Skip to content

Let start with feature extraction in "march 2018 progress.ipynb" (Jupyter notebook) then speechRecog.py

Notifications You must be signed in to change notification settings

GolfSuradej/Blind-T60-estimation-using-LSTM

Repository files navigation

blind T60 estimation using LSTM

Digital signal processing hand-on for feature extraction that implement with python (Jupyter notebook)

-Convolution of room impulse response and speech signal

-Seven-Octave bandpass filterbank

-Envelope extraction using Ayncronous Complex Hilbert Transfrom

-MCFF (Mel Ceptrum Frequency Function)

Dataset/Corpus: 1.SMILE from JAIST (RIR) 2.Aachen University (RIR) 3.Open AIR Library (RIR) 4.TIMIT (Speech) 5.Centre for Speech Technology Research,University of Edinburgh (Speech) 6.CSTR VCTK Corpus,English Multi-speaker Corpus for CSTR Voice Cloning Toolkit University of Edinburgh (Speech) 7.Speech Synthesis

About

Let start with feature extraction in "march 2018 progress.ipynb" (Jupyter notebook) then speechRecog.py

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published