in which the reference numeral first appears. 
       DETAILED DESCRIPTION 
       [0020]    Embodiments of the present disclosure provide a personal noise meter in a wearable audio device. For convenience, the wearable audio device is described herein in terms of a headset having a microphone and loudspeaker. However, it will be understood that the wearable audio device may be implemented as any wearable device. For example, the wearable audio device may be implemented as a headset, bracelet, garment, or the like. Furthermore, the loudspeaker is not required. Other features are contemplated as well. 
         [0021]      FIG. 1  illustrates a communication system  100  according to one embodiment. Referring to  FIG. 1 , the communication system  100  includes a headset  102 , a smartphone  104 , an access point  106 , a mobile network  108 , the Internet  110 , a server  112 , and a public switched telephone network (PSTN)  114 . In the example of  FIG. 1 , the headset  102  is a wireless headset, and so may have a wireless connection to the smartphone  104 . However, in other embodiments, the headset  102  may be a wired headset, and so may have a wired connection to the smartphone  104 . 
         [0022]    The wireless connection between the headset  102  and the smartphone  104  may be of any type. For example, the wireless connection may be a Bluetooth link, a DECT link, or the like. The headset  102  may have a Wi-Fi connection to an access point  106 . The smartphone  104  may have a Wi-Fi connection to the access point  106 . The access point  106  may be connected to the Internet  110 . The smartphone  104  may have a mobile connection to the mobile network  108 . The mobile network  108  may be connected to the Internet  110  and to the PSTN  114 . The Internet  110  may be connected to the PSTN  114 . The server  112  may be connected to the Internet  110 . 
         [0023]      FIG. 2  shows elements of the headset  102  of  FIG. 1  according to one embodiment. Although in the described embodiment elements of the headset  102  are presented in one arrangement, other embodiments may feature other arrangements. For example, elements of the headset  102  may be implemented in hardware, software, or combinations thereof. 
         [0024]    Referring to  FIG. 2 , the headset  102  may include one or more microphones  202 , a loudspeaker  204 , a processor  206 , one or more transmitters  208 , one or more receivers  210 , a vibrator  212 , an LED  214 , an ear detector  216 , a location sensor  218 , a clock  220 , a memory  222 , and a don/doff sensor  224 . The headset  102  may include other elements as well. The transmitters  208  and receivers  210  may include wired and wireless transmitters  208  and receivers  210 . The elements of the headset  102  may be interconnected by direct connections, by a bus  226 , by a combination thereof, or the like. 
         [0025]      FIG. 3  shows elements of the smartphone  104  of  FIG. 1  according to one embodiment. Although in the described embodiment elements of the smartphone  104  are presented in one arrangement, other embodiments may feature other arrangements. For example, elements of the smartphone  104  may be implemented in hardware, software, or combinations thereof. 
         [0026]    Referring to  FIG. 3 , the smartphone  104  may include a microphone  302 , a loudspeaker  304 , a processor  306 , one or more transmitters  308 , one or more receivers  310 , a vibrator  312 , an LED  314 , a display  316 , a location sensor  318 , a clock  320 , and a memory  322 . The smartphone  104  may include other elements as well. The transmitters  308  and receivers  310  may include wired and wireless transmitters  308  and receivers  310 . The elements of the smartphone  104  may be interconnected by direct connections, by a bus  326 , by a combination thereof, or the like. 
         [0027]      FIG. 4  shows a process  400  for the headset  102  of  FIGS. 1 and 2  according to one embodiment. Although in the described embodiments the elements of process  400  are presented in one arrangement, other embodiments may feature other arrangements. For example, in various embodiments, some or all of the elements of process  400  can be executed in a different order, concurrently, and the like. Also some elements of process  400  may not be performed, and may not be executed immediately after each other. In addition, some or all of the elements of process  400  can be performed automatically, that is, without human intervention. In some embodiments, some of the steps may be performed by corresponding elements of the smartphone  104 , the server  112 , or a combination thereof. 
         [0028]    Referring to  FIG. 4 , at  402 , the processor  206  receives input audio from the microphone  202 . The input audio represents sounds received by the microphone  202 . In embodiments having a loudspeaker  204 , the processor  206  provides output audio to the loudspeaker  204 , and the loudspeaker  204  produces sounds based on the output audio. At  404 , the processor  206  determines whether the headset  102  is being worn based on information provided by the don/doff sensor  224 . At  406 , if the headset  102  is being worn, then at  408 , the processor  206  generates a noise dose parameter based on the input audio provided by the microphone  202 . 
         [0029]    In some embodiments, the processor  206  generates noise dose parameters only under certain conditions. For example, the processor  206  may generate noise dose parameters only when the headset  102  is located within a selected area such as the wearer&#39;s workplace. In such an embodiment, the noise dose parameters may represent only the noise exposure incurred within the scope of the wearer&#39;s employment. At  410 , the processor  206  may determine a location of the headset  102  based on location information provided by the location sensor  218 . At  412 , only when the location is within a selected area does the processor  206  generate a noise dose parameter, at  408 . The processor  206  may determine the location in any manner. For example, the location may be determined using triangulation on signals such as global positioning system (GPS) signals, digital television signals, cellular signals, Wi-Fi signals, or the like, using inertial navigation or the like, or any combination thereof. 
         [0030]    As another example, the processor  206  may generate noise dose parameters only during a selected interval such as the wearer&#39;s working hours. In such an embodiment, the noise dose parameters may represent only the noise exposure incurred within the scope of the wearer&#39;s employment. At  414 , the processor  206  may determine a time of day based on time information provided by the clock  220 . At  416 , only when the time of day is within a selected interval does the processor  206  generate a noise dose parameter, at  408 . 
         [0031]    The audio provided by the microphone  202  may represent not only vocal sounds of a user of the headset  102 , but also other sounds such as background noise, noise from particular noise sources, and the like. In some embodiments, the processor  206  generates the noise dose parameter based only on these other sounds. In some embodiments, the processor  206  generates the noise dose parameter based only on the vocal sounds. In some embodiments, the processor  206  generates the noise dose parameter based on both vocal sounds and background sounds. Any sort of technique may be used to distinguish the vocal sounds from the background sounds. For example, conventional voice activity detection may be used. 
         [0032]    The noise dose parameters are independent of device, and may be collected for an individual despite changing wearable audio devices. The noise dose parameter generated by the processor  206  may include a noise level, noise dose, a time-weighted average of a plurality of the noise doses, or the like, or any combination thereof. For example, a noise dose may be calculated as shown in equation (1). 
         [0000]      Noise Dose=100×( C 1/ T 1+ C 2/ T 2+ C 3/ T 3+ . . . + Cn/Tn )  (1)
 
         [0000]      where 
         [0000]        Tn= 8/(2**(( L− 90)/5))  (2)
 
         [0033]    L is the measured sound level, and Cn is the time spent at that noise level. Alternatively, a look-up table may be used. 
         [0034]    An eight-hour time-weighted average (TWA) may be calculated, for example, as shown in equation (3). 
         [0000]      TWA=16.61 Log 10( D/ 100)+90  (3)
 
         [0000]    where D is the noise dose, for example from equation (1), and Log 10 is the base-10 logarithm. 
         [0035]    When the headset  102  is a monaural headset, the ear detector  216  may determine in which ear the headset  102  is being worn. Because that ear is protected to some extent by the headset  102 , the processor  206  associates the noise dose parameter with the other ear. When the audio transfer function of the headset is known, the processor  206  may use the noise dose parameter and the audio transfer function to determine a noise dose parameter for the ear in which the headset  102  is being worn. For a binaural headset, the processor  206  may use the noise dose parameter and the audio transfer function to determine a noise dose parameter for both ears. 
         [0036]    At  418 , responsive to the noise dose parameter exceeding the selected threshold, at  420 , the processor  206  may cause the transmitter  208  to transmit the signal representing the noise dose parameter. The signal representing the noise dose parameter may be transmitted regularly, when the noise dose parameter exceeds a selected threshold, or both. The signal may be transmitted to the server  112  ( FIG. 1 ). The server  112  may use the noise dose parameters to build records detailing noise exposure for individuals, for groups, for locations, for areas, for intervals, and the like, or any combination thereof. 
         [0037]    At  418 , responsive to the noise dose parameter exceeding a selected threshold, at  422 , the processor  206  may cause a user-perceivable indicator to generate a user-perceivable indication. For example, the processor  206  may cause the loudspeaker  204  of the headset  102 , or the loudspeaker  304  of the smartphone  104 , to play a warning message. As another example, the processor  206  may cause the vibrator  212  of the headset  102 , or the vibrator  312  of the smartphone  104 , to vibrate. As another example, the processor  206  may cause the LED  214  of the headset  102 , or the LED  314  of the smartphone  104 , to turn on, change color, or flash. As another example, the processor  206  may cause the display  316  of the smartphone  104 , to display a warning message, icon, or the like. 
         [0038]    In some embodiments, the headset  102  may determine a safe interval during which the wearer of the headset  102  may safely continue to receive the noise dose. At  424 , the processor  206  determines a safe interval based on the noise dose parameter and a noise dose threshold. The safe interval represents an interval during which further noise dose parameters will remain below the noise dose threshold. At  426 , the processor  206  causes a user-perceivable indicator to generate a user-perceivable indication of the safe interval. For example, the processor  206  may cause the loudspeaker  204  of the headset  102 , or the loudspeaker  304  of the smartphone  104 , to play a message. As another example, the processor  206  may cause the display  316  of the smartphone  104  to display a message, icon, or the like. 
         [0039]    The processor  206  may sample the audio periodically according to a sampling period. At  418 , responsive to the noise dose parameter exceeding the selected threshold, at  428 , the processor  206  may reduce the sampling period. 
         [0040]    At  430 , the location sensor  218  may provide location information. At  432 , the processor  206  may determine a location associated with the noise dose parameter based on the location information. At  420 , the transmitted signal may include the location associated with the noise dose parameter. 
         [0041]    In some embodiments, the noise dose parameters and associated locations are used to generate and modify a noise level map.  FIG. 5  shows a noise level mapping process  500  for the server  112  of  FIG. 1  according to one embodiment. Although in the described embodiments the elements of process  500  are presented in one arrangement, other embodiments may feature other arrangements. For example, in various embodiments, some or all of the elements of process  500  may be executed in a different order, concurrently, and the like. Also some elements of process  500  may not be performed, and may not be executed immediately after each other. In addition, some or all of the elements of process  500  may be performed automatically, that is, without human intervention. In the described embodiment, the noise level map is generated by the server  112 . However, in various embodiments, the noise level map may be generated and modified by the headset  102 , by the smartphone  104 , by the server  112 , or any combination thereof. 
         [0042]    Referring to  FIG. 5 , at  502 , the server  112  receives a localized noise report. Each localized noise report includes a noise dose parameter generated by a headset  102  and the location where the noise dose parameter was determined. For example, the headset  102  may determine the noise dose parameter as described above. The processor  206  may also determine the location at the time the noise parameter was determined. The processor  206  may then associate the location and noise dose parameter to form a localized noise report, and then transmit the report to the server  112 . 
         [0043]    At  504 , the server  112  generates a noise level map based on the localized noise report. Any technique may be used to generate the noise level map. For example, the server  112  may generate a noise level index for the reported location based on the reported noise dose parameter. The noise level index may be expressed on a scale from one to four, for example. The map may be a heat map. For example, the heat map may be generated by digitally filtering the array of noise level indices, or the like. In some embodiments, noise level maps may be generated for selected times, days, weeks, months, years, and the like. The noise level maps have many uses. For example, the maps may be used to devise seating plans for individuals with high noise sensitivity. 
         [0044]    At  506 , the server  112  receives a further localized noise report. At  508 , the server  112  modifies the noise level map based on the further localized noise report. For example, if the reported location has no noise level index in the map, the server  112  generates a noise level index for the reported location in the map based on the reported noise dose parameter. But if the reported map location has a noise level index, the server  112  modifies the noise level index for that map location based on the existing noise level index and the reported noise dose parameter. The process  500  may resume, at  504 . 
         [0045]      FIG. 6  shows an example noise level map according to one embodiment. The noise level map shows a building  600  having a model shop  602 , three conference rooms  604 ,  606 ,  608 , and a testing area  610 . In this example, the noise level map is a heat map having only two values: acceptable and unacceptable. The noise level map shows two areas of unacceptable noise levels. One area  612  is associated with the model shop  602 , and could be caused by modeling machinery. Another area  614  is associated with the testing area  610 , and could be caused by test equipment. The remaining areas of the building  600  have acceptable noise levels. A user consulting the map to avoid high noise doses would probably avoid the model shop  602 , the testing area  610 , and conference rooms  604  and  608 , which are covered or partially covered by areas  612  and  614  respectively, and could move to conference room  606 , which is not covered by either of those areas  612 ,  614 . 
         [0046]    In some embodiments, the noise level map is used to predict the noise dose parameter based on the location of the smartphone  104 .  FIG. 7  shows a noise level map utilization process  700  for the smartphone  104  of  FIG. 3  according to one embodiment. Although in the described embodiments the elements of process  700  are presented in one arrangement, other embodiments may feature other arrangements. For example, in various embodiments, some or all of the elements of process  700  may be executed in a different order, concurrently, and the like. Also some elements of process  700  may not be performed, and may not be executed immediately after each other. In addition, some or all of the elements of process  700  may be performed automatically, that is, without human intervention. 
         [0047]    Referring to  FIG. 7 , at  702 , the headset  102  or smartphone  104  determines its location. The location may be determined in any manner. For example, the location may be determined using triangulation on signals such as global positioning system (GPS) signals, digital television signals, cellular signals, Wi-Fi signals, or the like, using inertial navigation or the like, or any combination thereof. 
         [0048]    At  704 , the smartphone  104  provides a noise level map. In some embodiments, the noise level map may be generated by the smartphone  104 , and may be stored in the memory  322  of the smartphone  104 . In some embodiments, the noise level map may be generated by the server  112 , and may be sent to the smartphone  104  by the server  112 . 
         [0049]    At  706 , the smartphone  104  generates a predicted noise dose parameter based on the location of the smartphone  104  and the noise level map. For example, the predicted noise dose parameter may be the noise level index associated with the location of the smartphone  104  by the noise level map. 
         [0050]    At  708 , the smartphone  104 , the headset  102 , or both generates a user-perceivable indication of the predicted noise dose parameter. For example, the processor  232  may send an audio message to the headset  102  that indicates the predicted noise dose parameter and, responsive to receiving that message, the headset  102  may play the message over its loudspeaker  204 . As another example, the smartphone  104  may display the indication of the predicted noise dose parameter on its display screen  234 . For example, the display screen  234  may show a heat map with the location of the smartphone  104  indicated thereon. 
         [0051]    In some embodiments, at  710 , the smartphone  104  provides user-perceivable navigation instructions based on the location of the smartphone  104  and the noise level map. For example, the instructions may guide the user away from areas where the predicted noise dose parameter is high, toward areas where the predicted noise dose parameter is low, and the like. In addition, the instructions may prompt the user to take some action, for example such as turning on automatic noise reduction in the headset  102 , donning a more protective headset  102 , and the like. 
         [0052]    Various embodiments of the present disclosure can be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations thereof. Embodiments of the present disclosure can be implemented in a computer program product tangibly embodied in a computer-readable storage device for execution by a programmable processor. The described processes can be performed by a programmable processor executing a program of instructions to perform functions by operating on input data and generating output. Embodiments of the present disclosure can be implemented in one or more computer programs that are executable on a programmable system including at least one programmable processor coupled to receive data and instructions from, and to transmit data and instructions to, a data storage system, at least one input device, and at least one output device. Each computer program can be implemented in a high-level procedural or object-oriented programming language, or in assembly or machine language if desired; and in any case, the language can be a compiled or interpreted language. Suitable processors include, by way of example, both general and special purpose microprocessors. Generally, processors receive instructions and data from a read-only memory and/or a random access memory. Generally, a computer includes one or more mass storage devices for storing data files. Such devices include magnetic disks, such as internal hard disks and removable disks, magneto-optical disks; optical disks, and solid-state disks. Storage devices suitable for tangibly embodying computer program instructions and data include all forms of non-volatile memory, including by way of example semiconductor memory devices, such as EPROM, EEPROM, and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM disks. Any of the foregoing can be supplemented by, or incorporated in, ASICs (application-specific integrated circuits). As used herein, the term “module” may refer to any of the above implementations. 
         [0053]    A number of implementations have been described. Nevertheless, various modifications may be made without departing from the scope of the disclosure. Accordingly, other implementations are within the scope of the following claims.