Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/45350
Title: Spoken language translation
Authors: Chen, Min.
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Issue Date: 2011
Abstract: With technological advancement in info-communication, speech recognition has become a major area of research. The aim of this project is to develop a Speech Recognition System which then be used for Spoken Language Translation. This system receives speech inputs from users, analyzes the speech inputs by extracting the features of the speech, searches and matches the input speech features with the pre-recorded and stored speeches features in the trained database, and returns the translated matching result to the users through Matlab Graphic User Interface.Acoustic models are needed for this Speech Recognition System. The acoustic model is a collection of features which are extracted from the pre-recorded speeches. To extract features from the speech signals the Mel-Frequency Cepstral Coefficients (MFCC) algorithm was applied. And statistical based matching approach model Hidden Markov Models (HMM) is used to match the desired output.
URI: http://hdl.handle.net/10356/45350
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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