Myanmar Language Speech Recognition with Hybrid Artificial Neural Network and Hidden Markov Model Thin

@inproceedings{Nwe2015MyanmarLS,
  title={Myanmar Language Speech Recognition with Hybrid Artificial Neural Network and Hidden Markov Model Thin},
  author={Thin Thin Nwe and Theingi Myint},
  year={2015}
}
There are many artificial intelligence approaches used in the development of Automatic Speech Recognition (ASR), hybrid approach is one of them. The common hybrid method in speech recognition is the combination of Artificial Neural Network (ANN) and Hidden Markov Model (HMM). The hybrid ANN/HMM is able to classify the phoneme model and to combine the strength of HMM in sequential modeling structure. Thus, this paper proposed a speaker independent and continuous Myanmar Language speech… CONTINUE READING
1 Citations
8 References
Similar Papers

References

Publications referenced by this paper.
Showing 1-8 of 8 references

Balakrishnan-Aiyer S, “Performance of the IBM Large Vocabulary Continuous Speech Recognition System

  • LR Bahl
  • in Pro ICASSP
  • 1995
1 Excerpt

lakrishnan PS, “A Fast Admissible Method for Identifying a short list of candidate words”,Computer speech and language,Vol

  • L Bahl, Gopa
  • 1992
1 Excerpt

IEEE Transactions on acoustic speech and signal processing, “High performance connected digit recognition using Hidden Markov Model”,vol.37.No.8

  • R Lawrence, Rabiner, Fellow
  • 1989
2 Excerpts

A Fast Admissible Method for Identifying a short list of candidate words ”

  • L Bahl, PS Gopalakrishnan
  • Computer speech and language

Similar Papers

Loading similar papers…