DSP

• hw1 - discrete HMM in c++

• train.cpp

  • Given O and an initial model λ=(A, B, π), adjust λ to minimize P(O|λ)
  • Baum-Welch algorithm

• test.cpp

  • Given model λ and O, find the best state sequenceto minimize P(O|λ,q)
  • Viterbi Algorithm

• iterating 155 times will have the highest accuarcy in 1~400 times

• hw2 - shell script

  • modify shell script to train data, test data in order to get higher accuracy

  • using Hidden Markov Toolkit (HTK)

• hw3 - in c++

  • build a character-based language model with toolkit SRILM

  • mapping.cpp

    • turn Big5-ZhuYin.map to ZhuYin-Big5.map

  • disambig.cpp

    • Viterbi algorithm to find out the most possible sequence