/dnn

Primary LanguageC

File system

  • data/ (data main dir)
  • data/fbank
  • data/label
  • data/mfcc
  • data/phones
  • data/merge (create by your self)
  • dnn/ (git main dir)
  • dnn/hw1 (all hw1 file in here)
  • dnn/hw1/out (test prediction csv file will generate to this dir)
  • dnn/hw1/save_models (for model saving)

Data preprocessing

  1. create merge dir in data/
  2. run read.py
  3. run fbank.py
  4. run mfcc.py
  5. run l48to39.py

Compile main program

  1. Download Eigen from Eigen main website
  2. link path/to/Eigen to your include path
  3. go to hw1 dir
  4. type "make main" in hw1
    • You could also use g++ -O2 --std=c++11 main.cpp -o main -Ipath/to/Eigen if you don't want to include Eigen in your include path.

Run main program

  1. run main by ./main
  2. it will output test prediction for every 5000 mini-batchs to out/ in default settings

For concatenated frame feature training

  1. run new_fbank.py
  2. run new_l48to39.py
  3. set the parameters in new_main.cpp
  4. type make new_main or make omp_new_main if you want to use cpu parallelism
  5. run program by ./new_main or ./omp_new_main
  6. default settings have the best result parameters