公开(公告)号：US09600764B1

公开(公告)日：2017-03-21

申请号：US14307412

申请日：2014-06-17

Applicant: Amazon Technologies, Inc.

Inventor： Ariya Rastrow ,  Spyros Matsoukas ,  Sri Venkata Surya Siva Rama Krishna Garimella ,  Nikko Ström ,  Bjorn Hoffmeister

IPC: G06F15/18 ,  G06N3/08

CPC classification number: G06N3/08 ,  G06N3/0445 ,  G06N3/049

Abstract: Features are disclosed for using a neural network to tag sequential input without using an internal representation of the neural network generated when scoring previous positions in the sequence. A predicted or determined label (e.g., the highest scoring or otherwise most probable label) for input at a given position in the sequence can be used when scoring input corresponding to the next position the sequence. Additional features are disclosed for training a neural network for use in tagging sequential input without using an internal representation of the neural network generated when scoring previous positions the sequence.

公开(公告)号：US10032463B1

公开(公告)日：2018-07-24

申请号：US14982587

申请日：2015-12-29

Applicant: Amazon Technologies, Inc.

Inventor： Ariya Rastrow ,  Nikko Ström ,  Spyridon Matsoukas ,  Markus Dreyer ,  Ankur Gandhe ,  Denis Sergeyevich Filimonov ,  Julian Chan ,  Rohit Prasad

IPC: G10L15/183 ,  G10L15/197 ,  G10L15/16 ,  G10L25/30 ,  G10L15/26 ,  G10L15/06 ,  G10L15/22

Abstract: An automatic speech recognition (“ASR”) system produces, for particular users, customized speech recognition results by using data regarding prior interactions of the users with the system. A portion of the ASR system (e.g., a neural-network-based language model) can be trained to produce an encoded representation of a user's interactions with the system based on, e.g., transcriptions of prior utterances made by the user. This user-specific encoded representation of interaction history is then used by the language model to customize ASR processing for the user.

公开(公告)号：US09653093B1

公开(公告)日：2017-05-16

申请号：US14463411

申请日：2014-08-19

Applicant: Amazon Technologies, Inc.

Inventor： Spyridon Matsoukas ,  Nikko Ström ,  Ariya Rastrow ,  Sri Venkata Surya Siva Rama Krishna Garimella

IPC: G10L15/16 ,  G10L25/30 ,  G10L15/07 ,  G10L15/08 ,  G10L15/14

CPC classification number: G10L15/16 ,  G10L15/08 ,  G10L15/142 ,  G10L15/144

Abstract: Features are disclosed for using an artificial neural network to generate customized speech recognition models during the speech recognition process. By dynamically generating the speech recognition models during the speech recognition process, the models can be customized based on the specific context of individual frames within the audio data currently being processed. In this way, dependencies between frames in the current sequence can form the basis of the models used to score individual frames of the current sequence. Thus, each frame of the current sequence (or some subset thereof) may be scored using one or more models customized for the particular frame in context.

公开(公告)号：US10354184B1

公开(公告)日：2019-07-16

申请号：US14313906

申请日：2014-06-24

Applicant: Amazon Technologies, Inc.

Inventor： Shiv Naga Prasad Vitaladevuni ,  Nikko Ström ,  Rohit Prasad

IPC: G06N7/02 ,  G06N7/04 ,  G06N7/06 ,  G06N7/08 ,  G06N3/08

Abstract: A system and method is disclosed for predicting user behavior in response to various tasks and or/applications. This system can be a neural network-based joint model. The neural network can include a base neural network portion and one or more task-specific neural network portions. The artificial neural network can be initialized and trained using data from multiple users for multiple tasks and/or applications. This user data can be related to characteristics and behavior, including age, gender, geographic location, purchases, past search history, and customer reviews. Additional task-specific neural network portions can be added to the neural network and may be trained using a task-specific subset of the training data. The joint model can be used to predict user behavior in response to an identified task and/or application. The tasks and/or applications can relate to use of a website by users.