Google Inc.

Apple Inc.

Oracle International Corporation

Hui Lin

Xiaoyuan Tu

Vincent Olivier Vanhoucke

Francoise Beaufays

Brian Strope

John Mark Beresniewicz

Xin Lei

Yun-hsuan Sung

Aditya Sarathy

Jui-Ting Huang

Vipul Manubhai Shah

Suresh B Malakar

Hsiao-te Su

Nauman Ahmed Chaudhry

Kyle Hailey

Embodiments are disclosed for user posture transition detection and classification using a linked biomechanical model. In an embodiment, a method comprises: obtaining motion data from a headset worn by a user; selecting features of a linked biomechanical model based on a current posture state; determining at least one probability that a posture transition occurred based on an output of a classifier, where the output of the classifier is based on the selected features and the motion data; determining a posture transition based on the at least one probability; and performing at least one action based on detection of the posture transition.

Posture transition detection and classification using linked biomechanical model

A method and system for frame-level merging of HMM state predictions determined by different techniques is disclosed. An audio input signal may be transformed into a first and second sequence of feature vector, the sequences corresponding to each other and to a temporal sequence of frames of the audio input signal on a frame-by-frame basis. The first sequence may be processed by a neural network (NN) to determine NN-based state predictions, and the second sequence may be processed by a Gaussian mixture model (GMM) to determine GMM-based state predictions. The NN-based and GMM-based state predictions may be merged as weighted sums for each of a plurality of HMM state on a frame-by-frame basis to determine merged state predictions. The merged state predictions may then be applied to the HMMs to speech content of the audio input signal.

Frame-level combination of deep neural network and gaussian mixture models

Speech recognition systems may perform the following operations: receiving audio; recognizing the audio using language models for different languages to produce recognition candidates for the audio, where the recognition candidates are associated with corresponding recognition scores; identifying a candidate language for the audio; selecting a recognition candidate based on the recognition scores and the candidate language; and outputting data corresponding to the selected recognition candidate as a recognized version of the audio.

Recognizing speech in multiple languages

A method and apparatus for diagnosing database performance problems using a plurality of wait classes is provided. A set of statistical data that describes current activity within a database system is periodically retrieved. The set of statistical data may include information about the current activity of each user session connected to the database system. Thereafter, a set of cumulative statistical data that describes activity in the database system over a period of time is updated to reflect the retrieved set of statistical data. The set of cumulative statistical data includes statistics associated with each of a plurality of wait classes. A graphical user interface that displays the set of cumulative statistical data may be presented to a user. The graphical user interface allows the user to quickly ascertain the nature of the database performance problems by providing a view of the set of cumulative statistical data.

Diagnosing database performance problems using a plurality of wait classes

Growing community of inventors

Sunnyvale, CA, United States of America

Hui Lin