Google Inc.

Nuance Communications, Inc.

Effrosyni Kokiopoulou

Luciano Sbaiz

Jesse Berent

Lisa Amini

Pascal Frossard

Andrea Gesmundo

Dimitre Trendafilov

Oliver Verscheure

Krzysztof Stanislaw Maziarz

Gábor Bartók

Systems and methods for flexible parameter sharing for multi-task learning are provided. A training method can include obtaining a test input, selecting a particular task from one or more tasks, and training a multi-task machine-learned model for the particular task by performing a forward pass using the test input and one or more connection probability matrices to generate a sample distribution of test outputs, training the components of the machine-learned model based at least in part on the sample distribution, and performing a backwards pass to train a connection probability matrix of the multi-task machine-learned model using a straight-through Gumbel-softmax approximation.

Flexible parameter sharing for multi-task learning

A method for speech recognition, the method includes: extracting time-frequency speech features from a series of reference speech elements in a first series of sampling windows; aligning reference speech elements that are not of equal time span duration; constructing a common subspace for the aligned speech features; determining a first set of coefficient vectors; extracting a time-frequency feature image from a test speech stream spanned by a second sampling window; approximating the extracted image in the common subspace for the aligned extracted time-frequency speech features with a second coefficient vector; computing a similarity measure between the first and the second coefficient vector; determining if the similarity measure is below a predefined threshold; and wherein a match between the reference speech elements and a portion of the test speech stream is made in response to a similarity measure below a predefined threshold. The said reference speech elements correspond to a keyword of interest, wherein Simultaneous Orthogonal Matching Pursuit (SOMP) is used in their alignment.

Method and system for robust pattern matching in continuous speech for spotting a keyword of interest using orthogonal matching pursuit

A system for creating audiences for a shared content publisher, includes a data store comprising a computer readable medium storing a program of instructions for audiences for a shared content publisher; a processor that executes the program of instructions; a data processor to monitor access to an Internet web site by a first set of users for a reference time period; a window extraction module, based on a reference split period, to divide the monitored access into a vector X and a vector Y, wherein vector X is defined by accesses by the first set of users before the reference split period, and vector Y is defined by accesses by the first user after the reference split period; and a data analysis module to create a model based on the vector X and the vector Y, to evaluate the model based on a second set of users accessing content similar to vector X, to create a final model based on the evaluation, and to score a group of users associated with the shared content publisher based on the final model, the data processor monitors accesses by the first user by recording content or shared content identification and additional information items.

Automatic audience creation for shared content

Growing community of inventors

Adliswil, Switzerland

Effrosyni Kokiopoulou