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Signal Processing

2018

Vocal processing

Articles 1 - 3 of 3

Full-Text Articles in Engineering

Vocal Processing With Spectral Analysis, Bradley J. Fitzgerald Dec 2018

Vocal Processing With Spectral Analysis, Bradley J. Fitzgerald

ELAIA

A well-known signal processing issue is that of the “cocktail party problem,” which A well-known signal processing issue is that of the “cocktail party problem,” which refers to the need to be able to separate speakers from a mixture of voices. A solution to this problem could provide insight into signal separation in a variety of signal processing fields. In this study, a method of vocal signal processing was examined to determine if principal component analysis of spectral data could be used to characterize differences between speakers and if these differences could be used to separate mixtures of vocal signals. …


Vocal Processing With Spectral Analysis, Bradley Fitzgerald May 2018

Vocal Processing With Spectral Analysis, Bradley Fitzgerald

Honors Program Projects

A well-known signal processing issue is that of the “cocktail party problem”, which refers to the need to be able to separate speakers from a mixture of voices. A solution to this problem could provide insight into signal separation in a variety of signal processing fields. In this study, a method of vocal signal processing was examined to determine if principal component analysis of spectral data may be used to characterize differences between speakers and if these differences may be used to separate mixtures of vocal signals. Processing was done on a set of voice recordings from 30 different speakers …


Vocal Processing With Spectral Analysis, Brad Fitzgerald Apr 2018

Vocal Processing With Spectral Analysis, Brad Fitzgerald

Scholar Week 2016 - present

A method of vocal signal processing was examined to determine if principal component analysis of spectral data may be used to characterize differences between speakers and if these differences may be used to separate mixtures of vocal signals. Processing was done on a set of voice recordings from 30 different speakers in order to create a projection matrix which could be used by an algorithm to identify the source of an unknown recording from one of the 30 speakers. Two different identification algorithms were tested, both of which were generally unable to correctly identify the source of a single vocal …