Koolagudi, S.G.Vishwanath, B.K.Akshatha, M.Vishnu Srinivasa Murthy, Y.V.S.2026-02-062017Advances in Intelligent Systems and Computing, 2017, Vol.469, , p. 275-28021945357https://doi.org/10.1007/978-981-10-1678-3_27https://idr.nitk.ac.in/handle/123456789/31999Voice Conversion is a technique in which source speakers voice is morphed to a target speakers voice by learning source–target relationship from a number of utterances from source and the target. There are many applications which may benefit from this sort of technology for example dubbing movies, TV-shows, TTS systems and so on. In this paper, analysis on the performance of ANN-based Voice Conversion system is done using linear predictive coding (LPC) and mel-frequency cepstral coefficients (MFCCs). Experimental results show that Voice Conversion system based on LPC features is better than the ones based on MFCC features. © Springer Science+Business Media Singapore 2017.Linear predictive coding and neural networksMel-frequency cepstral coefficientsMorphingVoice conversion