Monday, 25 April 2016

DSPP APPLICATION

The last experiment, was a group experiment. We were asked to perform signal processing on a 1D signal and find out an application for the same.  The application that we selected was 'Noise Reduction Using Adaptive Filters'. The group members are Kapil Rawal, Prerana Sarode,Chinmay Upadhye and Harshit Shukla.

Summary of the paper I referred to.
A new adaptive speech noise removal algorithm was proposed based on a two-stage Wiener filtering. A first Wiener filter is used to produce a smoothed estimate of the a priori signal-to-noise ratio (SNR), aided by a classifier that separates speech from noise frames, and a second Wiener filter is used to generate the final output. Spectral analysis and synthesis is performed by a modulated complex lapped transform (MCLT).
Patent
An array of microphones utilizes two sets of two microphones for noise suppression. A primary microphone and secondary microphone of the three microphones may be positioned closely spaced to each other to provide acoustic signals used to achieve noise cancellation. A tertiary microphone may be spaced with respect to either the primary microphone or the secondary microphone in a spread-microphone configuration for deriving level cues from audio signals provided by tertiary and the primary or secondary microphone.

http://preranasarode1995.blogspot.com/2016/04/the-last-experiment-was-group-experiment.html

4 comments:

  1. Atleast correct the spelling of my name (Upadhye)

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  2. well written, upload link for your paper and patents

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  3. In signal processing, the Wiener filter is a filter used to produce an estimate of a desired or target random process by linear time-invariant (LTI) filtering of an observed noisy process.

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  4. In the application we have selected we use 2 Wiener filters.

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