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TIMIT Preprocessor

timit-preprocessor extract mfcc vectors and phones from TIMIT dataset for advanced use on speech recognition.

Overview

The TIMIT corpus of read speech is designed to provide speech data for acoustic-phonetic studies and for the development and evaluation of automatic speech recognition systems. More information on website or Wiki The instructions and scripts used here are built upon timit-preprocessor. make_dataset.py relies on kaldi-io-for-python

Dependencies

You must have downloaded the TIMIT dataset. You must have a compiled version of Kaldi.

Note that to install Kaldi first by following the instructions in INSTALL.

(1)
go to tools/ and follow INSTALL instructions there.

(2) go to src/ and follow INSTALL instructions there.

After running the scripts instructed by INSTALL in tools/, there will be reminder as followed. Go and run it.

Kaldi Warning: IRSTLM is not installed by default anymore. If you need IRSTLM, use the script extras/install_irstlm.sh

Preprocessing

Steps

  1. source the python interpreter matching the requirement.txt file.
$ source ../../pyenv/bin/activate
  1. Edit the default of variables KALDI_ROOT, TIMIT_ROOT, DATA_OUT in the Makefile to match your installation. You can also leave the default as is and use make with location arguments.
$ make KALDI_ROOT=abc/kaldi  TIMIT_ROOT=abc/timit DATA_OUT=abc/out ...
  1. Run the following commands (here without location arguments):
$ make convert
$ make -j 4

Note 1: noisy .wav files will be created alongside timit clean ones.

Note 2: In case of errors, display the remaining steps:

$ make -n

and try to debug them one by one.

Note 3: For serious problems you can always contact us in the [issues] section.

Acknowledgment

Some codes of the TIMIT Preprocessor are from the following repo: TIMIT Preprocessor