PREDIKSI JEDA DALAM UCAPAN KALIMAT BAHASA INDONESIA DENGAN HIDDEN MARKOV MODEL
Abstract: This study describes
the design of the pauses predictor application of speech sentences in Bahasa
Indonesia with Hidden Markov Model (HMM). This application serves to determine
the pauses event that occur in Bahasa Indonesia sentences. There are two main
processes in this application which is train to train the corpus, and
prediction to predict pause. On the train, the input text is produced from
sound files, and the output is training corpus for HMM engine. In the
prediction process, inputs are words of Bahasa, and outputs are pause
prediction that occurred earlier in the input sentence. The results of this
study is the sentence that has been predicted in each pause events. Testing is
done using precision and recall of training corpus and tagging pause prediction
results. The results of precision and recall is calculated back to the f-score.
Based on the testing that has been done, showed that the designed applications
can already predict a pause in the Indonesian sentences with precision of 0.364,
recall of 0.132, and F-score of 0.194
Penulis: Adhitya Teguh Nugraha
Kode Jurnal: jptinformatikadd140177
