Sri International

Maneesh Yadav

Patrick Denis Lincoln

Christopher Connolly

Bhaskar S Ramamurthy

Harry Bratt

Colleen Richey

David E Huber

Kevin Luebke

John Cornwell

Kathryn G Todd

Matthew D Puster

Keith Laderoute

A speech recognition module receives training data of speech and creates a representation for individual words, non-words, phonemes, and any combination. A set of speech processing detectors analyze the training data of speech from humans communicating. The set of speech processing detectors detect speech parameters that are indicative of paralinguistic effects on top of enunciated words, phonemes, and non-words in the audio stream. One or more machine learning models undergo supervised machine learning on their neural network to train on how to associate one or more mark-up markers with a textual representation, for each individual word, individual non-word, individual phoneme, and any combinations of these, that was enunciated with a particular paralinguistic effect. Each mark-up marker can correspond to its own paralinguistic effect.

Controllable, natural paralinguistics for text to speech synthesis

Embodiments in accordance with the present disclosure are directed to methods and apparatuses used for evaluating a protein in a sample using proteolysis and translocation. An example method includes isolating a single protein from a sample in a chamber having at least a first well and a second well separated from the first well by a membrane with a nanopore, the nanopore providing fluidic communication between the first and second wells. The single protein is cleaved into a plurality of peptide fragments via exposure to a protease in the first well, and translocated through the nanopore by applying an electric potential to the nanopore in the chamber after cleavage of the single protein by the protease. The method further includes detecting events indicative of the translocations of the plurality of peptide fragments through the nanopore and to the second well.

Apparatuses and methods involving protein exploration through proteolysis and nanopore translocation

Systems and methods of generating and applying a synthetic neuromodulatory signal are described. A subject may be put under a particular condition that causes an effect in the subject. While the subject is under the condition, a recording of neurogram signals derived from the condition can be made from the subject. For example, neuronal signals traveling on the vagus nerve of the subject may be monitored and recorded. The neurogram may then be used to create a synthetic neuromodulatory signal that can be administered to a user. When the synthetic neuromodulatory signal is administered to the user, the user may experience the same effect as the subject that had been placed in the condition, even though the user was never put under the same condition.

Methods and systems for stimulating nerve signals

A method, apparatus and system for enabling the searchable storage of sequential application programs includes normalizing the sequential application programs, canonicalizing the sequential application programs, determining a unique identifier for each of the sequential application programs, and storing the unique identifier for each of the sequential application programs. The stored, unique identifier for the canonicalized sequential application programs can then be searched to, for example, determine if a sequential application program is stored and/or to certify at least one of the stored, canonicalized sequential application programs.

Searchable storage of sequential application programs

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San Francisco, CA, United States of America

Maneesh Yadav