Selective sound enhancement and reduction

Abstract

The application discloses a method of identifying a user's voice, identifying the words used, generating an output signal that is composed of noiseless reference words that are equivalent to the actual identified words, where the noiseless reference words are of the user's own vocal patterns, then sending the output signal as a reduced noise communication that does not contain background noise. In effect rather than attempt to reduce the background noise in a real time acoustic communication, a clean real time communication is generated with the identified words of a user and streamed real-time without any background noise.

Description

Selective Sound Enhancement and Reduction CROSS REFERENCE TO RELATED APPLICATIONS AND PRIORITY

[0001] The present application claims priority to and the benefit of U.S. Provisional Patent Application No. 63528346, filed 21 Jul. 2023, the entirety of which is hereby incorporated by reference. FIELD OF THE APPLICATION

[0002] The present application relates to devices that detect voice and noise, and more particularly, though not exclusively, devices that can selectively remove or add acoustic signals. BACKGROUND

[0003] There are many methods of noise reduction either passive or active. In general noise reduction can be accomplished by playing an anti-noise signal and embedding it in emitted signals to reduce noise in a targeted spatial region. The anti-noise signal can target particular frequencies but typically not particular content.

[0004] Word and sound recognition can occur by analyzing the acoustic signal for recognized patterns, wherein a system attempts to find the start and end of a temporal signal and match spectral characteristics within that temporal span to learned pattern associated with a particular word. The difficultly being that the same word can be spoken with different temporal lengths.

[0005] The following references are useful in understanding the background of voice detection, voice assistance and noise reduction and should be reviewed during Examination: U.S. Patent 6,804,638 (Fiedler), U.S. Publication 2006 / 0195322A1 (Broussard), EP15196252 (Victorian), U.S. Publication 2008 / 0162133 (Couper), U.S. Publication 2003 / 0032447A1 (Bulthuis), U.S. Publication 2011 / 00267624 (Doclo), U.S. Publication 2006 / 0153394 (Beasley), U.S. Publication 2018 / 0115818 (Asada), U.S. Patent 6,567,524 (Svean), Sumit Basu et al., Smart Headphones: Enhancing Auditory Awareness Through Robust Speech Detection and Source Localization, 5 IEEE INT’L CONF. ON ACOUSTICS SPEECH & SIGNAL PROCESSING PROC. 3361 (2001) (“Basu”), U.S. Publication 2020 / 0380945A1 (Woodruff-1), U.S. Patent 11,393,486 (Woodruff-2), U.S. Publication 2003 / 0161097 (Le), U.S. Patent 7,430,299 (Armstrong), U.S. Patent 6,728,385 (Kvaloy), U.S. Publication 2004 / 0042103 (Mayer) and U.S. Publication 2006 / 0092043 (Lagassey).

[0006] It would be useful to have a system that can target content selectively. SUMMARY

[0007] Devices, system and methods for Acoustic translation to verbal text or vocal commands and control. The process described herein uses a method for word edge detection in an acoustic signal to define the start and end of a word. The start to end has a temporal extent. The temporal extent is shifted to a standard extent resulting in an adjusted temporal signal. The 1 77331874;2adjusted temporal signal associated with the word is then analyzed for spectral and phase properties. The spectral and phase properties are checked for a threshold level of analysis. If the threshold level has been exceeded, for example the average Sound Pressure Level (SPL) exceeds 65dB as compared to the background noise level (BNL), the properties are normalized. The normalized properties are then compared to stored normalized properties associated with known words. The known words are identified by comparing the properties, for example within a threshold. the threshold can be frequency dependent and time dependent. A time dependent threshold is one in which the threshold has been established for a frequency band in a spectrogram, and the threshold might change from the temporal start to the temporal end of the spectrogram for that particular frequency band.

[0008] Once the word has been identified the word can then be used to write the text of the word. Additionally, the word can be used to select a word audio signal that can be sent or used to clean up the original word or used instead of the original word. The cleaned word or reference to which the word was matched within the threshold difference arrays can then be used to improve communications. In other words rather than using noise reduction algorithms applied to the original signal for communication, the reference word can be placed in an outgoing signal that is heard by the person the user is communicating with, with no or very little noise. Essentially an English to English translator, if the words are in English (although any language can be used), where the output is a clean non noisy word. The reference word can be adjusted to fit the timespan of the original acoustic signal, for example the time between the forward edge and the rearward edge. SO if a person says the word slowly the refence word will be modified so that it also sounds as if the person is saying it slowly. Additionally in at least one embodiment, the refence word can be optionally amplitude matched to the originally extracted signal so that the amplitude of the conversation in the output signal composed of the identified refence words is at a normal intended conversational level in amplitude. Note that the refence words are generally noiseless, and the output signal (i.e., heard by a listener in a phone conversation with the user) will only hear the targeted audio, in non-limiting discussion herein the vocal communications.

[0009] Additional embodiments use learning models, an example is discussed, to identify particular words, or target sounds, remove the words, clean up the words and reinsert if desired. Alternatively targeted words, for example talking by another nearby person identified as not being the target person talking to, can be identified and removed prior to being sent to the speaker of a device.

[0010] These and other features of the sound detection / enhancement / reduction systems and methods are described in the following detailed description, drawings, and appended claims. BRIEF DESCRIPTION OF THE DRAWINGS 2 77331874;2

[0011] FIG.1 is a schematic of a process in accordance with at least one exemplary embodiment.

[0012] FIG.2 illustrates a microphone signal generated from a microphone.

[0013] FIG.3 illustrates the microphone signal being broken into time segments.

[0014] FIG.4 illustrates an amplitude spectrogram generated using spectral analysis of the time segments of Fig.3.

[0015] FIG.5 illustrates a phase spectrogram generated using spectral analysis of the time segments of Fig.3.

[0016] FIG.6 illustrates a process of comparing an amplitude spectrogram with a reference spectrogram.

[0017] FIG.7 illustrates a process of comparing an phase spectrogram with a reference spectrogram.

[0018] FIG.8 illustrates a process of comparing an difference spectrograms with threshold spectrograms.

[0019] FIG.9 illustrates a method prepare the microphone signal in anticipation of analysis.

[0020] FIG.10 illustrates a method of edge detection of the prepared microphone signal.

[0021] FIG.11 illustrates a method of reducing vocal noise by replacing the actual word with a stored cleaned version.

[0022] FIG.12 shows an audio spectrogram of the word “hot”.

[0023] FIG.13 shows the spectrogram of Fig.12 whose edges are expanded to a standard size.

[0024] FIG.14 illustrates the lines associated with the major amplitude peaks over time from FIG.13.

[0025] FIG.15 illustrates model lines and associated gaussian distribution at selected time steps used to generate the parameters used in learning models.

[0026] FIG.16 illustrates an earphone that can be used to implement embodiments.

[0027] FIG.17 illustrates a communication device (wearable such as a phone) that can be used to implement embodiments.

[0028] FIG.18 illustrates a communication device (wearable such as a tablet) that can be used to implement embodiments.

[0029] FIG.19 illustrates a communication device (wearable such as a watch) that can be used to implement embodiments.

[0030] FIG.20 illustrates a communication device (e.g., standalone such as a voice assistant device) that can be used to implement embodiments.

[0031] FIG.21 illustrates a communication device (wearable such as a smart eye glasses, 3 77331874;2virtual goggles) that can be used to implement embodiments.

[0032] FIG.22 illustrates a communication device (wearable such as a smart ring) that can be used to implement embodiments.

[0033] FIG 23 is a schematic diagram of a system for utilizing devices according to an embodiment of the present disclosure.

[0034] FIG.24 is a schematic diagram of a machine in the form of a computer system within which a set of instructions, when executed, may cause the machine to perform any one or more of the methodologies or operations of the systems and methods for utilizing a device according to embodiments of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0035] Exemplary embodiments of wearables and standalone devices (phones, earphones, watches, rings, bracelets, glasses, laptops, tablets, and other communication devices) are disclosed. Embodiments of the invention can be used on multiple devices and with networks to enhance audio clarity. Exemplary Embodiments

[0036] FIG. 1 illustrates one exemplary embodiment. An acoustic signal 400, for example from a microphone, (e.g., from a microphone) or a modified microphone signal (e.g., filtered, FFT, gain applied), wherein the signal can be a function of time or frequency, is retrieved for analysis (e.g., from memory). A check 410 is made to determine whether the signal 400 is of sufficient level (e.g., sound pressure level) to begin further analysis. For example, the pressure level, power level, is compared to a background noise level and optionally plus a threshold. When this occurs then, 420, a portion of the acoustic signal is extracted for analysis, (e.g., voltage vs time, amplitude vs. time). To analyze the portion for recognizable acoustic signals (e.g., a Word, drone identification, sound identification), the edges of such signals are detected. The extracted temporal portion is then analyzed 430 to determine the edges of individual words in the portion. Once the edges have been determined the temporal portions associated with individual words, between the edges, are extracted 440. For spectrogram analysis a standardized word is predetermined 450, for example a 2 second span or a 30 millisecond span. A longer standard word length enables one to capture length words, but also results in capture of multiple short words. This is handled by dealing with the portion between detected edges so that only one word is examined. So even if the real word is shorter than 2 seconds the temporal signal is expanded or contracted to fit the 2 second span, resulting in a standardized word for analysis. Another embodiment treats the span from edge to edge as the portion compressed or expanded into a standard word length or timespan. So, if a person says a word slower than normal, the portion between the edges is extracted and expanded into the standard word time length, that way whether 4 77331874;2a word is said quickly or dragged out similar spectrograms will exist when compressed or expanded into the standard word length. This changes the actual spectrum unless the standard word length happens to be the actual word length. The learning models can train on the standard word length spectrograms or the actual unprocessed spectrograms, in the embodiments discussed herein the spectrograms are those of the standard word model lengths. Once the temporal portion is expanded or contracted to fit the standard word model length (450) the standardized word properties are then extracted 460, for example spectral analysis, normalized temporal signal, etc. A spectrogram is generated from the temporal portion that has been fit within the standard word length. The spectrogram can be normalized so that the lowest portion is 0 while the largest portion is 1.0. The temporal steps of the spectrogram can be standardized with the word length standardization. For example, if the standard word length (SWL) is 2 seconds, then the temporal length (TL) can be chosen to be some % of the standard word length, for example 1% to 50%.

[0037] So if the TL is 10% then for a SWL of 2 seconds, TL=.2 seconds. Thus, the frequency component of the normalized spectrogram is acquired from analyzing (e.g., FFT) the temporal portion between t=0 to t=0.2 seconds. The next from t=0.2 to t=0.4 second and so on. Note that herein we refer to a normalized spectrogram, however normalization is not needed. It does help if a word is spoken softly compared to loudly, each is compressed or expanded into a normalized spectrogram, but it is not a necessity. Note that in addition to an amplitude form spectrogram (e.g., intensity as a function of frequency and time, power spectral density as a function of frequency and time, other amplitude related spectrograms) the phase as a function of frequency and time can also be used as added information. Thus, an additional spectrogram, a phase as a function of frequency and time can be used. Once the spectrograms have been derived for the extracted acoustic signal portion, the properties (e.g., spectrograms) can be compared 470 with a database 480 of reference values to attempt an identification. If no identification is successful then the extracted portion can be added to the database as a new acoustic signal to be matched later (e.g., from internet searching, remote query). For example, if the extracted acoustic portion does not match reference data for a local database (e.g., English words, vehicle signatures, wildlife sounds), the system can inquiry over wireless connection other language databases to determine if the portion matches other language words. The system can then notify the user the language being used and other information (e.g., English equivalent). If the identification is successful 490 then a notification can be sent to the user. Additionally, or alternatively, now that the word has been identified, the stored word can be used to clean up the spoken word, since the databased version will not have noise embedded. Thus, the identified word from the database can be expanded or contracted (495) to fit within the identified edges of the original sound portion, the original sound portion removed from the stored signal stream with the reference word inserted at 5 77331874;2similar amplitude, resulting in a clearer word (reduced noise), and the modified signal sent to a speaker in the device.

[0038] FIG.2 illustrates a microphone signal 1220 generated from a microphone 1200, having an initial time span 1210 between edges. Note that the microphone signal may be longer than 1210, for example a microphone signal may be 5 seconds while an acoustic signal of interest s1(t) embedded in the microphone signal might have a time span defined by its temporal edges of 2 seconds. Wherein an edge is defined as the temporal onset of an acoustic signal of interest s1(t) in the microphone signal. In the illustration of FIG.2 the microphone and acoustic signal of interest happen to be the same temporal length. When the edges are detected the acoustic signal s1(t) 1300 can be extracted (FIG.3) and divided into temporal segments 1310 within which spectral analysis 1320 (e.g., FFT, DFT) can be preformed to form spectrograms (e.g., 1400, 1500).

[0039] FIG.4 illustrates an amplitude spectrogram generated using spectral analysis of the time segments of Fig.3. The amplitude can be intensity, power spectral density, voltage amplitude, or any other spectral components that can be used in a spectrogram of amplitude versus time.

[0040] FIG.5 illustrates a phase spectrogram generated using spectral analysis of the time segments of Fig.3. The phase component result of the spectral analysis can also be plotted as a spectrogram (phase spectrogram), that can also be used for analysis.

[0041] FIG.6 illustrates a process of comparing an amplitude spectrogram with a reference spectrogram. A reference amplitude spectrum 1620 can be extracted from the reference amplitude pattern database 1600. The amplitude pattern database 1600 contains training spectrograms (e.g., for the learning model), and updated spectrograms for sound signal identification (e.g., alarms, animal noises, words). The reference spectrogram 1620 is compared 1630 to the amplitude spectrogram 1610 to generate a difference spectrogram 1640. The difference spectrogram 1640 can be compared later to a threshold array to isolate which reference spectrogram can be identified to most closely match the amplitude spectrogram. Alternatively, several spectrograms can be selected that most closely match (smallest total amplitude difference spectrogram 1640) then a phase difference spectrogram, discussed next, can be used to isolate which of the several amplitude reference spectrograms 1620 most likely matches the amplitude spectrogram 1610.

[0042] FIG.7 illustrates a process of comparing a phase spectrogram 1710 with a reference phase spectrogram 1720. A reference phase spectrogram 1720 can be extracted from a phase pattern database 1700. As with a reference amplitude spectrogram 1620 the reference phase spectrogram 1720 can be associated with an identified acoustic signal (e.g., spoken word, 6 77331874;2machine noise, animal call, music sample). The phase spectrogram 1710 can then be compared 1730 with the reference phase spectrogram 1720 to generate a phase difference spectrogram 1740.

[0043] FIG.8 illustrates a process of comparing difference spectrograms (1810, 1860) with threshold spectrograms (1820, 1870). To identify the acoustic signal the amplitude difference spectrogram 1810 is compared 1830 to a threshold array 1820. In the comparison certain array pixels can be weighted more. For example, for a low frequency alarm the amplitude difference spectrogram 1810 elements (pixels) that are associated within a certain low frequency bandwidth can be emphasized, for example the amplitude difference spectrogram can be multiplied by an emphasis (weighting) matrix prior to comparison with the threshold array. Then the sum difference of the amplitude difference spectrogram (array) 1810 with the threshold array 1, 1820 can be calculated and compared to a threshold value. If the calculated value is less than the threshold value then a possible identification can be recorded. Which can later be verified by comparing 1880 the phase difference array (spectrogram) 1860 with a second threshold array 1870. If 1810 is within the threshold array 1820 (i.e., equal to or less than) then 1860 is compared to a second threshold array 1870. If 1860 is within 1870 then a positive identification has occurred 1885, if not a negative identification 1890 has occurred and new references 1620 and 1720 can be examined. The identified acoustic signal or word 1895 can then be written (e.g., text message, email), and / or displayed (e.g., wearable display), and / or acoustically communicated. 1895 can now be used to clean up the original acoustic signal prior to being sent to communication, for example sent to speaker in the user’s earphone, or to a remote caller for clearer communication. Likewise multiple words and acoustics signals embedded in the normalized spectrogram can be identified in a similar manner, by focusing on frequency bands and overlapping patterns. Then a several of the identified acoustic signals and / or words can be selectively noise reduced while other identified words are removed from the communicated signal. For example, if the system is trained on the user’s voice, and background noise can be removed by constructing a communication signal that only includes identified words spoken by the user. Thus, a remote caller will only hear the user speaking in a very noisy environment without the noisy environment, since there is no attempt to use an anti-noise against the noisy environment but rather construct a new communication signal with only the selected identified word components. Note that multiple microphones can be analyzed, for example an ear canal microphone in conjunction with at leads on ambient sound microphone if user vocalization is desired to be identified.

[0044] FIG.9 and FIG.10 illustrate an exemplary embodiment of edge detection to isolate acoustic signals to be analyzed. A microphone 1900 measured sound an generates a microphone 7 77331874;2signal that includes a portion s1(t) 1920 of length 1910. A portion of the microphone signal 1930, including s1(t) , is sent to memory for analysis. In one exemplary embodiment the absolute value is obtained generating a new signal 1940. The slope of the new signal 1940 can be used to generate a slope signal 1950. The slope signal can be compared to a threshold 1970 to detect edge start 1960 and edge end 1965 of an acoustic signal of interest. The signal of interest can be extracted 1980 between the edges forming the signal to be analyzed. FIG. 10 illustrates a second exemplarily method of edge detection. A microphone 2000 generates a microphone signal 2020 of span 2010. An envelop can be used to detect edges. An envelop of the positive amplitude 2040 and / or the envelop of the negative amplitude 2050 can be used to detect edges of the signal of interest. Additionally, the slope 2060 of the positive envelop 2040 can be used to detect a forward edge 2070 and a rearward edge 2080. Additionally, the slope 2085 of 2060 can be used as well to detect the forward edge 2086 and the rearward edge 2087. By comparing the 2060 and / or 2085 to thresholds the edges can be determined.

[0045] FIG.11 illustrates a method of reducing vocal noise by replacing the actual word with a stored cleaned version. The word or acoustic signals properties are compared 470 to a database of references 480 to identify words 490. The output signal to be sent to a speaker or over wireless communication can be composed 1800 of identified words from the reference database minimizing any noise. The microphone acoustic signal is analyzed to see if the communication portion has ended (e.g., no one is talking anymore) 2110. If the acoustic signal is not ended 440 then the identification and replacement steps are repeated adding to an output signal. When the output signal has been constructed with the clean identified words then the output signal can be sent. Note that the clean version of the output signal can be sent in real time as it is being constructed with identified words. This avoids any background noise since the original signal is not being noise reduced rather the output signal is being constructed from scratch in real time. Thus, a person on the other end of a phone call will only hear the constructed output signal containing modified reference words which do not contain the background noise of the user speaking the original words. Note that the user can select which background noises to include in the constructed output signal and in that case selected background noises from the original signal will be added to the output signal. For example, suppose you are at a concert and you want the person you are having a phone conversation with to hear your voice (constructed of identified refence words) but also the band in the background. In that case the user can specify that background music be allowed to pass, and the algorithm will strip out non vocal music and add it to the output signal along with the noiseless vocal communication.

[0046] FIG.12 shows an audio spectrogram of and acoustic signal. In the example shown 8 77331874;2the spectrogram is of the word “hot” of the microphone signal. After edge detection the target signal can be expanded to a standard word length as discussed above and a spectrogram formed (FIG. 13). FIG.14 illustrates the lines associated with the major amplitude peaks 2400 over time from FIG. 13. FIG.15 illustrates model lines and associated gaussian distribution at selected time steps used to generate the parameters used in learning models. The equations of the fit lines can be expressed as;

[0047] (1) ^^^^= ^^1 ^^+ ^^2 ^^^^^^+ ^^3 ^^^^^^2+ ^^4 ^^^^^^3+ ^^5 ^^^^^^5

[0048] Note that the amplitude can also change along the ithfit line.

[0049] (2) ^^^^ ^^൫ ^^^^, ^^^^൯ = ^^1 ^^ ^^+ ^^2 ^^ ^^^^^^+ ^^3 ^^ ^^^^^^2+ ^^4 ^^ ^^^^^^3+ ^^5 ^^ ^^^^^^+ ^^6 ^^ ^^^^^^2+ ^^7 ^^ ^^^^^^3+ ^^ ^^

[0050] Note that (1) can use to replace ^^^^with ^^^^terms in (2).

[0051] Additionally, each position ^^^^and ^^^^, can be associated with a gaussian distribution in frequency about the position. 2 −(( ^^− ^^^^ ^^)− ^^^^ ^^)^^ ൫ ^12 ^^^^ ^^2^^ ^^^^^, ^^^^൯ = ^^ associated Gij or mij and sij.

[0054] For learning models the parameters used for the neural network are, a1ij, a2ij, a3ij, a4ij, a5ij, b1ij, b2ij, b3ij, b4ij, b5ij, b6ij, b7ij, b8ij, mij and sij, for i=1 to n, and j=1 to m. For example, rather than just raw pixels being used as simulated neurons, these parameters form the basis of a neural net. For example, a set number of fit lines, e.g., n=5, can be used for a normalized spectrogram with m=8 spectral temporal segments and k (e.g., 100) frequency segments. Then these parameters can be compared to reference values to identify acoustic signals in the normalized spectrograms. Thus, the actual temporal signals are converted into normalized spectrograms of standard word length (i.e. a chosen temporal length), the normalized spectrograms are converted into parameters of the equations above. These parameters are used in a neural network for a learning program as the neuron equivalents, each with their own weights (e.g., wa1ijfor a1ij) for example:

[0055] (4) W=∑^^, ^^^^ ^^1^^ ^^^^1^^ ^^+∑^^ , ^^^^ ^^2^^ ^^^^2^^ ^^+⋯

[0056] FIGs.16-22 illustrate various systems and devices that can implement various embodiments.

[0057] FIG.16 illustrates an earpiece, earphone, headset, earplug, hearing aid, 500 which can include 510 an eartip, made of foam, polymer, inflatable, balloon, and can be expandable; can include 520 an acoustic channel, which carries and / or directs acoustic energy from speaker, microphone, or even to / from sensors, can also include inflatable channel. 500 can include 530 a 9 77331874;2biosensor, such as amperometric sensors, potentiometric sensors, impedimetric sensors, voltametric sensors, electromagnetic sensors, light sensors (e.g., IR), acoustic sensors, electrochemical sensor, optical based sensors, location determination sensors (e.g., GPS, inertial sensors), thermal and piezoelectric sensor and other as known by one of ordinary skill in biosensor design. 500 can also include at least one 540 microphone, such as transducers, MEMs, electrofluid / coils / electrodes, hydrophones, and other as known by one of ordinary skill in microphone design; a 550 speaker, such as transducers, MEMs, electrofluid / coils / electrodes, hydrophones, and other as known by one of ordinary skill in speaker design; can include 555 memory, such as RAM, DRAM, static RAM, Double Data Rate SDRAM, hard drive, Rambus Dynamic RAM, read-only memory, quantum memory, and other as known by one of ordinary skill in memory design. The device 500 can include 560 a processor, circuit, logic circuit (e.g., composed of parts of processor established by the processor executing instructions to isolate parts to use in a particular order) and other as known by one of ordinary skill in integrated circuit design and manufacturing. Note in general referral to a processor and operations and / or functions performed, does not mean that such operations and functions are performed by one processor. Each function and or operation can be performed by separate processors and structure is intended to be conveyed. The device 500 can also include at least one ambient microphone 565, a sensor 570 sensor, such as amperometric sensors, potentiometric sensors, impedimetric sensors, voltametric sensors, electromagnetic sensors, light sensors (e.g., IR), acoustic sensors, electrochemical sensor, optical based sensors, location determination sensors (e.g., GPS, inertial sensors), magnetometer, gravitometer, thermal and piezoelectric sensor and other as known by one of ordinary skill in sensor design. The device 500 can also include a battery 580 or energy storage device, such as solar cells, fuel cells, bioenergy, micro engine, motion energy storage, lithium-ion battery, alkaline battery, carbon zinc battery, silver oxide battery, zinc air battery, NiCd battery, NiMH battery, and other as known by one of ordinary skill in battery or microenergy supply design. The device 500 can also include a housing 585, such as 3D printed material, moldable material, plastic, metal, and other as known by one of ordinary skill in earphone housing design and manufacturing, and an array microphone 590. Note that the housing 585 can be fabricated from material that converts light to electricity and recharges battery constantly while worn, extending battery (e.g., solar cell plastic)

[0058] FIG.17 illustrates another wearable (e.g., computer tablet) 600 (e.g., Samsung Galaxy Tab S8), having a tablet display 610, e.g., LED, touchscreen (also a user interactive element), a microphone 620, a speaker 630 and a user interactive element 640, (e.g., button). 10 77331874;2

[0059] FIG.18 illustrates another wearable 700 phone (e.g., Samsung Galaxy S23) having a display 710 (e.g., also user interface touchscreen), a microphone 720, a speaker 730, and a user interface 740.

[0060] FIG.19 illustrates another wearable 800 watch, having a display 810 and / or user interface, a speaker 820, a user interactive element 830 (also referred to as user interface) and additional user interface 840 and a biometric sensor 850.

[0061] FIG. 20 illustrates a voice assistant 900 that can include a display 910, a microphone 930, and a second microphone 940.

[0062] FIG. 21 illustrates another wearable device a 1000 eye glass, virtual goggle, mixed reality goggle, which can include a microphone 1010, visual projector 1020 or eyeglass lens can be semi transparent with embedded semi transparent LEDs, and visual projector 1030 rays.

[0063] FIG. 22 illustrates a ring or bracelet wearable 1100, that can include a user interface 1110, (e.g., button, microphone) a housing 1120, can also include sensors for user interaction or biosensors, batteries, processors, a transmitter 1130 for wireless communication, and a biosensor 1140 (biometric sensor).

[0064] FIG 23 is a schematic diagram of a system for utilizing devices according to an embodiment of the present disclosure.

[0065] FIG.24 is a schematic diagram of a machine in the form of a computer system within which a set of instructions, when executed, may cause the machine to perform any one or more of the methodologies or operations of the systems and methods for utilizing a device according to embodiments of the present disclosure. System Connectivity for Facilitating the Operation and Functionality of the System

[0066] As shown in Figure 23, a system 100 and methods for utilizing embodiments of the invention are shown.

[0067] The system 100 may be configured to support, but is not limited to supporting, data and content services, audio processing applications and services, audio output and / or input applications and services, applications and services for transmitting and receiving audio content, authentication applications and services, computing applications and services, cloud computing services, internet services, satellite services, telephone services, software as a service (SaaS) applications, platform-as-a-service (PaaS) applications, gaming applications and services, social media applications and services, productivity applications and services, voice-over-internet protocol (VoIP) applications and services, speech-to-text translation applications and services, interactive voice applications and services, mobile applications and services, and any other computing applications and services. The system may include a first user 101, who may utilize a first user device 102 to access data, content, and applications, or to perform a variety of other tasks 11 77331874;2and functions. As an example, the first user 101 may utilize first user device 102 to access an application (e.g. a browser or a mobile application) executing on the first user device 102 that may be utilized to access web pages, data, and content associated with the system 100. In certain embodiments, the first user 101 may be any type of user that may potentially desire to listen to audio content, such as from, but not limited to, a music playlist accessible via the first user device 102, a telephone call that the first user 101 is participating in, audio content occurring in an environment in proximity to the first user 101, any other type of audio content, or a combination thereof. For example, the first user 101 may be an individual that may be participating in a telephone call with another user, such as second user 120, and embodiments herein can be used to improve communications.

[0068] The first user device 102 utilized by the first user 101 may include a memory 103 that includes instructions, and a processor 104 that executes the instructions from the memory 103 to perform the various operations that are performed by the first user device 102. In certain embodiments, the processor 104 may be hardware, software, or a combination thereof. The first user device 102 may also include an interface 105 (e.g. screen, monitor, graphical user interface, etc.) that may enable the first user 101 to interact with various applications executing on the first user device 102, to interact with various applications executing within the system 100, and to interact with the system 100 itself. In certain embodiments, the first user device 102 may include any number of transducers, such as, but not limited to, microphones, speakers, any type of audio- based transducer, any type of transducer, or a combination thereof. In certain embodiments, the first user device 102 may be a computer, a laptop, a tablet device, a phablet, a server, a mobile device, a smartphone, a smart watch, smart ring, and / or any other type of computing device. Illustratively, the first user device 102 is shown as a mobile device in Figure 23. The first user device 102 may also include a global positioning system (GPS), which may include a GPS receiver and any other necessary components for enabling GPS functionality, accelerometers, gyroscopes, sensors, and any other componentry suitable for a mobile device. Many different types of processors can be used for example digital signal processor, such as Qualcomm QCC series of chips, Apple H1 chip, Sony QN1e chip, Samsung Exynos chips (e.g., W920), M2 chip, A14 Bionic chip, Apple S9 chip, Qualcomm Snapdragon Wear 4100+ chip, Oura Ring Gen 3 Processor, Huawei Kirin A1 chip, Ambid Apollo 4 chip, NVIDIA GPU chips, and others as know by one of ordinary skill in AI or wearable products. The term processor herein is meant to convey structure, a set of physical circuits that can be utilized or not depending upon the instructions stored in memory.

[0069] In addition to using first user device 102, the first user 101 may also utilize and / or have access to a second user device 106 and a third user device 110. As with first user device 102, the 12 77331874;2first user 101 may utilize the second and third user devices 106, 110 to transmit signals to access various online services and content. The second user device 106 may include a memory 107 that includes instructions, and a processor 108 that executes the instructions from the memory 107 to perform the various operations that are performed by the second user device 106. In certain embodiments, the processor 108 may be hardware, software, or a combination thereof. The second user device 106 may also include an interface 109 that may enable the first user 101 to interact with various applications executing on the second user device 106 and to interact with the system 100. In certain embodiments, the second user device 106 may include any number of transducers, such as, but not limited to, microphones, speakers, any type of audio-based transducer, any type of transducer, or a combination thereof. In certain embodiments, the second user device 106 may be and / or may include a computer, any type of sensor, a laptop, a set-top- box, a tablet device, a phablet, a server, a mobile device, a smartphone, a smart watch, and / or any other type of computing device. Illustratively, the second user device 102 is shown as a smart watch device in Figure 23.

[0070] The third user device 110 may include a memory 111 that includes instructions, and a processor 112 that executes the instructions from the memory 111 to perform the various operations that are performed by the third user device 110. In certain embodiments, the processor 112 may be hardware, software, or a combination thereof. The third user device 110 may also include an interface 113 that may enable the first user 101 to interact with various applications executing on the second user device 106 and to interact with the system 100. In certain embodiments, the third user device 110 may include any number of transducers, such as, but not limited to, microphones, speakers, any type of audio-based transducer, any type of transducer, or a combination thereof. In certain embodiments, the third user device 110 may be and / or may include a computer, any type of sensor, a laptop, a set-top-box, a tablet device, a phablet, a server, a mobile device, a smartphone, a smart watch, and / or any other type of computing device. Illustratively, the third user device 110 is shown as a smart watch device in Figure 23.

[0071] The first, second, and / or third user devices 102, 106, 110 may belong to and / or form a communications network 116. In certain embodiments, the communications network 116 may be a local, mesh, or other network that facilitates communications among the first, second, and / or third user devices 102, 106, 110 and / or any other devices, programs, and / or networks of system 100 or outside system 100. In certain embodiments, the communications network 116 may be formed between the first, second, and third user devices 102, 106, 110 through the use of any type of wireless or other protocol and / or technology. For example, the first, second, and third user devices 102, 106, 110 may communicate with one another in the communications network 116, such as by utilizing Bluetooth Low Energy (BLE), classic Bluetooth, ZigBee, cellular, NFC, Wi- 13 77331874;2Fi, Z-Wave, ANT+, IEEE 802.15.4, IEEE 802.22, ISA100a, infrared, ISM band, RFID, UWB, Wireless HD, Wireless USB, any other protocol and / or wireless technology, satellite, fiber, or any combination thereof. Notably, the communications network 116 may be configured to communicatively link with and / or communicate with any other network of the system 100 and / or outside the system 100.

[0072] The system 100 may also include an earphone device 115, which the first user 101 may utilize to hear and / or audition audio content, transmit audio content, receive audio content, experience any type of content, process audio content, adjust audio content, store audio content, perform any type of operation with respect to audio content, or a combination thereof. The earphone device 115 may be an earpiece, a hearing aid, an ear monitor, an ear terminal, a behind- the-ear device, any type of acoustic device, or a combination thereof. The earphone device 115 may include any type of component utilized for any type of earpiece. In certain embodiments, the earphone device 115 may include any number of ambient sound microphones that may be configured to capture and / or measure ambient sounds and / or audio content occurring in an environment that the earphone device 115 is present in and / or is proximate to. In certain embodiments, the ambient sound microphones may be placed at a location or locations on the earphone device 115 that are conducive to capturing and measuring ambient sounds occurring in the environment. For example, the ambient sound microphones may be positioned in proximity to a distal end (e.g. the end of the earphone device 115 that is not inserted into the first user's 101 ear) of the earphone device 115 such that the ambient sound microphones are in an optimal position to capture ambient or other sounds occurring in the environment. In certain embodiments, the earphone device 115 may include any number of ear canal microphones, which may be configured to capture and / or measure sounds occurring in an ear canal of the first user 101 or other user wearing the earphone device 115. In certain embodiments, the ear canal microphones may be positioned in proximity to a proximal end (e.g. the end of the earphone device 115 that is inserted into the first user's 101 ear) of the earphone device 115 such that sounds occurring in the ear canal of the first user 101 may be captured more readily.

[0073] The earphone device 115 may also include any number of transceivers, which may be configured transmit signals to and / or receive signals from any of the devices in the system 100. In certain embodiments, a transceiver of the earphone device 115 may facilitate wireless connections and / or transmissions between the earphone device 115 and any device in the system 100, such as, but not limited to, the first user device 102, the second user device 106, the third user device 110, the fourth user device 121, the fifth user device 125, the earphone device 130, the servers 140, 145, 150, 160, and the database 155. The earphone device 115 may also include any number of memories for storing content and / or instructions, processors that execute the 14 77331874;2instructions from the memories to perform the operations for the earphone device 115, and / or any type integrated circuit for facilitating the operation of the earphone device 115. In certain embodiments, the processors may comprise, hardware, software, or a combination of hardware and software. The earphone device 115 may also include one or more ear canal receivers, which may be speakers for outputting sound into the ear canal of the first user 101. The ear canal receivers may output sounds obtained via the ear canal microphones, ambient sound microphones, any of the devices in the system 100, from a storage device of the earphone device 115, or any combination thereof.

[0074] The ear canal receivers, ear canal microphones, transceivers, memories, processors, integrated circuits, and / or ear canal receivers may be affixed to an electronics package that includes a flexible electronics board. The earphone device 115 may include an electronics packaging housing that may house the ambient sound microphones, ear canal microphones, ear canal receivers (i.e. speakers), electronics supporting the functionality of the microphones and / or receivers, transceivers for receiving and / or transmitting signals, power sources (e.g. batteries and the like), any circuitry facilitating the operation of the earphone device 115, or any combination thereof. The electronics package including the flexible electronics board may be housed within the electronics packaging housing to form an electronics packaging unit. The earphone device 115 may further include an earphone housing, which may include receptacles, openings, and / or keyed recesses for connecting the earphone housing to the electronics packaging housing and / or the electronics package. For example, nozzles of the electronics packaging housing may be inserted into one or more keyed recesses of the earphone housing so as to connect and secure the earphone housing to the electronics packaging housing. When the earphone housing is connected to the electronics packaging housing, the combination of the earphone housing and the electronics packaging housing may form the earphone device 115. The earphone device 115 may further include a cap for securing the electronics packaging housing, the earphone housing, and the electronics package together to form the earphone device 115. Note that embodiments do not have to be earphone devices 15, but can be any wearable device or even a standalone device having at least a portion of the embodiment software operating.

[0075] In addition to the first user 101, the system 100 may include a second user 120, who may utilize a fourth user device 121 to access data, content, and applications, or to perform a variety of other tasks and functions. Much like the first user 101, the second user 120 may be may be any type of user that may potentially desire to listen to audio content, such as from, but not limited to, a storage device of the fourth user device 121, a telephone call that the second user 120 is participating in, audio content occurring in an environment in proximity to the second user 120, any other type of audio content, or a combination thereof. For example, the second user 120 may 15 77331874;2be an individual that may be listening to songs stored in a playlist that resides on the fourth user device 121. Also, much like the first user 101, the second user 120 may utilize fourth user device 121 to access an application (e.g. a browser or a mobile application) executing on the fourth user device 121 that may be utilized to access web pages, data, and content associated with the system 100. The fourth user device 121 may include a memory 122 that includes instructions, and a processor 123 that executes the instructions from the memory 122 to perform the various operations that are performed by the fourth user device 121. In certain embodiments, the processor 123 may be hardware, software, or a combination thereof. The fourth user device 121 may also include an interface 124 (e.g. a screen, a monitor, a graphical user interface, etc.) that may enable the second user 120 to interact with various applications executing on the fourth user device 121, to interact with various applications executing in the system 100, and to interact with the system 100. In certain embodiments, the fourth user device 121 may include any number of transducers, such as, but not limited to, microphones, speakers, any type of audio-based transducer, any type of transducer, or a combination thereof. In certain embodiments, the fourth user device 121 may be a computer, a laptop, a tablet device, a phablet, a server, a mobile device, a smartphone, a smart watch, and / or any other type of computing device. Illustratively, the fourth user device 121 may be a computing device in Figure 23. The fourth user device 121 may also include any of the componentry described for first user device 102, the second user device 106, and / or the third user device 110. In certain embodiments, the fourth user device 121 may also include a global positioning system (GPS), which may include a GPS receiver and any other necessary components for enabling GPS functionality, accelerometers, gyroscopes, sensors, and any other componentry suitable for a computing device.

[0076] In addition to using fourth user device 121, the second user 120 may also utilize and / or have access to a fifth user device 125. As with fourth user device 121, the second user 120 may utilize the fourth and fifth user devices 121, 125 to transmit signals to access various online services and content. The fifth user device 125 may include a memory 126 that includes instructions, and a processor 127 that executes the instructions from the memory 126 to perform the various operations that are performed by the fifth user device 125. In certain embodiments, the processor 127 may be hardware, software, or a combination thereof. The fifth user device 125 may also include an interface 128 that may enable the second user 120 to interact with various applications executing on the fifth user device 125 and to interact with the system 100. In certain embodiments, the fifth user device 125 may include any number of transducers, such as, but not limited to, microphones, speakers, any type of audio-based transducer, any type of transducer, or a combination thereof. In certain embodiments, the fifth user device 125 may be and / or may include a computer, any type of sensor, a laptop, a set-top-box, a tablet device, a phablet, a server, 16 77331874;2a mobile device, a smartphone, a smart watch, smart ring, smart bracelet and / or any other type of computing or communication device. Illustratively, the fifth user device 125 is shown as a tablet device in Figure 23.

[0077] The fourth and fifth user devices 121, 125 may belong to and / or form a communications network 131. In certain embodiments, the communications network 131 may be a local, mesh, or other network that facilitates communications between the fourth and fifth user devices 121, 125, and / or any other devices, programs, and / or networks of system 100 or outside system 100. In certain embodiments, the communications network 131 may be formed between the fourth and fifth user devices 121, 125 through the use of any type of wireless or other protocol and / or technology. For example, the fourth and fifth user devices 121, 125 may communicate with one another in the communications network 116, such as by utilizing BLE, classic Bluetooth, ZigBee, cellular, NFC, Wi-Fi, Z-Wave, ANT+, IEEE 802.15.4, IEEE 802.22, ISA100a, infrared, acoustic, ISM band, RFID, UWB, Wireless HD, Wireless USB, any other protocol and / or wireless technology, satellite, fiber, or any combination thereof. Notably, the communications network 131 may be configured to communicatively link with and / or communicate with any other network of the system 100 and / or outside the system 100.

[0078] Much like first user 101, the second user 120 may have his or her own earphone device 130. The earphone device 130 may be utilized by the second user 120 to hear and / or audition audio content, transmit audio content, receive audio content, experience any type of content, process audio content, adjust audio content, store audio content, perform any type of operation with respect to audio content, or a combination thereof. The earphone device 130 may be an earpiece, a hearing aid, an ear monitor, an ear terminal, a behind-the-ear device, any type of acoustic device, or a combination thereof. The earphone device 130 may include any type of component utilized for any type of earpiece, and may include any of the features, functionality and / or components described and / or usable with earphone device 115. For example, earphone device 130 may include any number of transceivers, ear canal microphones, ambient sound microphones, processors, memories, housings, eartips, foam tips, flanges, any other component, or any combination thereof.

[0079] In certain embodiments, the first, second, third, fourth, and / or fifth user devices 102, 106, 110, 121, 125 and / or earphone devices 115, 130 may have any number of software applications and / or application services stored and / or accessible thereon. For example, the first and second user devices 102, 111 may include applications for processing audio content, applications for playing, editing, transmitting, and / or receiving audio content, streaming media applications, speech-to-text translation applications, cloud-based applications, search engine applications, natural language processing applications, database applications, algorithmic 17 77331874;2applications, phone-based applications, product-ordering applications, business applications, e- commerce applications, media streaming applications, content-based applications, database applications, gaming applications, internet-based applications, browser applications, mobile applications, service-based applications, productivity applications, video applications, music applications, social media applications, presentation applications, any other type of applications, any types of application services, or a combination thereof. In certain embodiments, the software applications and services may include one or more graphical user interfaces so as to enable the first and second users 101, 120 to readily interact with the software applications. The software applications and services may also be utilized by the first and second users 101, 120 to interact with any device in the system 100, any network in the system 100 (e.g. communications networks 116, 131, 135), or any combination thereof. For example, the software applications executing on the first, second, third, fourth, and / or fifth user devices 102, 106, 110, 121, 125 and / or earphone devices 115, 130 may be applications for receiving data, applications for storing data, applications for auditioning, editing, storing and / or processing audio content, applications for receiving demographic and preference information, applications for transforming data, applications for executing mathematical algorithms, applications for generating and transmitting electronic messages, applications for generating and transmitting various types of content, any other type of applications, or a combination thereof. In certain embodiments, the first, second, third, fourth, and / or fifth user devices 102, 106, 110, 121, 125 and / or earphone devices 115, 130 may include associated telephone numbers, internet protocol addresses, device identities, or any other identifiers to uniquely identify the first, second, third, fourth, and / or fifth user devices 102, 106, 110, 121, 125 and / or earphone devices 115, 130 and / or the first and second users 101, 120. In certain embodiments, location information corresponding to the first, second, third, fourth, and / or fifth user devices 102, 106, 110, 121, 125 and / or earphone devices 115, 130 may be obtained based on the internet protocol addresses, by receiving a signal from the first, second, third, fourth, and / or fifth user devices 102, 106, 110, 121, 125 and / or earphone devices 115, 130 or based on profile information corresponding to the first, second, third, fourth, and / or fifth user devices 102, 106, 110, 121, 125 and / or earphone devices 115, 130.

[0080] The system 100 may also include a communications network 135. The communications network 135 may be under the control of a service provider, the first and / or second users 101, 120, any other designated user, or a combination thereof. The communications network 135 of the system 100 may be configured to link each of the devices in the system 100 to one another. For example, the communications network 135 may be utilized by the first user device 102 to connect with other devices within or outside communications network 135. Additionally, the communications network 135 may be configured to transmit, generate, and 18 77331874;2receive any information and data traversing the system 100. In certain embodiments, the communications network 135 may include any number of servers, databases, or other componentry. The communications network 135 may also include and be connected to a mesh network, a local network, a cloud-computing network, an IMS network, a VoIP network, a security network, a VoLTE network, a wireless network, an Ethernet network, a satellite network, a broadband network, a cellular network, a private network, a cable network, the Internet, an internet protocol network, MPLS network, a content distribution network, any network, or any combination thereof. Illustratively, servers 140, 145, and 150 are shown as being included within communications network 135. In certain embodiments, the communications network 135 may be part of a single autonomous system that is located in a particular geographic region, or be part of multiple autonomous systems that span several geographic regions.

[0081] Notably, the functionality of the system 100 may be supported and executed by using any combination of the servers 140, 145, 150, and 160. The servers 140, 145, and 150 may reside in communications network 135, however, in certain embodiments, the servers 140, 145, 150 may reside outside communications network 135. The servers 140, 145, and 150 may provide and serve as a server service that performs the various operations and functions provided by the system 100. In certain embodiments, the server 140 may include a memory 141 that includes instructions, and a processor 142 that executes the instructions from the memory 141 to perform various operations that are performed by the server 140. The processor 142 may be hardware, software, or a combination thereof. Similarly, the server 145 may include a memory 146 that includes instructions, and a processor 147 that executes the instructions from the memory 146 to perform the various operations that are performed by the server 145. Furthermore, the server 150 may include a memory 151 that includes instructions, and a processor 152 that executes the instructions from the memory 151 to perform the various operations that are performed by the server 150. In certain embodiments, the servers 140, 145, 150, and 160 may be network servers, routers, gateways, switches, media distribution hubs, signal transfer points, service control points, service switching points, firewalls, routers, edge devices, nodes, computers, mobile devices, or any other suitable computing device, or any combination thereof. In certain embodiments, the servers 140, 145, 150 may be communicatively linked to the communications network 135, the communications network 116, the communications network 131, any network, any device in the system 100, any program in the system 100, or any combination thereof.

[0082] The database 155 of the system 100 may be utilized to store and relay information that traverses the system 100, cache content that traverses the system 100, store data about each of the devices in the system 100 and perform any other typical functions of a database. In certain embodiments, the database 155 may be connected to or reside within the communications network 19 77331874;2135, the communications network 116, the communications network 131, any other network, or a combination thereof. In certain embodiments, the database 155 may serve as a central repository for any information associated with any of the devices and information associated with the system 100. Furthermore, the database 155 may include a processor and memory or be connected to a processor and memory to perform the various operation associated with the database 155. In certain embodiments, the database 155 may be connected to the earphone devices 115, 130, the servers 140, 145, 150, 160, the first user device 102, the second user device 106, the third user device 110, the fourth user device 121, the fifth user device 125, any devices in the system 100, any other device, any network, or any combination thereof.

[0083] The database 155 may also store information and metadata obtained from the system 100, store metadata and other information associated with the first and second users 101, 120, store user profiles associated with the first and second users 101, 120, store device profiles associated with any device in the system 100, store communications traversing the system 100, store user preferences, store information associated with any device or signal in the system 100, store information relating to patterns of usage relating to the first, second, third, fourth, and fifth user devices 102, 106, 110, 121, 125, store audio content associated with the first, second, third, fourth, and fifth user devices 102, 106, 110, 121, 125 and / or earphone devices 115, 130, store audio content and / or information associated with the audio content that is captured by the ambient sound microphones, store audio content and / or information associated with audio content that is captured by ear canal microphones, store any information obtained from any of the networks in the system 100, store audio content and / or information associated with audio content that is outputted by ear canal receivers of the system 100, store any information and / or signals transmitted and / or received by transceivers of the system 100, store any device and / or capability specifications relating to the earphone devices 115, 130, store historical data associated with the first and second users 101, 115, store information relating to the size (e.g. depth, height, width, curvatures, etc.) and / or shape of the first and / or second user's 101, 120 ear canals and / or ears, store information identifying and or describing any eartip utilized with the earphone devices 101, 115, store device characteristics for any of the devices in the system 100, store information relating to any devices associated with the first and second users 101, 120, store any information associated with the earphone devices 115, 130, store log on sequences and / or authentication information for accessing any of the devices of the system 100, store information associated with the communications networks 116, 131, store any information generated and / or processed by the system 100, store any of the information disclosed for any of the operations and functions disclosed for the system 100 herewith, store any information traversing the system 100, or any combination thereof. Furthermore, the database 155 may be configured to process queries sent to 20 77331874;2it by any device in the system 100.

[0084] The system 100 may also include a software application, which may be configured to perform and support the operative functions of the system 100, such as the operative functions of the first, second, third, fourth, and fifth user devices 102, 106, 110, 121, 125 and / or the earphone devices 115, 130. In certain embodiments, the application may be a website, a mobile application, a software application, or a combination thereof, which may be made accessible to users utilizing one or more computing devices, such as the first, second, third, fourth, and fifth user devices 102, 106, 110, 121, 125 and / or the earphone devices 115, 130. The application of the system 100 may be accessible via an internet connection established with a browser program or other application executing on the first, second, third, fourth, and fifth user devices 102, 106, 110, 121, 125 and / or the earphone devices 115, 130, a mobile application executing on the first, second, third, fourth, and fifth user devices 102, 106, 110, 121, 125 and / or the earphone devices 115, 130, or through other suitable means. Additionally, the application may allow users and computing devices to create accounts with the application and sign-in to the created accounts with authenticating username and password log-in combinations. The application may include a custom graphical user interface that the first user 101 or second user 120 may interact with by utilizing a browser executing on the first, second, third, fourth, and fifth user devices 102, 106, 110, 121, 125 and / or the earphone devices 115, 130. In certain embodiments, the software application may execute directly as an installed program on the first, second, third, fourth, and fifth user devices 102, 106, 110, 121, 125 and / or the earphone devices 115, 130. Computing System for Facilitating the Operation and Functionality of the System

[0085] Referring now also to Figure 24, at least a portion of the methodologies and techniques described with respect to the exemplary embodiments of the system 100 can incorporate a machine, such as, but not limited to, computer system 14100, or other computing device within which a set of instructions, when executed, may cause the machine to perform any one or more of the methodologies or functions discussed above. The machine may be configured to facilitate various operations conducted by the system 100. For example, the machine may be configured to, but is not limited to, assist the system 100 by providing processing power to assist with processing loads experienced in the system 100, by providing storage capacity for storing instructions or data traversing the system 100, by providing functionality and / or programs for facilitating the operative functionality of the earphone devices 115, 130, and / or the first, second, third, fourth, and fifth user devices 102, 106, 110, 121, 125 and / or the earphone devices 115, 130, by providing functionality and / or programs for facilitating operation of any of the components of the earphone devices 115, 130 (e.g. ear canal receivers, transceivers, ear canal microphones, 21 77331874;2ambient sound microphones, or by assisting with any other operations conducted by or within the system 100.

[0086] In some embodiments, the machine may operate as a standalone device. In some embodiments, the machine may be connected (e.g., using communications network 135, the communications network 116, the communications network 131, another network, or a combination thereof) to and assist with operations performed by other machines and systems, such as, but not limited to, the first user device 102, the second user device 111, the third user device 110, the fourth user device 121, the fifth user device 125, the earphone device 115, the earphone device 130, the server 140, the server 150, the database 155, the server 160, or any combination thereof. The machine may be connected with any component in the system 100. In a networked deployment, the machine may operate in the capacity of a server or a client user machine in a server-client user network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may comprise a server computer, a client user computer, a personal computer (PC), a tablet PC, a laptop computer, a desktop computer, a control system, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.

[0087] The computer system 14100 may include a processor 14102 (e.g., a central processing unit (CPU), a graphics processing unit (GPU, or both), a main memory 14104 and a static memory 14106, which communicate with each other via a bus 14108. The computer system 14100 may further include a video display unit 14110, which may be, but is not limited to, a liquid crystal display (LCD), a flat panel, a solid state display, or a cathode ray tube (CRT). The computer system 14100 may include an input device 14112, such as, but not limited to, a keyboard, a cursor control device 14114, such as, but not limited to, a mouse, a disk drive unit 14116, a signal generation device 14118, such as, but not limited to, a speaker or remote control, and a network interface device 14120.

[0088] The disk drive unit 14116 may include a machine-readable medium 14122 on which is stored one or more sets of instructions 14124, such as, but not limited to, software embodying any one or more of the methodologies or functions described herein, including those methods illustrated above. The instructions 14124 may also reside, completely or at least partially, within the main memory 14104, the static memory 14106, or within the processor 14102, or a combination thereof, during execution thereof by the computer system 14100. The main memory 14104 and the processor 14102 also may constitute machine-readable media. 22 77331874;2

[0089] Dedicated hardware implementations including, but not limited to, application specific integrated circuits, programmable logic arrays and other hardware devices can likewise be constructed to implement the methods described herein. Applications that may include the apparatus and systems of various embodiments broadly include a variety of electronic and computer systems. Some embodiments implement functions in two or more specific interconnected hardware modules or devices with related control and data signals communicated between and through the modules, or as portions of an application-specific integrated circuit. Thus, the example system is applicable to software, firmware, and hardware implementations.

[0090] In accordance with various embodiments of the present disclosure, the methods described herein are intended for operation as software programs running on a computer processor. Furthermore, software implementations can include, but not limited to, distributed processing or component / object distributed processing, parallel processing, or virtual machine processing can also be constructed to implement the methods described herein.

[0091] The present disclosure contemplates a machine-readable medium 14122 containing instructions 14124 so that a device connected to the communications network 135, the communications network 116, the communications network 131, another network, or a combination thereof, can send or receive voice, video or data, and communicate over the communications network 135, the communications network 116, the communications network 131, another network, or a combination thereof, using the instructions. The instructions 14124 may further be transmitted or received over the communications network 135, another network, or a combination thereof, via the network interface device 14120.

[0092] While the machine-readable medium 14122 is shown in an example embodiment to be a single medium, the term "machine-readable medium" should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and / or associated caches and servers) that store the one or more sets of instructions. The term "machine-readable medium" shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by the machine and that causes the machine to perform any one or more of the methodologies of the present disclosure.

[0093] The terms "machine-readable medium," "machine-readable device," or "computer- readable device" shall accordingly be taken to include, but not be limited to: memory devices, solid-state memories such as a memory card or other package that houses one or more read-only (non-volatile) memories, random access memories, or other re-writable (volatile) memories; magneto-optical or optical medium such as a disk or tape; or other self-contained information archive or set of archives is considered a distribution medium equivalent to a tangible storage medium. The "machine-readable medium," "machine-readable device," or "computer-readable 23 77331874;2device" may be non-transitory, and, in certain embodiments, may not include a wave or signal per se. Accordingly, the disclosure is considered to include any one or more of a machine-readable medium or a distribution medium, as listed herein and including art-recognized equivalents and successor media, in which the software implementations herein are stored.

[0094] The illustrations of arrangements described herein are intended to provide a general understanding of the structure of various embodiments, and they are not intended to serve as a complete description of all the elements and features of apparatus and systems that might make use of the structures described herein. Other arrangements may be utilized and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. Figures are also merely representational and may not be drawn to scale. Certain proportions thereof may be exaggerated, while others may be minimized. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense.

[0095] Thus, although specific arrangements have been illustrated and described herein, it should be appreciated that any arrangement calculated to achieve the same purpose may be substituted for the specific arrangement shown. This disclosure is intended to cover any and all adaptations or variations of various embodiments and arrangements of the invention. Combinations of the above arrangements, and other arrangements not specifically described herein, will be apparent to those of skill in the art upon reviewing the above description. Therefore, it is intended that the disclosure not be limited to the particular arrangement(s) disclosed as the best mode contemplated for carrying out this invention, but that the invention will include all embodiments and arrangements falling within the scope of the appended claims.

[0096] The foregoing is provided for purposes of illustrating, explaining, and describing embodiments of this invention. Modifications and adaptations to these embodiments will be apparent to those skilled in the art and may be made without departing from the scope or spirit of this invention. Upon reviewing the aforementioned embodiments, it would be evident to an artisan with ordinary skill in the art that said embodiments can be modified, reduced, or enhanced without departing from the scope and spirit of the claims described below. 24 77331874;2

Claims

CLAIMS I claim:

1. A method of noise reduction in communication comprising: receiving a microphone signal; extracting a portion of the microphone signal; determining a forward edge of an acoustic signal embedded in the microphone signal; determining a rearward edge of the acoustic signal; extracting a second signal between the forward edge and the rearward edge; forming a third acoustic signal by conforming the temporal length of the second signal to a standardized word length; forming a normalized spectrogram from the third signal; using a learning model to identify the third signal by analyzing the normalized spectrogram; and storing in memory a reference signal that corresponds to the identified third signal.

2. The method according to claim 1 further comprising: generating and output signal.

3. The method according to claim 2 further comprising: amending an output signal by adding the reference signal.

4. The method according to claim 3 further comprising: sending the output signal to a speaker.

5. The method according to claim 3, further comprising: sending the output signal to a communication device.

6. The method according to claim 1 further comprising: determining if a user of a wearable device is speaking.

7. The method according to claim 6, wherein the forward edge and rearward edge determination only occur when it has been determined that the user is speaking.

8. The method according to claim 3 further comprising: determining a time span between the forward edge and the rearward edge. 25 77331874;29. The method according to claim 8 further comprising: generating a modified reference signal by modifying the reference signal to fit the timespan prior to adding the reference signal to the output and adding the modified reference signal instead of the reference signal to the output signal.

10. The method according to claim 1, wherein the parameters used in the learning model to identify the third signal use coefficients of at least three fit lines. 26 77331874;2

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