Amazon Technologies, Inc.

Anirudh Raju

Arindam Mandal

Spyridon Matsoukas

Shiva Kumar Sundaram

Minhua Wu

Kenichi Kumatani

Ariya Rastrow

Ankur Gandhe

Raefer Christopher Gabriel

Chandra Prakash Khatri

Behnam Hedayatnia

Anushree Venkatesh

Ahmad Shikib Mehri

Described herein is a system for rescoring automatic speech recognition hypotheses for conversational devices that have multi-turn dialogs with a user. The system leverages dialog context by incorporating data related to past user utterances and data related to the system generated response corresponding to the past user utterance. Incorporation of this data improves recognition of a particular user utterance within the dialog.

Speech recognition using dialog history

Systems and methods for utilizing microphone array information for acoustic modeling are disclosed. Audio data may be received from a device having a microphone array configuration. Microphone configuration data may also be received that indicates the configuration of the microphone array. The microphone configuration data may be utilized as an input vector to an acoustic model, along with the audio data, to generate phoneme data. Additionally, the microphone configuration data may be utilized to train and/or generate acoustic models, select an acoustic model to perform speech recognition with, and/or to improve trigger sound detection.

Speech processing optimizations based on microphone array

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San Jose, CA, United States of America

Anirudh Raju