Abstract: This document relates to distributed teleconferencing. Some implementations can employ personalized enhancement models to enhance microphone signals for participants in a call. Further implementations can perform proximity-based mixing, where microphone signals received from devices in a particular room can be omitted from playback signals transmitted to other devices in the same room. These techniques can allow enhanced call quality for teleconferencing sessions where co-located users can employ their own devices to participate in a call with other users.

Abstract: This document generally relates to techniques for testing or training data augmentation. One example includes a method or technique that can include accessing a repository of private data items. The repository can provide a distribution of the private data items that is representative of a designated real-world scenario for a machine learning model. The method or technique can also include assigning classifications to the private data items in the repository. The method or technique can also include augmenting a testing or training set for the machine learning model based at least on the classifications of the private data items to obtain an augmented testing or training set that is relatively more representative of the distribution of classifications in the repository.

Abstract: This document relates to training and employing of quality estimation models to estimate the quality of different signal characteristics. One example includes a method or technique that can be performed on a computing device. The method or technique can include obtaining training signals exhibiting diverse impairments introduced when the training signals are captured or diverse artifacts introduced by different processing characteristics of a plurality of data enhancement models. The method or technique can also include obtaining quality labels for different signal characteristics of the training signals. The method or technique can also include training at least two different quality estimation models to estimate quality of at least two different signal characteristics based at least on the training signals and the quality labels.

Abstract: A system is provided herein that can correlate service issues with system telemetry associated with the software session associated with those service issues. Using a statistical approach, the system can evaluate data across numerous software sessions to rank the importance of the reported service issues. To accomplish the ranking, the system can parse the reports of service issues on a periodic basis, can extract telemetry identifiers (IDs) from the logs, can query the telemetry, may compute the relative importance of detected issues (in the context of calls going on for that day), and then can report this impact hack to the service issue database.

Abstract: A system is provided herein that can correlate service issues with system telemetry associated with the software session associated with those service issues. Using a statistical approach, the system can evaluate data across numerous software sessions to rank the importance of the reported service issues. To accomplish the ranking, the system can parse the reports of service issues on a periodic basis, can extract telemetry identifiers (IDs) from the logs, can query the telemetry, may compute the relative importance of detected issues (in the context of calls going on for that day), and then can report this impact hack to the service issue database.

Abstract: A system is provided herein that can correlate service issues with system telemetry associated with the software session associated with those service issues. Using a statistical approach, the system can evaluate data across numerous software sessions to rank the importance of the reported service issues. To accomplish the ranking, the system can parse the reports of service issues on a periodic basis, can extract telemetry identifiers (IDs) from the logs, can query the telemetry, may compute the relative importance of detected issues (in the context of calls going on for that day), and then can report this impact back to the service issue database.

Abstract: Techniques for conducting a communication session include obtaining capabilities of a set of one or more first devices and a second device configured to provide content to the first devices, the second device being configured to generate a plurality of data streams associated with the communication session; sending a first signal over a network to the second device to configure one or more operating parameters of the second device to generate the one or more data streams according to the capabilities of the first devices; and dynamically updating the operating parameters of the second device to alter the one or more data streams generated by the second device responsive to receiving an indication of changes in the capabilities of one or more of the first devices, a set of one or more third devices joining the communication session having different capabilities than the first set of devices, or both.

Abstract: A system is provided herein that can correlate service issues with system telemetry associated with the software session associated with those service issues. Using a statistical approach, the system can evaluate data across numerous software sessions to rank the importance of the reported service issues. To accomplish the ranking, the system can parse the reports of service issues on a periodic basis, can extract telemetry identifiers (IDs) from the logs, can query the telemetry, may compute the relative importance of detected issues (in the context of calls going on for that day), and then can report this impact back to the service issue database.

Abstract: Computer-aided identification of a potential problem node in a network. As part of data collection, a computing system gathers telemetric and trace route data for communications that occur within a network. Upon detecting that a performance problem has occurred within the network, multiple communications that occurred around the time of the performance problem are identified. Then, the trace route data for these multiple communications are aggregated. The aggregated data may then be used to identify a potential problem network node within the network. The identity of the potential problem network node (and potentially observed telemetry for that network node) may then be communicated to an entity that is affected by the performance problem. This may allow the entity to understand which network node is causing the problem and thus take appropriate remedial measures.

Abstract: A privacy image generation system may use a light field camera that includes an array of cameras or an RGBZ camera(s)) is used to capture images and display images according to a selected privacy mode. The privacy mode may include a blur background mode that can be automatically selected based on the meeting type, participants, location, and device type. A region of interest and/or an object(s) of interest (e.g. one or more persons in a foreground) is determined and the privacy image generation system is configured to clearly show the region/object of interest and obscure or replace the background by combining multiple images. The displayed image includes the region/object(s) of interest clearly shown (e.g. in focus) and any objects in a background of the combined image shown having a limited depth of field (e.g. blurry/not in focus) and/or blurred due to the combination of the multiple images.

Abstract: Provided herein are systems, methods, and software for facilitating a video environment. In at least one implementation, video of at least a first object to be displayed in the video environment is received. Video of at least a second object is also received which is to be displayed with the first object in the video environment. A zoom operation is identified to be performed on the first object to reduce a difference between a size of the first object and a size of the second object. The zoom operation is then performed on the video of the first object. In response to the zoom operation, the first object and the second object are displayed in the video environment.

Abstract: A privacy image generation system may use a light field camera that includes an array of cameras or an RGBZ camera(s)) is used to capture images and display images according to a selected privacy mode. The privacy mode may include a blur background mode and a background replacement mode and can be automatically selected based on the meeting type, participants, location, and device type. A region of interest and/or an object(s) of interest (e.g. one or more persons in a foreground) is determined and the privacy image generation system is configured to clearly show the region/object of interest and obscure or replace the background according to the selected privacy mode. The displayed image includes the region/object(s) of interest clearly shown (e.g. in focus) and any objects in a background of the combined image shown having a limited depth of field (e.g. blurry/not in focus) and/or the background replaced with another image and/or fill.

Abstract: Various examples related to determining a location of an active participant are provided. In one example, image data of a room from an image capture device is received. First audio data from a first microphone array at the image capture device is received. Second audio data from a second microphone array spaced from the image capture device is received. Using a three dimensional model, a location of the second microphone array is determined. Using the first audio data, second audio data, location of the second microphone array, and an angular orientation of the second microphone array, an estimated location of the active participant is determined.

Abstract: Provided herein are systems, methods, and software for facilitating collaboration environments. In at least one implementation, a presentation of an initial view of a collaboration scene is presented within a collaboration environment. A portion of the collaboration scene is identified that corresponds to an object of interest selected for separate viewing. A separate presentation within the collaboration environment is initiated related to the portion of the scene corresponding to the object of interest.

Abstract: Provided herein are systems, methods, and software for facilitating a video environment. In at least one implementation, video of at least a first object to be displayed in the video environment is received. Video of at least a second object is also received which is to be displayed with the first object in the video environment. A zoom operation is identified to be performed on the first object to reduce a difference between a size of the first object and a size of the second object. The zoom operation is then performed on the video of the first object. In response to the zoom operation, the first object and the second object are displayed in the video environment.

Abstract: Provided herein are systems, methods, and software for facilitating a video conference environment. In at least one implementation, video captured of a scene is received. A modification to display of the video is identified based at least in part on a share of a display space associated with an object in the scene relative to a share of another display space associated with another object in another scene. The modification to the display of the video is then initiated. In another implementation, the modification may also be based on a target share indicated by way of an interactive graphic.

Abstract: Provided herein are systems, methods, and software for facilitating collaboration environments. In at least one implementation, a presentation of an initial view of a collaboration scene is presented within a collaboration environment. A portion of the collaboration scene is identified that corresponds to an object of interest selected for separate viewing. A separate presentation within the collaboration environment is initiated related to the portion of the scene corresponding to the object of interest.

Abstract: A privacy camera, such as a light field camera that includes an array of cameras or an RGBZ camera(s)) is used to capture images and display images according to a selected privacy mode. The privacy mode may include a blur background mode and a background replacement mode and can be automatically selected based on the meeting type, participants, location, and device type. A region of interest and/or an object(s) of interest (e.g. one or more persons in a foreground) is determined and the privacy camera is configured to clearly show the region/object of interest and obscure or replace the background according to the selected privacy mode. The displayed image includes the region/object(s) of interest clearly shown (e.g. in focus) and any objects in a background of the combined image shown having a limited depth of field (e.g. blurry/not in focus) and/or the background replaced with another image and/or fill.

Abstract: Various examples related to determining a location of an active participant are provided. In one example, image data of a room from an image capture device is received. First audio data from a first microphone array at the image capture device is received. Second audio data from a second microphone array spaced from the image capture device is received. Using a three dimensional model, a location of the second microphone array is determined. Using the first audio data, second audio data, location of the second microphone array, and an angular orientation of the second microphone array, an estimated location of the active participant is determined.

Abstract: Various examples related to determining a location of an active speaker are provided. In one example, image data of a room from an image capture device is received and a three dimensional model is generated. First audio data from a first microphone array at the image capture device is received. Second audio data from a second microphone array laterally spaced from the image capture device is received. Using the three dimensional model, a location of the second microphone array with respect to the image capture device is determined. Using the audio data and the location and angular orientation of the second microphone array, an estimated location of the active speaker is determined. Using the estimated location, a setting for the image capture device is determined and outputted to highlight the active speaker.