如何为TTS选择一个好的声音

Sunhee Kim
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摘要

尽管说话人自然语音的感知质量不一定保证合成语音的质量,但在进入合成句子的评价阶段之前,需要根据说话人的自然语音选择一定数量的候选人。本文介绍了一种基于对说话人自然声音的感知评价和声学测量的英语和日语单元选择合成系统中男性说话人的选择过程。对每种语言的8位专业语音人才进行了感性评价。总共招募了20名以两种语言为母语的听众,每位听众被要求用5个等级的分数对8个分析因素进行评分,并选出3名最好的演讲者。声学测量侧重于通过从长期平均频谱(LTAS)中提取两个度量来衡量语音质量,即所谓的扬声器峰峰(SPF),它对应于3khz和4khz之间的峰值强度,以及α比(AR),它是0和1khz之间以及1和4khz之间的较低电平差。感知评价结果显示总分与两种语言偏好之间的相关性非常强,英语为0.9183,日语为0.8589。在SPF和AR方面,感知评价与声学测量之间的相关性适中,英语为0.473和-0.494,日语为0.288和-0.263。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How to select a good voice for TTS
Even though the perceived quality of a speaker’s natural voice does not necessarily guarantee the quality of synthesized speech, it is required to select a certain number of candidates based on their natural voice before moving to the evaluation stage of synthesized sentences. This paper describes a male speaker selection procedure for unit selection synthesis systems in English and Japanese based on perceptive evaluation and acoustic measurements of the speakers’ natural voice. A perceptive evaluation is performed on eight professional voice talents of each language. A total of twenty native-speaker listeners are recruited in both languages and each listener is asked to rate on eight analytical factors by using a five-scale score and rank three best speakers. Acoustic measurement focuses on the voice quality by extracting two measures from Long Term Average Spectrum (LTAS), the so-called Speakers Formant (SPF), which corresponds to the peak intensity between 3 kHz and 4 kHz, and the Alpha ratio (AR), which is the lower level difference between 0 and 1 kHz and 1 and 4 kHz ranges. The perceptive evaluation results show a very strong correlation between the total score and the preference in both languages, 0.9183 in English and 0.8589 in Japanese. The correlations between the perceptive evaluation and acoustic measurements are moderate with respect to SPF and AR, 0.473 and -0.494 in English, and 0.288 and -0.263 in Japanese.
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