an approach in reproducing the auto-tune effect mentees: dong-san choi & tejas rawal mentor:...

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An Approach in Reproducing the Auto- Tune Effect Mentees: Dong-San Choi & Tejas Rawal Mentor: David Jun

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Page 1: An Approach in Reproducing the Auto-Tune Effect Mentees: Dong-San Choi & Tejas Rawal Mentor: David Jun

An Approach in Reproducing the Auto-

Tune Effect

Mentees: Dong-San Choi & Tejas Rawal Mentor: David Jun

Page 2: An Approach in Reproducing the Auto-Tune Effect Mentees: Dong-San Choi & Tejas Rawal Mentor: David Jun

Overview

• Quick introduction to Auto-Tune• Methodology in recreating the Auto-

Tune effect• Application

Page 3: An Approach in Reproducing the Auto-Tune Effect Mentees: Dong-San Choi & Tejas Rawal Mentor: David Jun

What is Auto-Tune?

• First created by Andy Hildebrand• Corrects out-of-tune human sung

pitches or instruments• How? Autocorrelation & Phase Vocoder• Demo using “I Am T-Pain”

Page 4: An Approach in Reproducing the Auto-Tune Effect Mentees: Dong-San Choi & Tejas Rawal Mentor: David Jun

Methodology

Can be broken into two parts:1) Pitch Detection

- Autocorrelation2) Pitch Shifting

- Phase Vocoder

Page 5: An Approach in Reproducing the Auto-Tune Effect Mentees: Dong-San Choi & Tejas Rawal Mentor: David Jun

Pitch Detection

• There are many different approaches to estimate the pitch of a periodic signal

• We used the autocorrelation function to determine the fundamental frequency of our speech signal

• Autocorrelation refers to the correlation of a time series with its own past and future values.

• It compares a segmented section of a speech signal (human voice) with another segment from the same signal and calculates the time separation between them. Autocorrelation is a mathematical tool that helps find repeating patterns, such as: – A periodic signal which has been buried under noise – The fundamental frequency in a signal implied by

its harmonic frequencies.

Page 6: An Approach in Reproducing the Auto-Tune Effect Mentees: Dong-San Choi & Tejas Rawal Mentor: David Jun

A Visual Representation

Page 7: An Approach in Reproducing the Auto-Tune Effect Mentees: Dong-San Choi & Tejas Rawal Mentor: David Jun

Pitch Shifting

• Pitch – 12 pure notes in an octave• Each note corresponds to a

frequency• “In-tune” notes • “Out-of-tune” notes• Pitch shifting in Auto-Tune

- use of a phase vocoder

Page 8: An Approach in Reproducing the Auto-Tune Effect Mentees: Dong-San Choi & Tejas Rawal Mentor: David Jun

The Phase Vocoder

Use - to obtain a digital representation of speech

Application - can modify basic speech parameters to

permit alteration of time or frequency dimensions of a speech signal

Page 9: An Approach in Reproducing the Auto-Tune Effect Mentees: Dong-San Choi & Tejas Rawal Mentor: David Jun

The Phase Vocoder

So…Inputs <= speech signalOutputs <= magnitude & phase

What can we do with these parameters?

Page 10: An Approach in Reproducing the Auto-Tune Effect Mentees: Dong-San Choi & Tejas Rawal Mentor: David Jun

Our Approach

Page 11: An Approach in Reproducing the Auto-Tune Effect Mentees: Dong-San Choi & Tejas Rawal Mentor: David Jun

Application• Auto-tune is a audio

processing system use to enhance a singer’s vocal performance

• Auto-tune uses a phase vocoder unit to correct pitch and disguise vocal mistakes

• Many famous artists such as T-Pain and Kanye West currently use Auto-tune to perfect the vocals on their tracks

Page 12: An Approach in Reproducing the Auto-Tune Effect Mentees: Dong-San Choi & Tejas Rawal Mentor: David Jun

Thank You for your Time!

Special thanks to the PURE program for the opportunity and our mentor, David Jun

Any Questions/Comments?