论文标题
简单有效的无监督语音综合
Simple and Effective Unsupervised Speech Synthesis
论文作者
论文摘要
我们介绍了基于简单但有效的配方的第一个无监督语音合成系统。该框架利用了无监督的语音识别以及现有基于神经的语音综合的最新工作。我们的方法仅使用未标记的语音音频和未标记的文本以及词典，可以使语音合成无需人贴标记的语料库。实验表明，根据人类评估衡量的自然性和可理解性，无监督的系统可以合成类似于受监督对应物的语音。
We introduce the first unsupervised speech synthesis system based on a simple, yet effective recipe. The framework leverages recent work in unsupervised speech recognition as well as existing neural-based speech synthesis. Using only unlabeled speech audio and unlabeled text as well as a lexicon, our method enables speech synthesis without the need for a human-labeled corpus. Experiments demonstrate the unsupervised system can synthesize speech similar to a supervised counterpart in terms of naturalness and intelligibility measured by human evaluation.
