Abstract: Facilitating avatar modifications for learning and other videotelephony sessions in advanced networks is provided herein. Operations of a system include evaluating a recorded interaction associated with a first entity during consumption of a first portion of a video conference determined to include the first entity. The operations also can include transforming an actual representation of the first entity in the recorded interaction to an avatar representation, resulting in an edited interaction of the first entity. Further, the operations can include outputting the edited interaction of the first entity for consumption of a second portion of the video conference by rendering the edited interaction for a second entity.

Abstract: Facilitating avatar modifications for learning and other videotelephony sessions in advanced networks is provided herein. Operations of a system include evaluating a recorded interaction associated with a first entity during consumption of a first portion of a video conference determined to include the first entity. The operations also can include transforming an actual representation of the first entity in the recorded interaction to an avatar representation, resulting in an edited interaction of the first entity. Further, the operations can include outputting the edited interaction of the first entity for consumption of a second portion of the video conference by rendering the edited interaction for a second entity.

Abstract: A processing system may obtain a downscaled version of a reference copy of a video, comprising a plurality of downscaled versions of a plurality of frames of the reference copy of the video, obtain a first recorded frame of a first variant of a plurality of variants associated with the reference copy of the video, where the plurality of variants comprises a plurality of copies of the video encoded at different bitrates, generate a first downscaled version of the first recorded frame, calculate a first plurality of image distances between the first downscaled version of the first recorded frame and the plurality of downscaled versions of the plurality of frames of the reference copy of the video, and determine a first frame index of the first recorded frame in accordance with a first least image distance from among the first plurality of image distances that is calculated.

Abstract: A processing system including at least one processor may generate a plurality of visual tracks from a source visual content, where the plurality of visual tracks comprises visual tracks of different visual quality levels and with different intra frame offsets, apply at least one network condition within a communication network, transmit one or more visual streams to one or more client devices via the communication network, where the one or more visual streams includes frames selected from among the plurality of visual tracks, and measure at least one quality metric for at least one of the one or more visual streams in accordance with the applying of the at least one network condition within the communication network.

Abstract: A processing system may obtain a downscaled version of a reference copy of a video, comprising a plurality of downscaled versions of a plurality of frames of the reference copy of the video, obtain a first recorded frame of a first variant of a plurality of variants associated with the reference copy of the video, where the plurality of variants comprises a plurality of copies of the video encoded at different bitrates, generate a first downscaled version of the first recorded frame, calculate a first plurality of image distances between the first downscaled version of the first recorded frame and the plurality of downscaled versions of the plurality of frames of the reference copy of the video, and determine a first frame index of the first recorded frame in accordance with a first least image distance from among the first plurality of image distances that is calculated.

Abstract: Facilitating avatar modifications for learning and other videotelephony sessions in advanced networks is provided herein. Operations of a system include evaluating a recorded interaction associated with a first entity during consumption of a first portion of a video conference determined to include the first entity. The operations also can include transforming an actual representation of the first entity in the recorded interaction to an avatar representation, resulting in an edited interaction of the first entity. Further, the operations can include outputting the edited interaction of the first entity for consumption of a second portion of the video conference by rendering the edited interaction for a second entity.

Abstract: Personalized content delivery (e.g., using a computerized tool) is enabled. For example, a system can comprise: a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: determining a quality of service metric representative of a quality of service of streamed content delivered via a content delivery network, determining a quality of experience metric representative of a quality of experience associated with a user profile of a consumer of the streamed content, and based on the quality of service and the quality of experience, modifying the streamed content.

Abstract: Personalized content delivery (e.g., using a computerized tool) is enabled. For example, a system can comprise: a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: determining a quality of service metric representative of a quality of service of streamed content delivered via a content delivery network, determining a quality of experience metric representative of a quality of experience associated with a user profile of a consumer of the streamed content, and based on the quality of service and the quality of experience, modifying the streamed content.

Abstract: Concepts and technologies disclosed herein are directed to audio and video synchronization. According to one aspect disclosed herein, an audio-video (“AV”) synchronization system can simultaneously capture samples of a pre-encode media stream and a post-encode media stream. The pre-encode media stream can include AV content prior to being encoded. The post-encode media stream can include the AV content after being encoded. The AV synchronization system can align a pre-encode video component of the pre-encode media stream with a post-encode video component and can determine a video offset therebetween. The AV synchronization system can align a pre-encode audio component of the pre-encode media stream with a post-encode audio component of the post-encode media stream and can determine an audio offset therebetween. The AV synchronization system can then compare the video offset and the audio offset to determine if the post-encode media stream is synchronized with the pre-encode media stream.

Abstract: A processing system may obtain a downscaled version of a reference copy of a video, comprising a plurality of downscaled versions of a plurality of frames of the reference copy of the video, obtain a first recorded frame of a first variant of a plurality of variants associated with the reference copy of the video, where the plurality of variants comprises a plurality of copies of the video encoded at different bitrates, generate a first downscaled version of the first recorded frame, calculate a first plurality of image distances between the first downscaled version of the first recorded frame and the plurality of downscaled versions of the plurality of frames of the reference copy of the video, and determine a first frame index of the first recorded frame in accordance with a first least image distance from among the first plurality of image distances that is calculated.

Abstract: Concepts and technologies disclosed herein are directed to audio and video synchronization. According to one aspect disclosed herein, an audio-video (“AV”) synchronization system can simultaneously capture samples of a pre-encode media stream and a post-encode media stream. The pre-encode media stream can include AV content prior to being encoded. The post-encode media stream can include the AV content after being encoded. The AV synchronization system can align a pre-encode video component of the pre-encode media stream with a post-encode video component and can determine a video offset therebetween. The AV synchronization system can align a pre-encode audio component of the pre-encode media stream with a post-encode audio component of the post-encode media stream and can determine an audio offset therebetween. The AV synchronization system can then compare the video offset and the audio offset to determine if the post-encode media stream is synchronized with the pre-encode media stream.

Abstract: A processing system may obtain a downscaled version of a reference copy of a video, comprising a plurality of downscaled versions of a plurality of frames of the reference copy of the video, obtain a first recorded frame of a first variant of a plurality of variants associated with the reference copy of the video, where the plurality of variants comprises a plurality of copies of the video encoded at different bitrates, generate a first downscaled version of the first recorded frame, calculate a first plurality of image distances between the first downscaled version of the first recorded frame and the plurality of downscaled versions of the plurality of frames of the reference copy of the video, and determine a first frame index of the first recorded frame in accordance with a first least image distance from among the first plurality of image distances that is calculated.

Abstract: A processing system may obtain a downscaled version of a reference copy of a video, comprising a plurality of downscaled versions of a plurality of frames of the reference copy of the video, obtain a first recorded frame of a first variant of a plurality of variants associated with the reference copy of the video, where the plurality of variants comprises a plurality of copies of the video encoded at different bitrates, generate a first downscaled version of the first recorded frame, calculate a first plurality of image distances between the first downscaled version of the first recorded frame and the plurality of downscaled versions of the plurality of frames of the reference copy of the video, and determine a first frame index of the first recorded frame in accordance with a first least image distance from among the first plurality of image distances that is calculated.

Abstract: A buffer classification system calculates first flow metrics for a first flow in response to receiving first packet level data. The system in response to receiving HTTP information, generates buffer emulation data and creates one or more data training sets using the first flow metrics and buffer emulation data, wherein training data used to create the one or more training data sets is further generated by computing an average throughput per second observed over different time windows during a video playback. The system in response to creating the one or more training data sets, generates one or more classifier rules used to determine a buffer condition of a flow. The system in response to receiving second packet level data, calculates second flow metrics for a second flow and predicts a buffer condition for the second flow based on the second flow metrics and the one or more classifier rules.

Abstract: A processing system may obtain a first frame of a first variant associated with a reference copy of a video, where a plurality of variants comprises copies of the video encoded at different bitrates, determine a frame number of the first frame from a visual overlay containing the first frame number, calculate a first image distance between the first frame and a frame of the reference copy having the frame number, determine, from among a plurality of image distances for frames of each variant having the frame number, a closest image distance to the first image distance, the plurality of image distances comprising image distances between frames of the variants and the frame of the reference copy having the frame number, and identify the first frame as being from the first variant in accordance with a variant associated with the first closest image distance.

Abstract: A processing system may obtain a first frame of a first variant associated with a reference copy of a video, where a plurality of variants comprises copies of the video encoded at different bitrates, determine a frame number of the first frame from a visual overlay containing the first frame number, calculate a first image distance between the first frame and a frame of the reference copy having the frame number, determine, from among a plurality of image distances for frames of each variant having the frame number, a closest image distance to the first image distance, the plurality of image distances comprising image distances between frames of the variants and the frame of the reference copy having the frame number, and identify the first frame as being from the first variant in accordance with a variant associated with the first closest image distance.

Abstract: A buffer classification system comprising: a buffer emulator; a metrics calculator; a learning module; a training module; a classification module; wherein the buffer emulator is connected to a trusted proxy on a network, the trusted proxy in communication with a client server; the buffer emulator and metrics calculator are connected to the trusted proxy; the buffer emulator emulating a buffer condition of the trusted proxy; the metrics calculator is configured obtain at least one measurement from a flow between the trusted proxy and a client; wherein the learning module is configured to map the buffer condition to the at least one measurement, and communicates a mapped metric to the training module; wherein the training module is configured to define at least one classifier rules to predict a buffer condition from a calculated metric; and wherein the training module transmits the at least one classifier rule to a classifier module, the classifier module having an input configured to receive a user flow, the c