Judul: Pengembangan Hidden Markov Models untuk fonem berbahasa Indonesia pada sistem konversi suara ke teks
Abstrak: Speech to text transcription system is a system used to convert a voice signal from a microphone or a telephone into a single or a set of words. Research on speech to text transcription systems has been widely applied. But these systems tend to be developed based on words, hence they are inefficient when developed for a large vocabulary. This study uses Baum Welch algorithm for HMM training, Forward algorithm for HMM testing, and Mel-Frequency cepstral coefficient (MFCC) to extract voice features. Data used in this study consist of 5 words in Indonesian language. Phonemes are generated from the segmentation process, and then trained with Baum Welch algorithm to generate the model. This study produced 10 models. The best accuracy obtained is 82% generated by testing the HMM with 2 States and 5 epochs
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Judul: Pengenalan Kata Berbahasa Indonesia dengan Hidden  Markov Model (HMM) menggunakan Algoritme Baum-  Welch
Abstrak: Pengenalan suara atau Speech Recognition adalah proses konversi sebuah sinyal akustik, yang berasal dari mikropon atau telepon, menjadi satu atau sekumpulan kata. Sinyal suara sendiri merupakan gelombang yang tercipta dari tekanan udara yang berasal dari paru-paru yang berjalan melewati lintasan suara menuju mulut dan rongga hidung, sehingga memiliki frekuensi yang berbeda. Agar sistem komputer dapat mengenali sebuah kata, maka dibutuhkan representasi yang tepat terhadap sinyal-sinyal yang masuk berikut perubahan frekuensinya dalam rentang waktu tertentu. Penelitian ini menggunakan Algoritme Baum-Welch dalam melatih HMM sebagai model kata. Adapun tujuan penelitian ini ialah menerapkan HMM menggunakan algoritme Baumwelch untuk mengenali sebuah kata. Kata yang digunakan terbatas pada 40 buah kata berbahasa Indonesia yang dibedakan ke dalam 2 macam jumlah suku kata, yaitu : 2 suku kata dan 3 suku kata. Pembicara pada penelitian ini juga dibatasi pada 2 orang pembicara perempuan dan 2 orang pembicara laki-laki yang telah terlatih sebelumnya.
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Judul: Pengaruh Pemberian Jus Tomat dan Penyuluhan Gizi terhadap Gaya Hidup dan Status Antioksidan Likopen Plasma Penderita Kista Payudara
Abstrak: Tomatoes have been reported that have beneficial effects for preventing cancer, its because of the antioxidant properties, called lycopene. Breast cancer is the most common type of cancer in women and breast cysts of type 1 is a praedispose to develop breast cancer. This study was conducted to search the effect of ingestion tomato juice and nutrition promotion to antioxidant status of lycopene plasma concentration and the life style of respondents. The intervention was conducted from June 2009 to April 2010 which covered a period of 2-weeks for wash-out (intake a low antioxidant diet) and a 2-weeks intake a lycopene-rich tomato juice diet (480 ml tomato juice per day). Twenty women were actively participated in the study, age between 19-49 years old composed of 10 women with non cysts (NCG) and 10 women with cysts (CG). Pre-post intervention were determined using HPLC for plasma lycopene concentration and DPPH method for total antioxidant acitivity. A life style of respondents were determined using a structure questionaire. The results of the study showed that there is highly significant difference in term of a mean of plasma lycopene concentration for pre and post intervention (p<0.01), for NCG from 0.53 µmol/L to 1.3 µmol/L and for CG were 0.58 µmol/L to 1.25 µmol/L. However, for total antioxidant acitivity in plasma not significantly change (p>0.05). The study showed that nutrition promotion not sigificantly change their life style, but level of physical activity tend to increased and consumption fast food tend to decreased. However, the study showed that no significance difference in term of size of breast cyst, for the right and left breast (p>0.05).
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