公开(公告)号：US10854192B1

公开(公告)日：2020-12-01

申请号：US15084600

申请日：2016-03-30

Applicant: Amazon Technologies, Inc.

Inventor： Roland Maas ,  Ariya Rastrow ,  Rohit Prasad

IPC: G10L21/00 ,  G10L25/00 ,  G10L15/05 ,  G10L25/78 ,  G10L15/26

Abstract: An automatic speech recognition (ASR) system detects an endpoint of an utterance based on a domain of the utterance. The ASR system processes a first portion of the utterance to determine the domain and then determines an endpoint of the remainder of the utterance depending on the domain.

公开(公告)号：US20170270919A1

公开(公告)日：2017-09-21

申请号：US15196228

申请日：2016-06-29

Applicant: Amazon Technologies, Inc.

Inventor： Sree Hari Krishnan Parthasarathi ,  Bjorn Hoffmeister ,  Brian King ,  Roland Maas

IPC: G10L15/20 ,  G10L15/16 ,  G10L25/87 ,  G10L15/08 ,  G10L15/02 ,  G10L17/06

CPC classification number: G10L15/20 ,  G10L15/02 ,  G10L15/08 ,  G10L15/16 ,  G10L17/02 ,  G10L17/06 ,  G10L17/18 ,  G10L25/87 ,  G10L2015/088 ,  G10L2025/783

Abstract: A system configured to process speech commands may classify incoming audio as desired speech, undesired speech, or non-speech. Desired speech is speech that is from a same speaker as reference speech. The reference speech may be obtained from a configuration session or from a first portion of input speech that includes a wakeword. The reference speech may be encoded using a recurrent neural network (RNN) encoder to create a reference feature vector. The reference feature vector and incoming audio data may be processed by a trained neural network classifier to label the incoming audio data (for example, frame-by-frame) as to whether each frame is spoken by the same speaker as the reference speech. The labels may be passed to an automatic speech recognition (ASR) component which may allow the ASR component to focus its processing on the desired speech.

公开(公告)号：US11514901B2

公开(公告)日：2022-11-29

申请号：US16437763

申请日：2019-06-11

Applicant: Amazon Technologies, Inc.

Inventor： Sree Hari Krishnan Parthasarathi ,  Bjorn Hoffmeister ,  Brian King ,  Roland Maas

IPC: G10L15/20 ,  G10L15/02 ,  G10L17/06 ,  G10L25/87 ,  G10L15/08 ,  G10L15/16 ,  G10L17/18 ,  G10L25/78 ,  G10L17/02

Abstract: A system configured to process speech commands may classify incoming audio as desired speech, undesired speech, or non-speech. Desired speech is speech that is from a same speaker as reference speech. The reference speech may be obtained from a configuration session or from a first portion of input speech that includes a wakeword. The reference speech may be encoded using a recurrent neural network (RNN) encoder to create a reference feature vector. The reference feature vector and incoming audio data may be processed by a trained neural network classifier to label the incoming audio data (for example, frame-by-frame) as to whether each frame is spoken by the same speaker as the reference speech. The labels may be passed to an automatic speech recognition (ASR) component which may allow the ASR component to focus its processing on the desired speech.

公开(公告)号：US20200035231A1

公开(公告)日：2020-01-30

申请号：US16437763

申请日：2019-06-11

Applicant: Amazon Technologies, Inc.

Inventor： Sree Hari Krishnan Parthasarathi ,  Bjorn Hoffmeister ,  Brian King ,  Roland Maas

IPC: G10L15/20 ,  G10L15/02 ,  G10L17/06 ,  G10L25/87 ,  G10L15/08 ,  G10L15/16 ,  G10L17/18

Abstract: A system configured to process speech commands may classify incoming audio as desired speech, undesired speech, or non-speech. Desired speech is speech that is from a same speaker as reference speech. The reference speech may be obtained from a configuration session or from a first portion of input speech that includes a wakeword. The reference speech may be encoded using a recurrent neural network (RNN) encoder to create a reference feature vector. The reference feature vector and incoming audio data may be processed by a trained neural network classifier to label the incoming audio data (for example, frame-by-frame) as to whether each frame is spoken by the same speaker as the reference speech. The labels may be passed to an automatic speech recognition (ASR) component which may allow the ASR component to focus its processing on the desired speech.

公开(公告)号：US10373612B2

公开(公告)日：2019-08-06

申请号：US15196228

申请日：2016-06-29

Applicant: Amazon Technologies, Inc.

Inventor： Sree Hari Krishnan Parthasarathi ,  Bjorn Hoffmeister ,  Brian King ,  Roland Maas

IPC: G10L15/02 ,  G10L15/08 ,  G10L15/16 ,  G10L15/20 ,  G10L17/02 ,  G10L17/06 ,  G10L17/18 ,  G10L25/78 ,  G10L25/87

Abstract: A system configured to process speech commands may classify incoming audio as desired speech, undesired speech, or non-speech. Desired speech is speech that is from a same speaker as reference speech. The reference speech may be obtained from a configuration session or from a first portion of input speech that includes a wakeword. The reference speech may be encoded using a recurrent neural network (RNN) encoder to create a reference feature vector. The reference feature vector and incoming audio data may be processed by a trained neural network classifier to label the incoming audio data (for example, frame-by-frame) as to whether each frame is spoken by the same speaker as the reference speech. The labels may be passed to an automatic speech recognition (ASR) component which may allow the ASR component to focus its processing on the desired speech.