頁籤選單縮合
題 名 | Data Driven Approaches to Phonetic Transcription with Integration of Automatic Speech Recognition and Grapheme-to-Phoneme for Spoken Buddhist Sutra |
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作 者 | Liang, Min-siong; Lyu, Ren-yuan; Chiang, Yuang-chin; | 書刊名 | International Journal of Computational Linguistics & Chinese Language Processing |
卷 期 | 13:2 2008.06[民97.06] |
頁 次 | 頁233-253 |
分類號 | 312.13 |
關鍵詞 | Automatic phonetic transcription; Phone recognition; Grapheme-to-phoneme; G2P; Pronunciation variation; Chinese text; Taiwanese; Min-Nan; Dialect; Buddhist Sutra; |
語 文 | 英文(English) |
英文摘要 | We propose a new approach for performing phonetic transcription of text that utilizes automatic speech recognition (ASR) to help traditional grapheme-to-phoneme (G2P) techniques. This approach was applied to transcribe Chinese text into Taiwanese phonetic symbols. By augmenting the text with speech and using automatic speech recognition with a sausage searching net constructed from multiple pronunciations of text, we are able to reduce the error rate of phonetic transcription. Using a pronunciation lexicon with multiple pronunciations for each item, a transcription error rate of 12.74% was achieved. Further improvement can be achieved by adapting the pronunciation lexicon with pronunciation variation (PV) rules derived manually from corrected transcription in a speech corpus. The PV rules can be categorized into two kinds: knowledge-based and data-driven rules. By incorporating the PV rules, an error rate of 10.56% could be achieved. Although this technique was developed for Taiwanese speech, it could easily be adapted to other Chinese spoken languages or dialects. |
本系統中英文摘要資訊取自各篇刊載內容。