Abstract: A computer implemented method processes audio streams recorded during a meeting by a plurality of distributed devices.

Abstract: The invention features diagnostic and therapeutic methods and compositions featuring androgen receptor variant proteins and nucleic acid molecules whose expression is increased in androgen related diseases or disorders.

Abstract: A computer implemented method includes receiving audio signals representative of speech via multiple audio streams transmitted from corresponding multiple distributed devices, performing, via a neural network model, continuous speech separation for one or more of the received audio signals having overlapped speech, and providing the separated speech on a fixed number of separate output audio channels.

Abstract: Techniques are described for implementing an out-of-band communication channel used to exchange control channel information in sub-carrier-based optical communication systems. In an example implementation, a transmitter includes a laser operable to supply an optical signal, a digital signal processor operable to supply first electrical signals based on first data input to the digital signal processor and second data input to the digital signal processor, digital-to-analog conversion circuitry operable to output second electrical signals based on the first electrical signals, modulator driver circuitry is operable to output third electrical signals based on the second electrical signals, and an optical modulator operable to supply first and second modulated optical signals based on the third electrical signals. The first modulated optical signal includes a plurality of optical subcarriers carrying user data. The plurality of optical subcarriers also being amplitude modulated to carry control information.

Abstract: A method for semi-automated labeling of data for machine learning training. Data is collected via time-series sensors to form an unlabeled dataset. After receiving one or more event type labels for a subset of the dataset, thereby forming a labeled dataset, the remainder of the unlabeled dataset is automatically labeled. Potential new labels for the remainder of the unlabeled dataset are determined via cross correlation between the labeled dataset and unlabeled dataset. The potential new labels are presented as training data for a machine learning algorithm.

Abstract: A transcription of audio speech included in electronic content associated with a meeting is created by an ASR model trained on speech-to-text data. The transcription is post-processed by modifying text included in the transcription, for example, by modifying punctuation, grammar, or formatting introduced by the ASR model and by changing or omitting one or more words that were included in both the audio speech and the transcription. After the transcription is post-processed, output based on the post-processed transcription is generated in the form of a meeting summary and/or template.

Abstract: Systems and methods for performing impairment compensation in point-to-multi-point communication systems are described. In a data snapshot mode, a hub node can send instructions to each communication node connected to the hub node to send a data snapshot of data being received and processed by the communication nodes at a particular time. In a trench line mode, a hub node sends instructions to each communication node to send trench line data back to the hub node. The hub node uses the data snapshot or trench line data to determine how to tune filter coefficients in the hub node to perform impairment compensation and improve performance of the communication system.

Abstract: A computer implemented method includes receiving information streams on a meeting server from a set of multiple distributed devices included in a meeting, receiving audio signals representative of speech by at least two users in at least two of the information streams, receiving at least one video signal of at least one user in the information streams, associating a specific user with speech in the received audio signals as a function of the received audio and video signals, and generating a transcript of the meeting with an indication of the specific user associated with the speech.

Abstract: A transcription of audio speech included in electronic content associated with a meeting is created by an ASR model trained on speech-to-text data. The transcription is post-processed by modifying text included in the transcription, for example, by modifying punctuation, grammar, or formatting introduced by the ASR model and by changing or omitting one or more words that were included in both the audio speech and the transcription. After the transcription is post-processed, output based on the post-processed transcription is generated in the form of a meeting summary and/or template.

Abstract: A transcription of audio speech included in electronic content associated with a meeting is created by an ASR model trained on speech-to-text data. The transcription is post-processed by modifying text included in the transcription, for example, by modifying punctuation, grammar, or formatting introduced by the ASR model and by changing or omitting one or more words that were included in both the audio speech and the transcription. After the transcription is post-processed, output based on the post-processed transcription is generated in the form of a meeting summary and/or template.

Abstract: Techniques enabling improved classification of touch or hover interactions of objects with a touch sensitive surface of a device are presented. A speaker of the device can emit an ultrasonic audio signal comprising a first frequency distribution. A microphone of the device can detect a reflected audio signal comprising a second frequency distribution. The audio signal can be reflected off of an object in proximity to the surface to produce the reflected audio signal. A classification component can determine movement status of the object, or classify the touch or hover interaction, in relation to the surface, based on analysis of the signals. The classification component also can classify the touch or hover interaction based on such ultrasound data and/or touch surface or other sensor data. The classification component can be trained, using machine learning, to perform classifications of touch or hover interactions of objects with the surface.

Abstract: A computer implemented method includes receiving audio streams at a meeting server from two distributed devices that are streaming audio captured during an ad-hoc meeting between at least two users, comparing the received audio streams to determine that the received audio streams are representative of sound from the ad-hoc meeting, generating a meeting instance to process the audio streams in response to the comparing determining that the audio streams are representative of sound from the ad-hoc meeting, and processing the received audio streams to generate a transcript of the ad-hoc meeting.

Abstract: Described herein are composition and method for manufacturing a cultured plant-based dairy alternative based on fermenting ancient grains. In one aspect, the composition contains flour of one or more ancient grains, one or more plant seed butters, one or more plant-based creams, one or more texturizers or stabilizers, and water that is cultured to form a hypoallergenic plant-based dairy alternative containing no added monosaccharides or disaccharides.

Abstract: A computer implemented method processes audio streams recorded during a meeting by a plurality of distributed devices.

Abstract: Disclosed herein are compositions and methods for detecting biological molecules and biomarkers associated with prostate cancer. Disclosed herein are compositions and methods for detecting biological molecules and biomarkers associated with castration-resistant prostate cancer wherein such biological molecules and biomarkers comprise androgen-receptor splice variants that can be used to develop effective therapeutic regimens for prostate cancer patients. Disclosed herein are methods of using biological molecules and biomarkers related to androgen-receptor splice variants for assessing therapeutic resistance to drugs such as enzalutamide and abiraterone.

Abstract: A computer implemented method processes audio streams recorded during a meeting by a plurality of distributed devices.

Abstract: Techniques enabling improved classification of touch or hover interactions of objects with a touch sensitive surface of a device are presented. A speaker of the device can emit an ultrasonic audio signal comprising a first frequency distribution. A microphone of the device can detect a reflected audio signal comprising a second frequency distribution. The audio signal can be reflected off of an object in proximity to the surface to produce the reflected audio signal. A classification component can determine movement status of the object, or classify the touch or hover interaction, in relation to the surface, based on analysis of the signals. The classification component also can classify the touch or hover interaction based on such ultrasound data and/or touch surface or other sensor data. The classification component can be trained, using machine learning, to perform classifications of touch or hover interactions of objects with the surface.

Abstract: Systems and methods for performing impairment compensation in point-to-multi-point communication systems are described. In a data snapshot mode, a hub node can send instructions to each communication node connected to the hub node to send a data snapshot of data being received and processed by the communication nodes at a particular time. In a trench line mode, a hub node sends instructions to each communication node to send trench line data back to the hub node. The hub node uses the data snapshot or trench line data to determine how to tune filter coefficients in the hub node to perform impairment compensation and improve performance of the communication system.

Abstract: Techniques enabling improved classification of touch or hover interactions of objects with a touch sensitive surface of a device are presented. A speaker of the device can emit an ultrasonic audio signal comprising a first frequency distribution. A microphone of the device can detect a reflected audio signal comprising a second frequency distribution. The audio signal can be reflected off of an object in proximity to the surface to produce the reflected audio signal. A classification component can determine movement status of the object, or classify the touch or hover interaction, in relation to the surface, based on analysis of the signals. The classification component also can classify the touch or hover interaction based on such ultrasound data and/or touch surface or other sensor data. The classification component can be trained, using machine learning, to perform classifications of touch or hover interactions of objects with the surface.

Abstract: A computer implemented method includes receiving audio signals representative of speech via multiple audio streams transmitted from corresponding multiple distributed devices, performing, via a neural network model, continuous speech separation for one or more of the received audio signals having overlapped speech, and providing the separated speech on a fixed number of separate output audio channels.