Sasak speech-language is can't operate in application such as google speech, Alexa assistance, and so on. It makes society need a new development technology who can solve the problem for sasak language. West Nusa Tenggara Province has more than thousand ancient manuscript writen in lontar leaves and papers, that the manuscript spread in Lombok Island and Sumbawa Island. Speech recognition technique for local language is important topic in computer science research, that it can save the culture from the island. This research should be explained how speech processing method working for conversion analog speech signal in Sasak language into Latin text. This study uses the Mel-Frequency Cepstral Coefficient (MFCC) method as a feature extraction method and Convolutional Neural Network (CNN) as a voice classification method into text, and the Rule Base method with UTF-16 which is used to provide rules on Latin letters that will be converted into text. Sasak characters. The algorithm developed is expected to be able to change 50 sound classes into Sasak letters with good accuracy results or above 88%, in changing the voice of the Sasak language into Sasak script by 90.00%.