PROJECT PROPOSAL

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PROJECT PROPOSAL

• Shamalee Deshpande

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Problem Statement

• Extracting soft biometric features
• Age
• Gender
• Accent

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Speaker Database

• A Speaker database from the LDC Corpus Catalog
• Preferable use half the speaker set for training
  and the later half for verification of results
• Contain varying gender, age and accent

Linguistic Data Consortium, http//www.ldc.upenn.
edu/Catalog/
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Possible Computation for Gender

• Pitch
• In Cepstrum Analysis, Formants are completely
  removed from the spectrum thus isolating the
  pitch frequency. LPC also used to find pitch
• Pitch is used to classify speech with regards to
  Gender
• Av Males100-132Hz Av Females142-256Hz

LOG
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Possible Computation for Accent

• People usually have characteristic styles of
  pronouncing phonemes from an early age dependant
  on the primary language learned.
• Cepstral coefficients may again be used and
  presumably the MFCCs for the analysis of the
  speech spectrum to identify local/non-local
  speakers in a database.

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Possible Computation for Age
Vocal tract length is said to be a good
classifier of the age of a speaker Formant
frequencies derived using LPC co-relate to the
length of the vocal tract Children are said to
have a higher formant frequency range than
adults Specifically, elderly speakers are said to
have lower formant frequencies F1,F2,F3 than
their younger counterparts more so seen with
regards to F1