Intonation in text‐to‐speech synthesis: Evaluation of algorithms
Intonation in text‐to‐speech synthesis: Evaluation of algorithms
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文本到语音合成中的语调：算法评估
DOI：
10.1121/1.391739
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发表时间：
1985
期刊：
影响因子：
--
通讯作者：
Matthew Lennig
中科院分区：
文献类型：
--
作者：
G. Akers;Matthew Lennig
两种算法，称为示意性和自然主义，在英语文本到语音系统中生成语调轮廓进行了比较，从总共21个主题引发的偏好判断。这两种算法的主要问题，但特别是对于示意性算法，与重音分配和确定的语调短语，而不是与语音实现的口音，通过操纵F0。由于分析器错误，在三个实验中使用的句子中有30%的短语边界被错误地识别。此外，自然主义算法使用语法词性等级，将名词排在动词之前。因此，将动词错误地分类为名词（主要的分类错误）会导致意外的重音。结果表明，重音分配和短语确定是需要改进的主要领域，以进一步提高合成语音语调的自然度。
Two algorithms, termed schematic and naturalistic, for generating intonation contours in an English text‐to‐speech system are compared by eliciting preference judgments from a total of 21 subjects. The major problem for both algorithms, but especially for the schematic algorithm, has to do with accent assignment and with the determination of the intonation phrase rather than with the phonetic realization of accent through manipulation of F0. Due to parser errors, phrase boundaries are incorrectly identified in 30% of the sentences used in the three experiments. Moreover, the naturalistic algorithm uses a grammatical part‐of‐speech hierarchy which ranks nouns higher than verbs. Therefore, incorrect classification of verbs as nouns (the major classification error) results in an unintended accent. The results indicate that accent assignment and phrase determination are the primary areas requiring improvement in order to further increase the naturalness of synthetic speech intonation.