1 / 17

Speech Processing

Speech Processing. Dr. Veton Këpuska, FIT Jacob Zurasky, FIT. Front-End Speech Processing . Motivation

wynn
Download Presentation

Speech Processing

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Speech Processing Dr. Veton Këpuska, FIT Jacob Zurasky, FIT

  2. Front-End Speech Processing • Motivation Speech audio processing has increased in its usefulness especially after SIRI. To understand how the features are computed in such applications is very important. Hence we propose to implement feature extraction stage of speech processing application. • Applications • Speech Processing • Speech Coding • Speech Recognition • Speaker Recognition Dr. Veton Këpuska

  3. Typical MFCC Based System • Front-End Processing of a Speech Recognizer Features Speech Dr. Veton Këpuska

  4. Pre-emphasis log FFT Pre-emphasis Windowing Mel-Filter IFFT Dr. Veton Këpuska

  5. Pre-emphasis Filter Output Signal y Input Signal x Pre-emphasis Filter Dr. Veton Këpuska

  6. Windowing log FFT Pre-emphasis Windowing Mel-Filter IFFT Dr. Veton Këpuska

  7. Windowing Dr. Veton Këpuska

  8. Short-Time Analysis Dr. Veton Këpuska

  9. Short Time FFT log FFT Pre-emphasis Windowing Mel-Filter IFFT Dr. Veton Këpuska

  10. An FFT Spectrogram Some have walked through pain and sorrow to bring you their message of hope Dr. Veton Këpuska

  11. Mel-Frequency Filter log FFT Pre-emphasis Windowing Mel-Filter IFFT Dr. Veton Këpuska

  12. Mel-Frequency Scale Dr. Veton Këpuska

  13. Mel-Frequency Scale Dr. Veton Këpuska

  14. Log and IFFT log FFT Pre-emphasis Windowing Mel-Filter IFFT Dr. Veton Këpuska

  15. Proposed Work; Related Knowledge • Signal Processing: • Windowing • Filtering • Math knowledge • Fourier Transform • Mel-Filtering • Cepstrum • Programming: • Matlab Fundamentals • Signal Processing Toolbox Functionality • Algorithms • Fast Fourier Transform • Cepstral Analysis Dr. Veton Këpuska

  16. Proposed Work Timeline • Week 1: • How to Use MATLAB • Week 2: • Fundamentals of Signal Processing • Introduction of Filtering, Averaging • Week 3: • Windowing • Fast Fournier Transform • Cepstral Transform • Week 4: • Implementation of MFCC Processing • Week 5: • Implementation of MFCC Processing • Week 6: • Work on deliverables Dr. Veton Këpuska

  17. END Thank You! Questions?

More Related