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A NEURAL-NETWORK-BASED APPROACH FOR SPEECH DENOISING STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

机译:基于神经网络的语音去噪方法关于联邦资助研究的声明

摘要

Disclosed are methods, systems, device, and other implementations, including a method that includes receiving an audio signal representation, detecting in the received audio signal representation, using a first learning model, one or more silent intervals with reduced foreground sound levels, determining based on the detected one or more silent intervals an estimated full noise profile corresponding to the audio signal representation, and generating with a second learning model, based on the received audio signal representation and on the determined estimated full noise profile, a resultant audio signal representation with a reduced noise level.
机译:公开了方法、系统、设备和其他实现,包括一种方法,该方法包括接收音频信号表示,使用第一学习模型在所接收的音频信号表示中检测一个或多个具有降低前景声级的静音间隔,基于检测到的一个或多个静默间隔确定与音频信号表示相对应的估计全噪声剖面,并基于接收到的音频信号表示和确定的估计全噪声剖面,使用第二学习模型生成具有降低噪声电平的结果音频信号表示。

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