PERANCANGAN SISTEM PENCARIAN LAGU INDONESIA MENGGUNAKAN QUERY BY HUMMING BERBASIS LONG SHORT-TERM MEMORY - Henry Hartono; Viny Christanti Mawardi; Janson Hendryli (Fakultas Teknologi Informasi Universitas Tarumanagara, 2021)
Song identification dan query by humming is an application that is developed using Mel-frequency cepstral coefficients (MFCC) and Long Short-Term Memory (LSTM) algorithm.The application purpose is to detect and recognize humming from the input data. In this application the humming input will be divided into two parts, namely the training audio and test audio. For the training audio, the training audio will be divided into two process stages, namely recognizing humming and searching for the unique features of a humming audio.To recognize the humming feature, the humming will be processed using the MFCC method. After obtaining a part of the MFCC Features, the MFCC features will be saved as a vector model. The feature that has been extracted will be learned by the LSTM method. For the test audio of the stages carried out as in the training audio, after the MFCC Feature is detected, an introduction will be made based on learning that has been done with the LSTM method to obtain output in the form of a song name that is successfully recognized and detected will be labeled by the application.