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Wiktionary as a Source for Automatic Pronunciation Extraction

机译:维基词典作为自动语音提取的来源

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In this paper, we analyze whether dictionaries from the World Wide Web which contain phonetic notations, may support the rapid creation of pronunciation dictionaries within the speech recognition and speech synthesis system building process. As a representative dictionary, we selected Wiktionary [1] since it is at hand in multiple languages and, in addition to the definitions of the words, many phonetic notations in terms of the International Phonetic Alphabet (IPA) are available. Given word lists in four languages English, French, German, and Spanish, we calculated the percentage of words with phonetic notations in Wiktionary. Furthermore, two quality checks were performed: First, we compared pronunciations from Wiktionary to pronunciations from dictionaries based on the GlobalPhone project, which had been created in a rule-based fashion and were manually cross-checked [2]. Second, we analyzed the impact of Wiktionary pronunciations on automatic speech recognition (ASR) systems. French Wiktionary achieved the best pronunciation coverage, containing 92.58% phonetic notations for the French GlobalPhone word list as well as 76.12% and 30.16% for country and international city names. In our ASR systems evaluation, the Spanish system gained the most improvement from Wiktionary pronunciations with 7.22% relative word error rate reduction.
机译:在本文中,我们分析了包含语音符号的来自万维网的词典是否可以支持在语音识别和语音合成系统构建过程中快速创建发音词典。作为代表性词典,我们选择了Wiktionary [1],因为它具有多种语言,并且除了单词的定义以外,还可以使用国际语音字母(IPA)的许多语音符号。给定英语,法语,德语和西班牙语四种语言的单词列表,我们计算了维基词典中带有注音符号的单词所占的百分比。此外,还进行了两次质量检查:首先,我们将Wiktionary的发音与基于GlobalPhone项目的字典的发音进行了比较,后者是基于规则创建的,并经过了手动交叉检查[2]。其次,我们分析了维基词典发音对自动语音识别(ASR)系统的影响。法语维基词典获得了最佳的语音覆盖率,其中法语GlobalPhone单词列表包含92.58%的语音符号,而国家和国际城市名称包含76.12%和30.16%的语音符号。在我们的ASR系统评估中,西班牙语系统在Wiktionary语音方面获得了最大的改进,相对词错误率降低了7.22%。

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