Abstract:
A server or other computing device manages meetings in a virtual meeting room on behalf of a virtual meeting room owner. A request is received from an attendee to join a meeting in the virtual meeting room. A determination is made, based on configurations set by the virtual meeting room owner, whether to connect the attendee to a virtual waiting room. The attendee is connected to the virtual waiting room in accordance with the configurations set by the virtual meeting room owner.
Abstract:
A networking environment accessible by a plurality of computing devices is established to facilitate communications between participants associated with the computing devices, where content is generated and shared by participants via the networking environment. An item of content is shared with a group of recipients associated with computing devices via the networking environment, where the shared item of content includes one or more tags associated with the content, and each tag includes an initial weight value associated with the tag. A relevance factor associated with the group is determined, where the relevance factor is based upon information obtained from profiles of recipients from the group, and the initial weight value of each tag associated with the shared item of content is adjusted based at least in part upon the collective relevance factor associated with the group.
Abstract:
Systems, methods, and devices are disclosed for training a model. Media data is separated into one or more clusters, each cluster based on a feature from a first model. The media data of each cluster is sampled and, based on an analysis of the sampled media data, an accuracy of the media data of each cluster is determined. The accuracy is associated with the feature from the first model. Based on a subset dataset of the media data being outside a threshold accuracy, the subset dataset is automatically forwarded to a crowd source service. Verification of the subset dataset is received from the crowd source service, and the verified subset dataset is added to the first model.
Abstract:
A system and method for training a virtual assistant to recognize and learn new context for known terms is presented. The method includes receiving a natural language input, corresponding to at least one of a desired intent and a desired entity, at a natural language processor. The method involves scoring known intents based on the natural language input to generate an intent confidence score for each known intent, and scoring known entities based on the natural language input to generate an entity confidence score for each known entity. The method involves comparing the intent confidence scores and entity confidence scores to a threshold value, and determining that the natural language input does not correspond to at least one of the known intents and the known entities based on the comparing. Finally, at least one of a new intent and a new entity are determined based on the natural language input.
Abstract:
Systems and methods are disclosed for anticipating a video switch to accommodate a new speaker in a video conference comprising a real time video stream captured by a camera local to a first videoconference endpoint is analyzed according to at least one speaker anticipation model. The speaker anticipation model predicts that a new speaker is about to speak. Video of the anticipated new speaker is sent to the conferencing server in response to a request for the video on the anticipated new speaker from the conferencing server. Video of the anticipated new speaker is distributed to at least a second videoconference endpoint.
Abstract:
The disclosed technology relates to a process for automatically training a machine learning algorithm to recognize a custom wake word. By using different text-to-speech services, input providing a custom wake word to a text to speech service can be used in order to generate different speech samples covering different variations in how the custom wake word can be pronounced. These samples are automatically generated and are subsequently used to train the wake word detection algorithm that will be used by the computing device to recognize and detect when the custom wake word is uttered by any user nearby a computing device for the purposes of initiating a virtual assistant. In a further embodiment, “white-listed” words (e.g different words that are pronounced similar to the custom wake word) are also identified and trained in order to minimize the occurrence of erroneously initiating the virtual assistant.
Abstract:
The present technology can receive audio segments from sources within one or more conference room, and can create audio fingerprints from the sources. The audio fingerprints are optimized for audio in conference room environments, which include distortions from room impulse responses, and various encoding used by telecommunication networks. In some embodiments, when two audio segments are matched, a user equipment can be instructed to mute its speakers to avoid feedback. In some embodiments, when two audio segments are matched, a user equipment can be given instructions to join a conference taking place in the room in when the audio segment originated.
Abstract:
A method for communicating in a digital conversation is implemented on a computing device and includes: receiving an interactive contextual emoji from a first digital conversation participant to post in the digital conversation with at least a second digital conversation participant, where the interactive contextual emoji is pre-defined to indicate at least a current availability status associated with the first digital conversation participant, requesting the current availability status from a status application based on at least an indication of the interactive contextual emoji, where the status application maintains the current availability status, receiving the current availability status from the status application, and displaying the interactive contextual emoji in the digital conversation with at least an indication of the current availability status.
Abstract:
Systems and methods are disclosed for anticipating a video switch to accommodate a new speaker in a video conference comprising a real time video stream captured by a camera local to a first videoconference endpoint is analyzed according to at least one speaker anticipation model. The speaker anticipation model predicts that a new speaker is about to speak. Video of the anticipated new speaker is sent to the conferencing server in response to a request for the video on the anticipated new speaker from the conferencing server. Video of the anticipated new speaker is distributed to at least a second videoconference endpoint.
Abstract:
Disclosed is a system, method and computer readable medium enabling collaboration service providers to more accurately predict packet loss, jitter and delay based on current session, historical session and user location parameters. The prediction can be used to forecast the occurrence of poor media quality at the current location and potential future locations.