Because the ruby annotation may not contain pronunciation information, or if it does, will usually present it using kana, bopomofo, or a form of pinyin, some special treatment is necessary. If ruby information is present, however, and it is known to contain pronunciation information, it may be possible for a speech processor to extract some pronunciation information from that markup. see ).Īlthough ruby annotation can indicate pronunciation, the i18n WG does not see this as a natural fit for general text-to-speech semantics, and recommends against ruby being considered as the format to use for expressing pronunciation information. Without using morphological features, this approach can also achieve a good performance compa-rable with the Stanford POS tagger. In the API, these tags are known as Token.tag. The data is roughly evenly divided across five genres: weblogs, newsgroups, email, reviews, and question-answers. ![]() A words tag in a sentence depends on the words syntactic property in the context it occurs in. ![]() It is the process of automatic annotation of lexical categories (verb, adjective, noun, etc.) to words. However, not all ruby annotations are associated with pronunciation (eg. When tested on Penn Treebank WSJ test set, a state-of-the-art performance of 97.40 tag-ging accuracy is achieved. The part-of-speech tagger assigns each token a fine-grained part-of-speech tag. English Web Treebank is a dataset containing 254,830 word-level tokens and 16,624 sentence-level tokens of webtext in 1174 files annotated for sentence- and word-level tokenization, part-of-speech, and syntactic structure. Part-of-speech tagging is usually used at the preprocessing step in many natural language processing applications. This seems like a natural fit for text-to-speech.Īs mentioned in the text, ruby markup is primarily a way of visually aligning annotations with base text, and the standard usage is for both annotation and base to be presented to the user and to be present in element content.
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