Abstract: Disclosed is an dynamic speech recognition system and associated methods for improving speech recognition accuracy by biasing, tuning, and/or otherwise adjusting a speech recognition model to account or compensate for different speech characteristics of individual speakers and/or different environmental factors that have different effects on the characteristics of the audio recorded from each speaker. The system receives an audio stream, identifies a speaker in the audio stream, selects a first vector that is generated by a first machine learning model and that encodes speech characteristics of the speaker, selects a second vector that is generated by a second machine learning model and that encodes audio characteristics that affect a capture of the audio stream, and adjusts a third machine learning model based on the first vector and the second vector. The system uses the third machine learning model after it is adjusted to convert speech into text.

Abstract: Disclosed is a system and associated methods for secure media stream distribution across different platforms associated with different Internet domains. A first node of a first platform receives a first request from a device, performs a first verification based on credentials provided by the device matching stored credentials, generates a first signed token, and provides the first signed token with a second link for the device to access the requested media stream from a second network node of a second platform. The second network node determines that the device was verified at the first network node based on a second stream request from the device including the first signed token, generates a second token that uniquely identifies the device in the second domain, and streams requested stream data to the device in response to performing a second verification based on requests for the stream data including the second token.

Abstract: Disclosed is a system and associated methods for secure media stream distribution across different platforms associated with different Internet domains. A first node of a first platform receives a first request from a device, performs a first verification based on credentials provided by the device matching stored credentials, generates a first signed token, and provides the first signed token with a second link for the device to access the requested media stream from a second network node of a second platform. The second network node determines that the device was verified at the first network node based on a second stream request from the device including the first signed token, generates a second token that uniquely identifies the device in the second domain, and streams requested stream data to the device in response to performing a second verification based on requests for the stream data including the second token.

Abstract: Disclosed is a system and associated methods for secure media stream distribution across different platforms associated with different Internet domains. A first node of a first platform receives a first request from a device, performs a first verification based on credentials provided by the device matching stored credentials, generates a first signed token, and provides the first signed token with a second link for the device to access the requested media stream from a second network node of a second platform. The second network node determines that the device was verified at the first network node based on a second stream request from the device including the first signed token, generates a second token that uniquely identifies the device in the second domain, and streams requested stream data to the device in response to performing a second verification based on requests for the stream data including the second token.

Abstract: The present disclosure provides systems and methods for enhancing audio communications. In one aspect, the present disclosure provides a method for enhancing audio communications. The method may comprise (a) detecting one or more parameters associated with a medical procedure and one or more audio communications associated with the medical procedure; and (b) processing the one or more audio communications based on the one or more parameters to generate one or more enhanced audio communications.

Abstract: Systems and methods for medical resource intelligence are provided. Systems and methods are provided for identifying appropriate remote users to contact based on a plurality of factors including availability and operator preference.

Abstract: The present disclosure provides methods and systems for video collaboration. The method may comprise (a) obtaining a plurality of videos of a surgical procedure; (b) determining an amount of progress for the surgical procedure based at least in part on the plurality of videos; and (c) updating an estimated timing of one or more steps of the surgical procedure based at least in part on the amount of progress. The method may further comprise providing the estimating timing to one or more end users to coordinate another surgical procedure or patient room turnover. In some cases, the method may comprise (a) obtaining a plurality of videos of a surgical procedure and (b) providing the plurality of videos to a plurality of end users, wherein each end user of the plurality of end users receives a different subset of the plurality of videos.

Abstract: Systems and methods for medical procedure preparation are provided. Systems and methods are provided for identifying appropriate medical resources to prepare, prior to a medical procedure. Systems and methods are provided for automatically updating records of medical personnel preferences based on usage. Optionally, scheduling and forecasting of location availability may occur in real-time. Furthermore, medical console identifiers may be used to aid in the systems and methods provided herein.

Abstract: Systems and methods for video analysis are provided. The systems and methods may utilize machine learning to recognize steps of a medical procedure as they are being performed, and compare them with expected steps. The systems and methods may aid in supporting a medical practitioner before the procedure, during the procedure, as well as providing feedback after the procedure has been completed.

Abstract: Systems and methods for machine vision/audio use and analysis are provided. Systems and methods are provided for identifying medical conditions based on data collected during a procedure. Systems and methods are provided for providing recommendations relating to procedures based on data collected during a procedure. Furthermore, recommendations may be provided relating to products and potential improvements based on data collected during a procedure.

Abstract: Systems and methods for medical resource intelligence are provided. Systems and methods are provided for identifying appropriate remote users to contact, and for assessing productivity of such remote users. Systems and methods are provided for forecasting usage of medical resources. Furthermore, performance may be tracked in accordance with one or more metrics with aid of a video collaboration system.

Abstract: Described are platforms, systems, media, and methods for enterprise resource planning and tracking inventory. The systems and methods provided herein may be able to allow for items at a health care facility to be tracked in real-time. Item storage and item usage may be updated in real-time. In some instances, information associated with items may be accessed and presented to individuals who are managing or using the items.

Abstract: A method, a device, and a non-transitory storage medium are described in which a power of late reverberation of a speech signal is estimated based on early samples of the speech signal. The power of the late reverberation may be subtracted linearly or non-linearly from the speech signal.

Abstract: A method, a device, and a non-transitory storage medium are described in which a power of late reverberation of a speech signal is estimated based on early samples of the speech signal. The power of the late reverberation may be subtracted linearly or non-linearly from the speech signal.

Abstract: An exemplary method includes a cloud-based service provider system detecting an input command provided by a user during a scheduling session and representative of a request for a local digital video recording (“DVR”) system to record a media program during a presentation time period. In response to the detecting of the input command, the cloud-based service provider system identifies a conflict associated with the request for the local DVR system to record the media program, performs a prioritization operation to determine a relative priority of media programs that are at least one of scheduled to be recorded by the local DVR system at any given time during the presentation time period and currently recorded in a memory of the local DVR system, and automatically performs, based on the performing of the prioritization operation, a predetermined action to resolve the conflict and facilitate the local DVR system recording the media program.

Abstract: Techniques, described herein, may enable a computing device (e.g., a set-top-box, a user equipment (UE), etc.) with an array of sensors (e.g., microphones, antennas, etc.) to engage in beamforming in a manner that optimizes the signal strength of the target signal. For example, the computing device may create an optimized beam pattern by applying a pre-selected band width to a steering direction of the target signal. The beam width may include steering vectors at equal, angular distances from the steering direction, enabling steep transition slopes to be applied to the optimized beam pattern. In some implementations, the beam width and transition slopes may be standardized, such that the optimized beam pattern for any signal may be uniform, regardless of variables such as frequency and time.

Abstract: Techniques, described herein, may enable a computing device (e.g., a set-top-box, a user equipment (UE), etc.) with an array of sensors (e.g., microphones, antennas, etc.) to engage in beamforming in a manner that optimizes the signal strength of the target signal. For example, the computing device may create an optimized beam pattern by applying a pre-selected band width to a steering direction of the target signal. The beam width may include steering vectors at equal, angular distances from the steering direction, enabling steep transition slopes to be applied to the optimized beam pattern. In some implementations, the beam width and transition slopes may be standardized, such that the optimized beam pattern for any signal may be uniform, regardless of variables such as frequency and time.

Abstract: A method, a system, and a non-transitory storage medium provides to store first recording information that indicates programs that are recorded and stored at user devices, and programs to be recorded and stored at the user devices, receive, from a user device, a message that includes second recording information, wherein the second recording information includes second data instances; compare a portion of the first recording information with the second recording information; determine whether there is a difference between each first data instance relative to each corresponding second data instance; determine a master source for each first data instance that differs from each corresponding second data instance; update each first data instance that differs, one of the network device or the user device based on the master source, and provide the DVR service based on an updated portion of the first recording information, an updated second recording information, or both.

Abstract: A method, a system, and a non-transitory storage medium provides to store first recording information that indicates programs that are recorded and stored at user devices, and programs to be recorded and stored at the user devices, receive, from a user device, a message that includes second recording information, wherein the second recording information includes second data instances; compare a portion of the first recording information with the second recording information; determine whether there is a difference between each first data instance relative to each corresponding second data instance; determine a master source for each first data instance that differs from each corresponding second data instance; update each first data instance that differs, one of the network device or the user device based on the master source, and provide the DVR service based on an updated portion of the first recording information, an updated second recording information, or both.

Abstract: An exemplary method includes a cloud-based service provider system detecting an input command provided by a user during a scheduling session and representative of a request for a local digital video recording (“DVR”) system to record a media program during a presentation time period. In response to the detecting of the input command, the cloud-based service provider system identifies a conflict associated with the request for the local DVR system to record the media program, performs a prioritization operation to determine a relative priority of media programs that are at least one of scheduled to be recorded by the local DVR system at any given time during the presentation time period and currently recorded in a memory of the local DVR system, and automatically performs, based on the performing of the prioritization operation, a predetermined action to resolve the conflict and facilitate the local DVR system recording the media program.