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Hi everyone,

I am working on a problem statement where I need to extract the relevant part/section from audio files. for instance my data has audio files of engines with background noise - birds, people conversation, etc.

I read couple of papers which have mainly used PCA for denoising the noise. Couple of them have used SNR too. But I am not very convinced as how this can actually work considering that PCA take n-components value so how we can be sure that the components that it is picking up will actually not contain noise?. 

The articles/links that I explored for this are:

https://arxiv.org/pdf/1804.07177.pdf (applies SNR),

http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005995 ,

https://refractedrendition.wordpress.com/ + http://willdrevo.com/fingerprinting-and-audio-recognition-with-python/ + https://www.acrcloud.com/docs/acrcloud/introduction/audio-fingerprinting/  + http://www.cp.jku.at/research/papers/Sonnleitner_Dissertation.pdf + http://www.music.mcgill.ca/~ich/classes/mumt621_09/fingerprinting/cano05review.pdf +n http://www.ismir2002.ismir.net/proceedings/02-FP04-2.pdf + http://www.ismir2002.ismir.net/proceedings/02-FP04-2.pdf (audio-fingerprinting),

Any lead as to how this relevant part extraction can be done would be very helpful to me.

Looking forward to getting good leads in solving this problem.

Best,

Priya Arora

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