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Patent

Low complexity noise reduction method

Kamran Rahbar
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TLDR
In this article, a method of reducing noise in a speech signal using a fast Fourier transform (FFT) is proposed. But the method is not suitable for the frequency domain.
Abstract
A method of reducing noise in a speech signal involves converting the speech signal to the frequency domain using a fast fourier transform (FFT), creating a subset of selected spectral subbands, determining the appropriate gain for each subband, and interpolating the gains to match the number of FFT points. The converted speech signal is then filtered using the interpolated gains as filter coefficients, and an inverse FFT performed on the processed signal to recover the time domain output signal.

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Citations
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TL;DR: In this paper, the authors proposed a method for generating clean speech from a speech signal representing a mixture of a noise and speech using a model of speech using auditory and speech production principles.
References
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Patent

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TL;DR: In this article, an input signal is converted to frequency domain by discrete Fourier analysis and divided into Bark bands, and a noise estimate is subtracted from the signal in each band.
PatentDOI

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PatentDOI

System and process for locating a speaker using 360 degree sound source localization

TL;DR: In this article, a system and process for estimating the location of a speaker using signals output by a microphone array characterized by multiple pairs of audio sensors is described, and a consensus location for the speaker is computed from the individual location estimates associated with each pair of microphone array audio sensors taking into consideration the uncertainty of each estimate.
Patent

Method and apparatus for adaptively suppressing noise

TL;DR: In this paper, an apparatus and method for suppressing noise is presented, which utilizes a filter bank of bandpass filters to split the input noisy speech-containing signal into separate frequency bands.
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Communication system tonal component maintenance techniques

TL;DR: In this paper, a joint voice activity and DTMF activity detector (JVADADAD) is used to determine whether the input signal contains speech, DTMFs tones or silence, and the power estimation processes are adapted based on the signal activity indicated by the JVADAD.