THE CMU ENTRY TO BLIZZARD MACHINE LEARNING CHALLENGE

被引：0

作者：

Baljekar, Pallavi ^{[1
]}

Rallabandi, Sai Krishna ^{[1
]}

Black, Alan W. ^{[1
]}

机构：

[1] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA

来源：

2017 IEEE AUTOMATIC SPEECH RECOGNITION AND UNDERSTANDING WORKSHOP (ASRU) | 2017年

关键词：

Blizzard challenge; speech synthesis; parametric speech synthesis; audiobook synthesis; recurrent neural networks;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The paper describes Carnegie Mellon University's (CMU) entry to the ES-1 sub-task of the Blizzard Machine Learning Speech Synthesis Challenge 2017. The submitted system is a parametric model trained to predict vocoder parameters given linguistic features. The task in this year's challenge was to synthesize speech from children's audiobooks. Linguistic and acoustic features were provided by the organizers and the task was to find the best performing model. The paper explores various RNN architectures that were investigated and describes the final model that was submitted.

引用

页码：644 / 649

页数：6

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