Amazon Technologies, Inc.

Spyros Matsoukas

Ariya Rastrow

Bjorn Hoffmeister

Shiv Naga Prasad Vitaladevuni

Nikko Strom

Ming Sun

Sri Venkata Surya Siva Rama Krishna Garimella

Yixin Gao

Nikko Ström

David Snyder

A method for selective transmission of audio data to a speech processing server uses detection of an acoustic trigger in the audio data in determining the data to transmit. Detection of the acoustic trigger makes use of an efficient computation approach that reduces the amount of run-time computation required, or equivalently improves accuracy for a given amount of computation, by combining a 'time delay' structure in which intermediate results of computations are reused at various time delays, thereby avoiding computation of computing new results, and decomposition of certain transformations to require fewer arithmetic operations without sacrificing significant performance. For a given amount of computation capacity the combination of these two techniques provides improved accuracy as compared to current approaches.

Acoustic trigger detection

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.

Markov-based sequence tagging using neural networks

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Hopkinton, MA, United States of America

Spyros Matsoukas