Show simple item record

dc.contributor.advisorBuono, Agus
dc.contributor.authorHapsari, Aditya Dwi
dc.date.accessioned2013-01-17T02:20:48Z
dc.date.available2013-01-17T02:20:48Z
dc.date.issued2012
dc.identifier.urihttp://repository.ipb.ac.id/handle/123456789/59528
dc.description.abstractVoice recognition is a field study in voice processing. Research on voice signal has several methods of processing, one of them is the Mel Frequency Cepstrum Coefficients (MFCC). The purpose of MFCC is to extract voice features. The goal of this research is to apply MFCC as a feature extraction and the normal distribution as a method for word recognition. The first step of the research is data reprocessing, and then data extraction using MFCC. Afterwards, the normal distribution method is used to process the data. From the result, it can be concluded that the normal distribution method can be used for word recognition.The results obtained from the word recognition using normal distribution and MFCC as feature extraction have the highest accuracy of 100% for the phonemes /g/, /n/, /p/, /v/, /x/, /y/ and the lowest accuracy of 67% for the phonemes /a/ and /ken
dc.subjectBogor Agricultural University (IPB)en
dc.subjectword recognitionen
dc.subjectMFCCen
dc.subjectnormal distributionen
dc.titleModel Fonem dengan Pendekatan Distribusi Normal untuk Pengenalan Kata Menggunakan MFCC sebagai Ekstraksi Cirien


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record