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dc.contributor.author黃培遠en_US
dc.contributor.authorHuang, Pei-Yuanen_US
dc.contributor.author李其昌en_US
dc.contributor.authorLi, Qi-Changen_US
dc.date.accessioned2014-12-12T02:04:03Z-
dc.date.available2014-12-12T02:04:03Z-
dc.date.issued1985en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#NT744436007en_US
dc.identifier.urihttp://hdl.handle.net/11536/52697-
dc.description.abstract本文提出一個通用的連續數字國語語音辨認系統,系統中對於不同的語者收集認音信 號,經過線性預估編碼,二元樹向量量化後,針對每個單字建成隱藏式馬可夫模型。 在辨認的步驟中,將連續語音信號針對每一個建好的單字馬可夫模型,使用分層建立 和凡特比法則來決定待測連續語音是由那幾個單字組成。 本文並針對向量量化的量化碼個數,以及馬可夫模型的狀態數等變數,對於辨認結準 確率的影響加以討論。zh_TW
dc.language.isozh_TWen_US
dc.subject二位樹zh_TW
dc.subject向量量化zh_TW
dc.subject向量zh_TW
dc.subject量化zh_TW
dc.subject馬可夫模型zh_TW
dc.subject語音zh_TW
dc.subject辨認zh_TW
dc.subject語音辨認zh_TW
dc.subject電信zh_TW
dc.subject電子工程zh_TW
dc.subjectTELECOMMUNICATIONen_US
dc.subjectELECTRONIC-ENGINEERINGen_US
dc.title利用向量量化和隱藏式馬可夫模型以及分層建立方法的非特定語者國語連續數字語音辨認zh_TW
dc.titleSpeaker-independent connected Chinese spoken word recognition based on vector quantization, hidden Markov model and level buildingen_US
dc.typeThesisen_US
dc.contributor.department電信工程研究所zh_TW
Appears in Collections:Thesis