Communication device audio transmission modification

A method can include obtaining audio data corresponding to a user of a communication device. The communication device can be configured to transmit the audio data. The method can further include obtaining proximity data indicating a user distance between the user and the communication device. The method can further include determining that the user distance exceeds a threshold distance. The method can further include determining, based at least in part on the audio data, an activity status of the user. The method can further include determining that the activity status is an inactive status. The method can further include modifying, in response to the determining that the threshold distance is exceeded and that the activity status is the inactive status, a transmission of the audio data from the communication device.

BACKGROUND

The present disclosure relates to a transmission of audio data from a communication device, and more specifically, to modification of a transmission of audio data from a communication device.

A communication device, such as a conferencing telephone or a telephone having speakerphone functionality, can broadcast audio data (e.g., speech) from a second location to a first environment where the communication device is located. Additionally, such a communication device can obtain audio data from the first environment and transmit the audio data to the second location. In some instances, such a communication device can be configured to increase and/or decrease a volume corresponding to the audio data transmitted from the first environment to the second location. In some instances, such a communication device can be configured to be muted, such that the transmission of audio data from the first environment to the second location is stopped.

SUMMARY

According to embodiments of the present disclosure, a method can include obtaining audio data. The audio data can correspond to a user of a communication device. The communication device can be configured to transmit the audio data. The method can further include obtaining proximity data. The proximity data can indicate a user distance between the user and the communication device. The method can further include determining that the user distance exceeds a threshold distance. The method can further include determining, based at least in part on the audio data, an activity status of the user. The method can further include determining that the activity status is an inactive status. The method can further include modifying, in response to the determining that the threshold distance is exceeded and that the activity status is the inactive status, a transmission of the audio data from the communication device.

A system and a computer program product corresponding to the above method are also included herein.

DETAILED DESCRIPTION

Aspects of the present disclosure relate to the transmission of audio data from a communication device; more particular aspects relate to modification of a transmission of audio data from a communication device. While the present disclosure is not necessarily limited to such applications, various aspects of the disclosure may be appreciated through a discussion of various examples using this context.

A communication device, such as a conferencing telephone or a telephone having speakerphone functionality, can broadcast audio data (e.g., speech) from a second location to a first environment where the communication device is located. Additionally, such a communication device can obtain audio data from the first environment and transmit the audio data to the second location. In some instances, such a communication device can be configured to increase and/or decrease a volume corresponding to the audio data transmitted from the first environment to the second location. In some instances, such a communication device can be configured to be muted, such that the transmission of audio data from the first environment to the second location is stopped.

In some instances, an environment where a communication device is located (i.e., a “communication device environment”) can include an office or meeting room of a commercial facility, such as an office building. In some instances, a communication device environment can include a residential structure, such as a house or a condominium, where a user of a communication device resides. On occasion, the communication device can obtain audio data that the user does not desire the communication device to transmit from the environment. Such audio data can be unanticipated and can interfere with communication activities, such as conference telephone calls, in which the user participates.

For example, a user can employ a communication device to participate in a business conference telephone call with multiple remotely-located coworkers. The user and the communication device can be located in a home office space of the user's home. Additionally, the communication device can operate as a speakerphone, such that the communication device can obtain sounds from a vicinity of the communication device (e.g., a region that includes the home office space) and transmit those sounds to the remotely-located coworkers. Continuing with this example, during the conference call, the user can decide to make a brief trip downstairs to get a glass of water. While downstairs, an infant in a bedroom of the home can be awakened and begin crying. The crying can be loud enough for the communication device to obtain the sound and transmit it to the multiple coworkers. Furthermore, the crying sound can cause a distraction in the business conference telephone call until the user returns to the home office space and activates a mute function of the communication device. Such a mute function can stop the transmission of sound from the communication device to the multiple coworkers.

In another example, continuing with the user and the communication device configuration discussed above, the user can be speaking to multiple coworkers using the communication device. While the user is speaking, a mail delivery person can approach the front door of the user's home. In response, the user's dog, recognizing that someone is at the front door, can begin barking. The barking sound can be louder than the user's voice and can be transmitted by the communication device to the multiple coworkers. Thus, the barking sound can interrupt the business conference telephone call until the user activates the mute function.

To address these and other challenges, embodiments of the present disclosure include an audio modification system. In some embodiments, the audio modification system can autonomously modify a transmission of audio data from a communication device (e.g., activate a mute function of the communication device) based, at least in part, on a user's proximity to the communication device. In some embodiments, the audio modification system can autonomously modify a transmission of audio data from a communication device based, at least in part, on a potential disruption to use of the communication device. In some embodiments, the audio modification system can notify a communication device user of a potential disruption to use of the communication device, so that the user can determine if and/or when to modify a transmission of audio data from the communication device. Accordingly, embodiments of the present disclosure can implement one or more dynamic, proactive operations to avoid one or more undesired audio data transmissions from a communication device. Thus, embodiments of the present disclosure can aid in reducing disruptions that can occur during the use of communication devices.

For example, in the “crying sound” example discussed above, embodiments of the present disclosure can determine when a user is not actively participating in a conference call (e.g., when the user is not speaking) and when the user's distance from the communication device exceeds a threshold (e.g., when the user goes downstairs). In response, embodiments of the present disclosure can autonomously activate a mute function of the communication device to avoid potential transmissions of disruptive audio data.

In another example, in the “barking sound” example discussed above, embodiments of the present disclosure can identify a potential audio disruption (e.g., the mail delivery person approaching the front door) based on data such as images from a networked camera at the front door. Embodiments of the present disclosure can additionally determine when the user is actively participating in a conference call by analyzing the user's speech. In the example discussed above, since the user is actively participating in the conference call, embodiments of the present disclosure can display a notification to the user indicating the presence of the mail delivery person. Based on the notification, the user can excuse himself or herself from the conference call and activate a mute function of the communication device to avoid the forthcoming audio disruption. Additionally, in an otherwise identical scenario in which the user is not actively participating in the conference call, embodiments of the present disclosure can autonomously activate the mute function of the communication device and notify the user of the modification.

Turning to the figures,FIG. 1illustrates a computing environment100that includes one or more of each of an audio modification system (“AMS”)150, a networked device120, a communication device130, a server140, and a network160. The computing environment100also includes a set of mobile devices110. The set of mobile devices110can include one or more mobile devices. For example, in some embodiments, the set of mobile devices110can include n mobile devices, where n is an integer greater than zero. For example, n=1 in embodiments in which the set of mobile devices110includes only a first mobile device110-1; n=2 in embodiments in which the set of mobile devices110includes two mobile devices (a first mobile device110-1and a second mobile device110-2); and so on.

In some embodiments, at least one AMS150, networked device120, communication device130, server140, and/or mobile device110-ncan obtain and store data, such as activity data and/or proximity data (discussed below). In some embodiments, at least one AMS150, networked device120, communication device130, server140, and/or mobile device110-ncan exchange data with at least one other through the at least one network160. For example, in some embodiments, at least one AMS150, networked device120, communication device130, server140, and/or mobile device110-ncan exchange activity data and/or proximity data with at least one other through the at least one network160. One or more of each of the AMS150, networked device120, communication device130, server140, mobile device110-nand/or network160can include a computer system, such as the computer system501discussed with respect toFIG. 5.

In some embodiments, the AMS150can be a software application installed on a computer system of at least one of the networked device120, communication device130, server140, and/or mobile device110-n. In some embodiments, the AMS150can be integrated into one or more software applications installed on at least one of the networked device120, communication device130, server140, and/or mobile device110-n. For example, in some embodiments, the AMS150can be included as a plug-in software component of a software application (e.g., a conference-call software application) installed on the communication device130. The AMS150can include program instructions implemented by a processor, such as a processor of the communication device130, to perform one or more operations discussed with respect toFIG. 3and/orFIG. 4. In some embodiments, the AMS150can be identical or substantially similar to the AMS230discussed with respect toFIG. 2.

In some embodiments, communication device130can be a device configured to obtain and transmit audio data (e.g., sounds, such as speech) and to receive and emit audio data. For example, in some embodiments, a communication device130can include a telephone and/or teleconferencing equipment. In some embodiments, a communication device130can include a computer, such as a tablet computer, desktop computer, and/or notebook computer. In some embodiments, the communication device130can include a microphone135configured to obtain audio data and a speaker125configured to emit audio data. For example, in some embodiments, the communication device130can include a notebook computer having a microphone135and a speaker125. In this example, the notebook computer can implement a conference-call software application that allows a user to participate in a conference call using the notebook computer. Further in this example, the AMS150can be included as a plug-in software component of the conference-call software.

In some embodiments, the set of mobile devices110can include one or more devices such as a mobile phone, wearable technology (e.g., smart watch and/or fitness tracker), and/or computer (e.g., tablet computer and/or notebook computer). In some embodiments, the set of mobile devices110can be configured to present to a user a visual and/or an audible notification from the AMS150. For example, in some embodiments, a mobile device110-ncan include a display (not shown) and/or a speaker (not shown) configured, respectively, to present an alphanumeric notification and/or an automated speech notification from the AMS150to the user.

In some embodiments, a networked device120can include a device that can be connected to one or more networks and configured to communicate with one or more electronic devices. For example, networked devices120can include Internet of things (“IoT”) devices, such as cameras, televisions and/or monitors, sensors, and/or wireless transmitters (e.g., beacon technology beacons).

In some embodiments, server140can be a web server accessible by one or more of each of the AMS150, networked device120, communication device130, and/or mobile device110-nthrough the network160. In some embodiments, the network160can be a wide area network (WAN), a local area network (LAN), the internet, or an intranet. In some embodiments, the network160can be substantially similar to, or the same as, cloud computing environment50discussed with respect toFIG. 6.

FIG. 2illustrates an example data flow diagram200of an AMS230, in accordance with embodiments of the present disclosure. In the data flow diagram200, the AMS230can obtain activity data205and/or proximity data225and can output an audio modification decision and corresponding notification250.

In some embodiments, the AMS230can be identical or substantially similar to the AMS150discussed with respect toFIG. 1. In some embodiments, the AMS230can include one or more modules, such as a data analysis manager235, a machine learning module240, and/or a device manager245(discussed further below). In some embodiments, one or more of the AMS230, the data analysis manager235, machine learning module240, and/or device manager245can include program instructions implemented by a processor, such as processor510,FIG. 5, to perform one or more operations discussed with respect toFIG. 3and/orFIG. 4. In some embodiments, one or more of the data analysis manager235, machine learning module240, and/or device manager245can be integrated into a single module.

In some embodiments, activity data205can include information corresponding to a communication device environment. For example, in some embodiments, activity data205can include information corresponding to sounds, images, entities, and/or actions, that can affect a room or space where a communication device is located. The audio modification system230can obtain activity data205from one or more sources, such as one or more mobile devices, networked devices, communication devices, and/or servers (e.g., mobile devices110, networked devices120, communication devices130, and/or servers140,FIG. 1). In some embodiments, activity data205can include one or more of audio data210, image data215, and/or event data220.

In some embodiments, audio data210can include data corresponding to sounds, such as speech and/or ambient noises, that are audible in a communication device environment. For example, in some embodiments, a communication device can include a microphone (e.g., microphone135,FIG. 1). The microphone can be configured to convert received sounds (e.g., sound waves) into a corresponding electrical signal. In this example, audio data210can include the electrical signal corresponding to the sound waves received by the microphone. In some embodiments, audio data210can include one or more of user voice data (e.g., a sound of a voice of a user of a communication device); third-party voice data (e.g., a sound of a voice other than a user's voice); and/or ambient noises (e.g., sounds in the communication device environment).

For example, in some embodiments, a user can participate in a telephone call with a second party using a communication device. In this example, the user and the communication device can be located in the user's office. Additionally in this example, the communication device can function as a speakerphone. For example, a speaker of the communication device can broadcast sounds from the second party's location to a vicinity of the communication device, and a microphone of the communication device can receive sounds from the vicinity of the communication device. Additionally, the communication device can transmit the received sounds to the second party's location. Continuing with this example, user voice data can include the sound of the user speaking to the second party through the communication device. Additionally in this example, third-party voice data can include the sound of the user's coworker entering the user's office and speaking to the user about a topic unrelated to the topic of the telephone call. Additionally in this example, ambient noises can include sounds such as a telephone ringing in an adjacent office, a vacuum cleaner being used in a hallway, and the user typing on the user's computer. In some embodiments, audio data210can include sounds such as a clock chime, a passing train, an overhead airplane, a siren, a doorbell, a barking dog, and the like. In some embodiments, audio data210can include times and/or dates corresponding to sounds that are audible in a communication device environment.

In some embodiments, image data215can include images corresponding to a communication device environment. In some embodiments, image data215can include information about activities inside a communication device environment and/or activities that can affect a communication device environment. For example, in some embodiments, image data215can include video data from a networked doorbell camera at a house where a communication device is located. Such video data can indicate when a visitor is about to ring a doorbell, which can affect the communication device environment. In another example, in some embodiments, image data215can include images from one or more networked cameras inside an office meeting room where a communication device is located. Such images can indicate activities such as whether a user is typing and/or whether a user has left the meeting room. In some embodiments, image data215can include times and/or dates corresponding to images.

In some embodiments, event data220can include information about one or more specific actions and/or one or more activities that can be scheduled. In some embodiments, such specific actions and/or activities can affect a communication device environment. For example, in some embodiments, event data220can include data from one or more door sensors indicating that a door has been opened. In another example, in some embodiments, event data220can include calendar data that the AMS230can download from a resource, such as a web server. In some embodiments, such calendar data can include one or more event times (e.g., a time of day corresponding to an occurrence of an event) and/or one or more event dates (e.g., a calendar date corresponding to an occurrence of an event). For example, calendar data can include an email indicating an event time and an event date for an office building fire drill. In another example, such calendar data can include a scheduled communication time. A communication time can refer to a time period and/or date during which the communication device is to be in operation by a user (e.g., an electronic calendar entry indicating a date, time, and duration of a scheduled conference call). In another example, in some embodiments, event data220can include one or more scheduled events input into the AMS230by a user. For example, in some embodiments, a user's home office can be located near a tornado siren that is tested on a predetermined weekday and time. In this example, the user can input the predetermined weekday and time into the AMS230with a mobile device, such as a mobile telephone.

In another example, in some embodiments, event data220can include one or more scheduled events generated by the AMS230. For example, in some embodiments, the AMS230can generate one or more scheduled events based on audio data210and/or image data215. For example, in some embodiments, a communication device that includes an AMS230can be located within an audible range of a chiming clock. In this example, based on the times and/or dates corresponding to chiming sounds generated by the clock, the AMS230can generate one or more scheduled events corresponding to those times and/or dates.

Accordingly, embodiments of the present disclosure can be configured to obtain activity data205in a variety of manners and from a plurality of sources. Thus, embodiments of the present disclosure can be configured to obtain comprehensive information about activities that can affect a communication device environment.

In some embodiments, proximity data225can include information corresponding to a device distance. A device distance can refer to a distance between one or more mobile devices (e.g., mobile devices110,FIG. 1) and a communication device (e.g., communication device130,FIG. 1). In some embodiments, such a device distance can indicate a user distance (i.e., a distance between a communication device user and a communication device). In some embodiments, such a device distance can indicate a third-party distance (i.e., a distance between a third-party (e.g., a person who is not participating in a conference call using the communication device) and the communication device).

For example, in some embodiments, a user can participate in a conference call using a conferencing telephone that includes AMS230. In this example, the user can have two mobile devices in the user's possession: a mobile telephone in the user's pocket and a smart watch on the user's wrist. Thus, under an assumption that the user maintains such possession of the two mobile devices, a distance between one or both of the mobile devices and the conferencing telephone (i.e., a device distance) can indicate a distance between the user and the conferencing telephone (i.e., a user distance). Similarly, a distance between a mobile telephone carried by a third-party, such as the user's spouse, and the conferencing telephone (i.e., a device distance) can indicate a distance between the third-party and the conferencing telephone (i.e., a third-party distance).

In some embodiments, proximity data225can include information that can indicate a user distance and/or a third-party distance. For example, in some embodiments, proximity data can include images of a user standing in a location that is approximately 25 meters (m) from a communication device. Thus, such images can indicate a user distance of approximately 25 m.

In some embodiments, the AMS230can obtain proximity data225through network communication with one or more of a mobile device, networked device, and/or communication device. For example, in some embodiments, a fitness tracker of a user can transmit information about its location to an AMS230included on a communication device through a wireless network connection with the communication device. In this example, the AMS can determine a distance between a location of the communication device and the location of the fitness tracker.

In some embodiments, the AMS230can obtain proximity data225by analyzing image data215and/or audio data210. For example, in some embodiments, the AMS230can obtain images of a user from a networked camera. In this example, the images can indicate that the user is located in a room other than a room where a communication device is located. Thus, such images can indicate to the AMS230that the user is located at a distance that exceeds a threshold distance from the communication device.

In some embodiments, the AMS230can obtain proximity data225through one or more audible sounds generated by a mobile device. For example, in some embodiments, an AMS230included on a communication device can issue a command to a mobile telephone of a user through a network connection with the mobile telephone. In this example, the command can cause the mobile telephone to emit one or more audible sounds that can be obtained by a microphone of the communication device. Continuing with this example, based on a sound level (e.g., a decibel value) of the one or more audible sounds obtained by the microphone, the AMS230can determine a distance between the mobile telephone and the communication device.

In some embodiments, proximity data225can include a numerical value, such as a distance in meters, between a mobile device and a communication device. In some embodiments, proximity data225can include an indication of a distance, such as whether a user and/or a mobile device of a user is located outside of a room where a communication device is located.

Turning to the one or more modules that can be included with the AMS230, in some embodiments, the AMS230can include a data analysis manager235. The data analysis manager235can obtain and analyze activity data205and/or proximity data225. For example, in some embodiments, the data analysis manager235can include program instructions to perform operations305-320and335,FIG. 3. In some embodiments, the data analysis manager235can include program instructions to perform operations405-425and440,FIG. 4. In some embodiments, the data analysis manager235can implement technology such as image analysis technology, audio analysis technology, speech recognition technology, and/or natural language processing technology to determine an activity status of a user, identify a potential audio disruption, generate a potential-disruption rating, and/or interpret activity data205and/or proximity data225.

For example, in some embodiments, the data analysis manager235can be configured to analyze speech obtained by a communication device. Based on the analysis of the speech, the data analysis manager235can determine if the speech is by a user who is scheduled to participate in a conference call, or if the speech is by a third-party who is not scheduled to participate in the conference call. In some embodiments, the data analysis manager235can be configured to analyze sound parameters, such as a sound level and/or sound frequency. Additionally, in some embodiments, the data analysis manager235can be configured to identify characteristics of sound parameters, such as a recurring pattern of sounds having substantially similar parameters, changes in sound parameters (e.g., an increasing and/or decreasing sound level and/or sound frequency), and/or sounds that exceed a threshold sound level.

In another example, some embodiments, the data analysis manager235can be configured to obtain and analyze text compositions, such as email messages and calendar entries, to obtain data such as event data220.

In some embodiments the data analysis manager235can include one or more stored thresholds (e.g., one or more threshold distances, activity thresholds, and/or disruption thresholds). Such one or more stored thresholds can be selected by a user or included as one or more default values in programming instructions of the AMS230.

In some embodiments, the AMS230can include a machine learning module240. In some embodiments, the machine learning module240can include program instructions to perform operations315and320,FIG. 3. In some embodiments, the machine learning module240can include program instructions to perform operations410-425,FIG. 4. In some embodiments, the machine learning module240can be a processor that includes a machine learning algorithm. The machine learning algorithm can be generated by performing supervised, unsupervised, or semi-supervised training on a data set. In some embodiments, the machine learning module240can apply the machine learning algorithm to activity data205and/or proximity data225to predict an activity status, a potential-disruption rating, and/or whether a distance between a user and a communication device exceeds a threshold. In some embodiments, the machine learning module240can apply the machine learning algorithm to activity data205and/or proximity data225to predict whether to modify a transmission of audio data from a communication device. In these embodiments, in response to the machine learning module240predicting that a transmission of audio data should be modified, the AMS230can initiate such a modification by generating a modification command and/or notification250. In some embodiments, the AMS230can obtain user feedback that can be used to train the machine learning module240.

In some embodiments, the AMS230can include a device manager245. In some embodiments, the device manager245can include program instructions to perform operations325and330,FIG. 3. In some embodiments, the device manager245can include program instructions to perform operations430and435,FIG. 4.

In some embodiments, the device manager245can manage communication between the AMS230and one or more devices, such as mobile devices, networked devices, communication devices, and servers (e.g., mobile devices110, networked device120, communication device130, and/or server140). In some embodiments, device manager245can issue one or more commands to one or more such devices. For example, in some embodiments, the device manager245can issue a command to a communication device to modify a transmission of audio data from the communication device. For example, the device manager245can issue a command to a communication device to activate a mute function that stops transmission of audio data from the communication device. In another example, the device manager245can issue a command to a communication device to reduce the volume of a microphone of the communication device to reduce a sound level of audio data transmitted from the communication device. In some embodiments, the device manager245can issue a command to a mobile device to cause the mobile device to emit an audible sound that can be analyzed by the AMS230.

In some embodiments, the device manager245can generate and issue one or more notifications to one or more devices, such as a text notification to a mobile phone of a user indicating that a visitor is approaching the front door of the user's house.

FIG. 3illustrates a flowchart of an example method300for modifying a transmission of audio data based, at least in part, on a threshold distance, in accordance with embodiments of the present disclosure. The method300can be performed by an AMS, such as the AMS150,FIG. 1and/or the AMS230,FIG. 2.

Referring back toFIG. 3, in operation305, the AMS can obtain proximity data. In some embodiments, the AMS can obtain proximity data from one or more mobile devices, networked devices, and/or communication devices.

In operation310, the AMS can obtain activity data. In some embodiments, the AMS can obtain activity data from one or more sources, such as one or more mobile devices, networked devices, communication devices, and/or servers.

In some embodiments, in operation315, the AMS can determine an activity status. An activity status can indicate a degree to which a user is engaged in a use of a communication device. For example, in some embodiments, the AMS can determine that a user has a highest degree of engagement in a use of the communication device when the user is actively speaking to a second party through the communication device. For example, in some embodiments, the AMS can determine such a highest degree of engagement when a user is audibly explaining terms of a contract to a coworker during a conference call using the communication device. In this example, the AMS can determine that the user's activity status is an active status. In another example, in some embodiments, the AMS can determine that a user has a lowest degree of engagement in a use of the communication device when the user does not actively speak to a second party using the communication device for a period of time that exceeds a threshold. For example, the AMS can determine such a lowest degree of engagement when a user is a party to a conference call using the communication device and remains silent for more than 20 minutes. In this example, the AMS can determine that the user's activity status is an inactive status.

In some embodiments, operation315can include the AMS generating, based at least in part on activity data obtained in operation310, an activity rating that corresponds to an activity status of the user. For example, in some embodiments, the AMS can analyze audio data and/or image data to generate a numerical activity rating that can indicate a degree to which a user is engaged in a use of a communication device. For example, the AMS can analyze audio data from the communication device to determine one or more characteristics, such as a characteristic that the user is speaking in intervals (e.g., periods of speech followed by periods of silence) that are consistent with intervals of a back-and-forth dialogue. In this example, the AMS can correlate the characteristic with a numerical activity rating, such as 95%. This numerical activity rating can indicate a 95% certainty that the user's activity status is an active status. In another example, the AMS can analyze audio data from a communication device to determine that a user has remained silent for 15 minutes during a conference call. Further in this example, the AMS can analyze image data from a networked camera to determine that a user is actively typing on a computer. Continuing with this example, based on the audio data and the image data, the AMS can generate an activity rating such as 25%. This numerical activity rating can indicate a 25% certainty that the user's activity status is an active status.

In some embodiments, operation320can include the AMS comparing a user distance between a communication device user and the communication device to a threshold distance. Operation320can further include the AMS comparing an activity rating to an activity threshold. In some embodiments, if the activity rating exceeds the activity threshold, then the AMS can determine that the user has an active status. In some embodiments, if the activity rating does not exceed the activity threshold, then the AMS can determine that the user has an inactive status. Additionally, in operation320, if the AMS determines that the user distance exceeds the threshold distance and that the user's activity status is an inactive status, then the AMS can proceed to operation325. Alternatively, in operation320if the AMS determines that the user distance does not exceed the threshold distance or that the user's activity status is an active status, then the AMS can proceed to operation330.

In operation325, in response to determining that the user distance exceeds the threshold distance and that the user's activity status is an inactive status, the AMS can modify a transmission of audio data from the communication device. In some embodiments, modifying a transmission of audio data can include stopping a transmission of the audio data from the communication device (e.g., stopping an audio signal from being transmitted across a network from the communication device). In some embodiments, modifying a transmission of audio data can include muting a microphone of the communication device (e.g., deactivating a microphone of the communication device such that it is not operable to convert received sounds into a corresponding electrical signal). In some embodiments, modifying a transmission of audio data can include reducing a volume of the audio data transmitted from the communication device (e.g., decreasing a decibel level of the audio data transmitted from the communication device such that it is below a threshold, such as 5 decibels (dB)).

In operation330, the AMS can transmit a notification to a user. In some embodiments, the AMS can perform operation330in response to determining that the activity status is an active status in operation320. For example, in some embodiments, the AMS can transmit a text notification to a mobile phone of a user who the AMS determines to have an active status and to have a user distance that exceeds the threshold distance. In this example, the notification can indicate to the user that the user is beyond a threshold distance from the communication device. The notification can further indicate to the user that the mute function of the communication device is not activated.

In some embodiments, operation330can include the AMS transmitting a notification to one or more mobile devices that can have one or more respective device distances. For example, as discussed in an example above, in some embodiments, a user can participate in a conference call using a conferencing telephone that includes an AMS. In this example, the user can have two mobile devices in the user's possession: a mobile telephone and a smart watch. Continuing with this example, the user can exit a room where the communication device is located. The user can leave the mobile telephone in the room, but take the smart watch from the room. Thus, a device distance of the mobile telephone obtained by the AMS can be within a threshold distance, and a device distance obtained by the AMS of the smart watch can exceed the threshold distance. Accordingly, in this example, the device distance of the mobile telephone can indicate to the AMS that the user distance is within the threshold distance, and the device distance of the smart watch can indicate to the AMS that the user distance exceeds the threshold distance. Therefore, in some embodiments, the AMS can transmit a notification to the mobile device (i.e., the smart watch) having the device distance that exceeds the threshold distance. In this way, the AMS can be configured to accurately transmit a notification to a user.

In operation335, the AMS can obtain feedback from a user. In some embodiments, such feedback can include information such as a verification of a user's location, a verification of a user's activity status, and/or whether the user agrees with an audio modification decision of the AMS.

FIG. 4illustrates a flowchart of an example method400for modifying a transmission of audio data based, at least in part, on a potential audio disruption, in accordance with embodiments of the present disclosure. The method400can be performed by an AMS, such as the AMS150,FIG. 1and/or the AMS230,FIG. 2.

Referring back toFIG. 4, in operation405, the AMS can obtain activity data. In some embodiments, the AMS can obtain activity data from one or more sources, such as one or more mobile devices, networked devices, communication devices, and/or servers. In some embodiments, operation405can include the AMS obtaining proximity data from one or more mobile devices, networked devices, and/or communication devices.

In operation410, the AMS can identify, based at least in part on the activity data, a potential audio disruption. A potential audio disruption can include one or more activities that can generate audio data that can interfere with use of a communication device. For example, in some embodiments, a potential audio disruption can include activities such as a chiming clock, a guest approaching a house, a visitor opening a meeting room door, a barking dog, a starting of a vacuum cleaner, and/or a passage of a vehicle such as a truck, airplane, and/or train. In some embodiments, the AMS can identify such potential audio disruptions by analyzing activity data obtained in operation405.

In some embodiments, identifying a potential audio disruption can include the AMS analyzing proximity data indicating a third-party distance between a third-party and the communication device, and determining that the third-party distance does not exceed a threshold distance. For example, in some embodiments, a user can employ a communication device that includes an AMS. The communication device can be located in the user's home office. Continuing with this example, the AMS can obtain proximity data from a smart watch worn by a third-party (e.g., the user's child). The proximity data can include a device distance of the smart watch that indicates a third-party distance of the user's child. Continuing with this example, when the AMS determines that the third-party distance of the user's child does not exceed a threshold distance, the AMS can identify a potential audio disruption. For example, if a threshold distance is a distance from the communication device to an area just outside the user's home office (e.g., 2 m outside a door of the user's home office), and the AMS obtains proximity data indicating a third-party distance of approximately 1 m outside the door of the user's home office, then the AMS can identify a potential audio disruption.

In some embodiments, identifying a potential audio disruption can include the AMS determining that an event time coincides with a communication time. For example, in some embodiments, a user can be participating in a conference call at the user's office using a communication device that includes an AMS. Continuing with this example, the conference call can be scheduled for 1 PM to 3 PM that day. Continuing with this example, the user can receive an e-mail message at 1:30 PM reminding the user that an office public address system will be tested from 2:30 PM to 2:35 PM that day. In this example, the AMS can obtain the communication time for the conference call and the e-mail message from a web server. Further in this example, the AMS can implement natural language processing technology to interpret the email message. Additionally in this example, the AMS can compare the communication time to the event time for the office public address system test. Based on the comparison, the AMS can determine that the event time coincides with the communication time; thus, the AMS can identify the office public address system test as a potential audio disruption.

In some embodiments, operation410can include the AMS generating a potential-disruption rating. A potential-disruption rating can indicate a likelihood that an activity is generating or can generate one or more sounds that can interfere with use of a communication device. In some embodiments, a potential-disruption rating can include a label, such as “high” or “low.” In some embodiments, a potential-disruption rating can include a numerical value.

For example, in some embodiments, a potential-disruption rating can have a value of 1, 2, or 3. In this example, a potential-disruption rating of “1” can indicate a lowest likelihood of disruption, and a potential-disruption rating of “3” can indicate a highest likelihood of disruption. For example, an ambient sound having a sound level of 40 dB or less can have a potential-disruption rating of “1” due to that sound level being unlikely to interfere with use of the communication device. In another example, an ambient sound having a sound level of 70 dB or more can have a potential-disruption rating of “3” due to that sound level being highly likely to interfere with use of the communication device (e.g., the sound level can impede one or more party's ability to interpret speech by other parties to a phone call).

In some embodiments, one or more potential-disruption ratings for one or more respective activities can be selected by a user. In some embodiments, the AMS can predict one or more potential-disruption ratings for one or more activities by applying a machine learning algorithm, as discussed with respect toFIG. 2.

In operation415, the AMS can compare the potential-disruption rating to a disruption threshold. In some embodiments, if the potential-disruption rating does not exceed the disruption threshold, then method400can end. Alternatively, in some embodiments, if the potential-disruption rating exceeds the disruption threshold, then the AMS can proceed to operation420.

In operation420, the AMS can determine, based at least in part on the activity data, an activity status of the user. In some embodiments, operation420can be substantially similar to operation315,FIG. 3.

In operation425, the AMS can determine whether the activity status of the user is an inactive status. In some embodiments, if the activity status is an inactive status, then the AMS can proceed to operation430. Alternatively, in some embodiments, if the activity status is an active status, then the AMS can proceed to operation435.

In operation430, the AMS can modify a transmission of audio data from the communication device. In some embodiments, operation430can be substantially similar to operation325,FIG. 3. In some embodiments, operation430can include the AMS modifying a transmission of audio data at an event time and/or date. For example, continuing with the “public address system test” example discussed above, if the AMS determines that the user is inactive at 2:30 PM, then the AMS can autonomously activate a mute function of the communication device. In this way, the AMS can autonomously prevent sounds from the public address system test from interfering with the conference call.

In operation435, the AMS can transmit a notification to the user. In some embodiments, the AMS can perform operation435in response to determining that the activity status is an active status in operation425. For example, continuing with the “public address system test” example discussed above, if the AMS determines that the user has an active status, then the AMS can transmit a text notification regarding the public address system test to a networked television in the user's office. Based on the notification, the user can complete and end the conference call or excuse himself or herself from the conference call and activate a mute function of the communication device. In this way, the user can determine, according to the user's needs, how and/or when to modify a transmission of audio data from the communication device. In some embodiments, operation435can be substantially similar to operation330,FIG. 3.

In operation440, the AMS can obtain feedback from a user. In some embodiments, operation440can be substantially similar to operation335,FIG. 3.

FIG. 5depicts the representative major components of an exemplary Computer System501that can be used in accordance with embodiments of the present disclosure. The particular components depicted are presented for the purpose of example only and are not necessarily the only such variations. The Computer System501can comprise a Processor510, Memory520, an Input/Output Interface (also referred to herein as I/O or I/O Interface)530, and a Main Bus540. The Main Bus540can provide communication pathways for the other components of the Computer System501. In some embodiments, the Main Bus540can connect to other components such as a specialized digital signal processor (not depicted).

The Processor510of the Computer System501can be comprised of one or more CPUs512. The Processor510can additionally be comprised of one or more memory buffers or caches (not depicted) that provide temporary storage of instructions and data for the CPU512. The CPU512can perform instructions on input provided from the caches or from the Memory520and output the result to caches or the Memory520. The CPU512can be comprised of one or more circuits configured to perform one or methods consistent with embodiments of the present disclosure. In some embodiments, the Computer System501can contain multiple Processors510typical of a relatively large system. In other embodiments, however, the Computer System501can be a single processor with a singular CPU512.

The Memory520of the Computer System501can be comprised of a Memory Controller522and one or more memory modules for temporarily or permanently storing data (not depicted). In some embodiments, the Memory520can comprise a random-access semiconductor memory, storage device, or storage medium (either volatile or non-volatile) for storing data and programs. The Memory Controller522can communicate with the Processor510, facilitating storage and retrieval of information in the memory modules. The Memory Controller522can communicate with the I/O Interface530, facilitating storage and retrieval of input or output in the memory modules. In some embodiments, the memory modules can be dual in-line memory modules.

The I/O Interface530can comprise an I/O Bus550, a Terminal Interface552, a Storage Interface554, an I/O Device Interface556, and a Network Interface558. The I/O Interface530can connect the Main Bus540to the I/O Bus550. The I/O Interface530can direct instructions and data from the Processor510and Memory520to the various interfaces of the I/O Bus550. The I/O Interface530can also direct instructions and data from the various interfaces of the I/O Bus550to the Processor510and Memory520. The various interfaces can comprise the Terminal Interface552, the Storage Interface554, the I/O Device Interface556, and the Network Interface558. In some embodiments, the various interfaces can comprise a subset of the aforementioned interfaces (e.g., an embedded computer system in an industrial application may not include the Terminal Interface552and the Storage Interface554).

Logic modules throughout the Computer System501—including but not limited to the Memory520, the Processor510, and the I/O Interface530—can communicate failures and changes to one or more components to a hypervisor or operating system (not depicted). The hypervisor or the operating system can allocate the various resources available in the Computer System501and track the location of data in Memory520and of processes assigned to various CPUs512. In embodiments that combine or rearrange elements, aspects of the logic modules' capabilities can be combined or redistributed. These variations would be apparent to one skilled in the art.

Characteristics are as follows:

Service Models are as follows:

Deployment Models are as follows:

As discussed in more detail herein, it is contemplated that some or all of the operations of some of the embodiments of methods described herein can be performed in alternative orders or may not be performed at all; furthermore, multiple operations can occur at the same time or as an internal part of a larger process.