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Recent advances in speech synthesis suggest that limitations such as the lossy nature of the amplitude spectrum with minimum phase approximation and the over-smoothing effect in acoustic modeling can be overcome by using advanced machine learning approaches. In this paper, we build a framework in which we can fairly compare new vocoding and acoustic modeling techniques with conventional approaches by means of a large scale crowdsourced evaluation. Results on acoustic models showed thatdoi:10.1109/icassp.2018.8461452 dblp:conf/icassp/WangLTJY18 fatcat:v7utkglqnzehzmrlnngqwsgnoa