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Contemporaneous machine-learning analysis of audio streams

机译:音频流的同期机学习分析

摘要

Described techniques select portions of an audio stream for transmission to a trained machine learning application, which generates response recommendations in real-time. This real-time response is facilitated by the system identifying, selecting and transmitting those portions of the audio stream likely to be most relevant to the conversation. Portions of an audio stream less likely to be relevant to the conversation are identified accordingly and not transmitted. The system may identify the relevant portions of an audio stream by detecting events in a contemporaneous event stream, use a trained machine learning model to identify events in an audio stream, or both.
机译:描述技术选择音频流的部分,用于传输到培训的机器学习应用程序,该应用程序实时生成响应建议。通过系统识别,选择和发送可能与对话最相关的音频流的那些部分的系统识别出该实时响应。相应地识别不太可能与对话相关的音频流的部分并未传输。系统可以通过检测在同时活动流中的事件中来识别音频流的相关部分,使用训练的机器学习模型来识别音频流中的事件,或两者。

著录项

  • 公开/公告号US11049497B1

    专利类型

  • 公开/公告日2021-06-29

    原文格式PDF

  • 申请/专利权人 CRESTA INTELLIGENCE INC.;

    申请/专利号US202017083486

  • 发明设计人 TIANLIN SHI;KENNETH GEORGE OETZEL;

    申请日2020-10-29

  • 分类号G10L15/16;G10L15/22;G06F21/62;G10L15/06;G10L25/51;G06N20;G10L15/08;H04M3/51;

  • 国家 US

  • 入库时间 2022-08-24 19:38:37

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