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The HTS-2008 System: Yet Another Evaluation of the Speaker-Adaptive HMM-based Speech Synthesis System in The 2008 Blizzard Challenge

机译:HTS-2008系统:在2008年暴雪挑战赛中对基于说话者自适应HMM的语音合成系统的又一次评估

摘要

For the 2008 Blizzard Challenge, we used the same speaker-adaptive approach to HMM-based speech synthesis that was used in the HTS entry to the 2007 challenge, but an improved system was built in which the multi-accented English average voice model was trained on 41 hours of speech data with high-order mel-cepstral analysis using an efficient forward-backward algorithm for the HSMM. The listener evaluation scores for the synthetic speech generated from this system was much better than in 2007: the system had the equal best naturalness on the small English data set and the equal best intelligibility on both small and large data sets for English, and had the equal best naturalness on the Mandarin data. In fact, the English system was found to be as intelligible as human speech.
机译:在2008年暴雪挑战赛中,我们使用了与说话人自适应的基于HMM的语音合成方法,该方法与2007年挑战赛的HTS参赛时所采用的方法相同,但是我们构建了一种改进的系统,在该系统中训练了多口音的英语平均语音模型使用高效的HSMM前向后算法,对41个小时的语音数据进行高阶mel-倒谱分析。该系统生成的合成语音的听众评估得分比2007年要好得多:该系统在小型英语数据集上具有同等的最佳自然度,在大型和小型英语数据集上具有同等的最佳清晰度,并且具有在普通话数据上具有最佳自然度。实际上,发现英语系统与人类语音一样可理解。

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