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VAD (Voice Activity Detector)

VAD (Voice Activity Detector). Supervised by Dr. Kepuska By Preetham Nosum. VAD. Part of Front End Module – Spectrum, MFCC Detects speech using various features Overall flag set when individual flags are all ON. Tools. Visual C++ - Parameters stored into respective extensions Matlab

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VAD (Voice Activity Detector)

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  1. VAD(Voice Activity Detector) Supervised by Dr. Kepuska By Preetham Nosum

  2. VAD • Part of Front End Module – Spectrum, MFCC • Detects speech using various features • Overall flag set when individual flags are all ON

  3. Tools • Visual C++ - Parameters stored into respective extensions • Matlab - Graphs plotted from the data

  4. VAD Features • Energy Feature • MFCC Feature • Spectrum Feature • MFCC Enhanced Feature

  5. Energy Feature • Input used from the previous module – Frame energy • Mean Frame energy calculated • Compared to current frame energy • Energy flag set if the difference is high • Mean not calculated during the VAD ON stage

  6. MFCC Feature • MFCC feature calculated from vector • Each frame compared to the overall mean mfcc • Deviation from mean sets the MFCC flag • Mean not calculated during the VAD ON stage

  7. Spectrum Feature • Uses Variance for detectioin • How much the signal changed after each frame • Mean compared to variance • Flag is set after a certain threshold is crossed

  8. MFCC Enhanced Feature • Uses Hybrid of Spectrum and MFCC • Two ways to detect: Variance mean and Variance of variance • Most sensitive of all features • Flag set ON/OFF based on two different conditions

  9. Logic • Overall flag set when all the flags are turned on • Overall flag turned off when any one of the feature flags is turned off • Waits certain frames to make sure it’s speech

  10. Future • Needs more refinement • Test the MFCC and MFCC Enhanced features with different set of MFCC vector values • Test with more data

  11. Refrences • Discrete-Time Speech Signal Processing, Thomas F. Quantieri

  12. Questions?

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