Splitting PhonemesAdam Burkhalter

Duong ChauMicah Lee

Project Overview

● Isolate phonemes in a signalo Read in an audio fileo Separate the individual phonemeso Determine phoneme signatureo Output results

Audio Reader Application

● Audio Recorder using Javao Save audio as .WAVo Save audio as bytes

● Playback audio● Add saved audio

Key Algorithm Vocabulary

● Phonemes● Exponential Sinusoidal Model● Accumulated Autocorrelated Functions● Transients● Variable Segmentation Strategy

Phonemes

Is a basic unit of a language’s phonology, which is combined with other phonemes to form meaningful units such as words or morphemes.

Cow has 2 phonemes: \c and \ou

Example of Phonemes

/A/ a (table), a_e (bake), ai (train), ay (say)/a/ a (flat)/b/ b (ball)/k/ c (cake), k (key), ck (back)/d/ d (door)/E/ e (me), ee (feet), ea (leap), y (baby)

Transients

● High amplitude, short-duration sound ● At beginning of a waveform● Occurs in phenomena such as musical

sounds, noises or speech

Phoneme Boundaries

● Transients model phoneme boundaries

Exponential Sinusoidal Model (ESM)

● Amplifies signal contento Extreme values get amplifiedo Low values do not

● Helps determine phoneme boundaries

Accumulated Autocorrelated Functions (AACF)

● Determines the coefficients of the ESM

Variable Segmentation Strategy

● Uses high difference transients to determine phoneme boundaries

● Boundaries are used to isolate phonemes for processing

Phoneme Processing

● FFT analysis to determine signal composition

● FFT data used to create filter banks● Filter banks used to identify phonemes● Identified phonemes are characterized● Results displayed

References

Parameterizing Speech Phonemes by Exponential Sinusoidal Model- Jayanth Kumar Talasila and Pradip Sircar