Deep ahs: a deep learning approach to acoustic howling suppression
AssigneeTencent America LLC
InventorsHao ZHANG, Meng YU, Dong YU
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Abstract
A method and apparatus comprising computer code configured to cause a processor or processors to receive an audio signal obtained from a microphone, input the audio signal into a neural-network based AHS model, wherein the neural-network based AHS model is trained using a training audio signal, and output an AHS signal from the neural-network based AHS model in which AHS is applied to the audio signal, wherein the AHS signal is a version of the audio signal in which acoustic howling noise of the audio signal is suppressed and target audio of the audio signal is sustained.
Claims20
A method of acoustic howling suppression (AHS), the method performed by at least one processor and comprising:
- receiving an audio signal obtained from a microphone;
- inputting the audio signal into a neural-network based AHS model, wherein the neural-network based AHS model is trained using a training audio signal;
- and
- outputting an AHS signal from the neural-network based AHS model in which AHS is applied to the audio signal, wherein the AHS signal is a version of the audio signal in which acoustic howling noise of the audio signal is suppressed and target audio of the audio signal is sustained.
An apparatus for video coding, the apparatus comprising:
- at least one memory configured to store computer program code;
- at least one processor configured to access the computer program code and operate as instructed by the computer program code, the computer program code including:
- receiving code configured to cause the at least one processor to receive an audio signal obtained from a microphone;
- inputting code configured to cause the at least one processor to input the audio signal into a neural-network based AHS model, wherein the neural-network based AHS model is trained using a training audio signal;
- and
- outputting code configured to cause the at least one processor to output an AHS signal from the neural-network based AHS model in which AHS is applied to the audio signal, wherein the AHS signal is a version of the audio signal in which acoustic howling noise of the audio signal is suppressed and target audio of the audio signal is sustained.
A non-transitory computer readable medium storing a program causing a computer to:
- receive an audio signal obtained from a microphone;
- input the audio signal into a neural-network based AHS model, wherein the neural-network based AHS model is trained using a training audio signal;
- and
- output an AHS signal from the neural-network based AHS model in which AHS is applied to the audio signal, wherein the AHS signal is a version of the audio signal in which acoustic howling noise of the audio signal is suppressed and target audio of the audio signal is sustained.
Dependencies are inferred from the claim text.