公开(公告)号：US11532300B1

公开(公告)日：2022-12-20

申请号：US16913996

申请日：2020-06-26

Applicant: AMAZON TECHNOLOGIES, INC.

Inventor： Daniel Kenneth Bone ,  Viktor Rozgic ,  Chao Wang

IPC: G10L15/18 ,  G10L15/16

Abstract: A device with a microphone acquires audio data of a user's speech. A neural network accepts audio data as input and provides sentiment data as output. The neural network is trained using training data based on input from raters who provide votes as to which sentiment descriptors they think are associated with a sample of speech. A vote by a rater assessing the sample for a particular semantic descriptor is distributed to a plurality of semantically similar semantic descriptors. Semantic descriptor similarity data indicates relative similarity between possible semantic descriptors in the semantic space. The distributed partial votes may be aggregated to produce training data comprising samples of speech and weights of corresponding semantic descriptors. The training data is then used to train the neural network. For example, the neural network may be trained with the training data using per-instance cosine similarity loss or correlational loss.

公开(公告)号：US11302329B1

公开(公告)日：2022-04-12

申请号：US16914589

申请日：2020-06-29

Applicant: Amazon Technologies, Inc.

Inventor： Ming Sun ,  Spyridon Matsoukas ,  Venkata Naga Krishna Chaitanya Puvvada ,  Chao Wang ,  Chieh-Chi Kao

IPC: G10L15/22 ,  G10L15/08

Abstract: A system may include an acoustic event detection component for detecting acoustic events, which may be non-speech sounds. Upon detection of a command to detect a new sound, a device may prompt a user to cause occurrence of the sound one or more times. The acoustic event detection component may then be reconfigured, using audio data corresponding to the occurrences, to detect future occurrences of the event.

公开(公告)号：US20210104245A1

公开(公告)日：2021-04-08

申请号：US16429689

申请日：2019-06-03

Applicant: Amazon Technologies, Inc.

Inventor： Gustavo Alfonso Aguilar Alas ,  Viktor Rozgic ,  Chao Wang

IPC: G10L15/26 ,  G10L15/06 ,  G06F17/27 ,  G10L15/16

Abstract: Described herein is a system for sentiment detection in audio data. The system is trained using acoustic information and lexical information to determine a sentiment corresponding to an utterance. In some cases when lexical information is not available, the system (trained on acoustic and lexical information) is configured to determine a sentiment using only acoustic information.

公开(公告)号：US10943604B1

公开(公告)日：2021-03-09

申请号：US16456158

申请日：2019-06-28

Applicant: Amazon Technologies, Inc.

Inventor： Daniel Kenneth Bone ,  Chao Wang ,  Viktor Rozgic

IPC: G10L25/63 ,  G10L17/04

Abstract: Described herein is a system for emotion detection in audio data using a speaker's baseline. The baseline may represent a user's speaking style in a neutral emotional state. The system is configured to compare the user's baseline with input audio representing speech from the user to determine a emotion of the user. The system may store multiple baselines for the user, each associated with a different context (e.g., environment, activity, etc.), and select one of the baselines to compare with the input audio based on the contextual situation.