Title: 不特定語者國語連續音節辨認
Speaker Independent Continuous Mandarin Syllable Recognition
Authors: 吳瑞彬
Wu, Rui-Bin
陳信宏
Sin-Horng Chen
電信工程研究所
Keywords: 隱藏式馬可夫模型;國語連續音辨認;聲調辨認;大字彙辨認;基頻軌跡;一步驟式辨認器;Hidden Markov Model;Continuous Mandarin Speech Recognition;Tone Recognition;Large Vocabulary Recognition;Pitch Contour;One-stage Recognizer
Issue Date: 1995
Abstract: 論文中探討不特定語者國語連續音節之辨認,所建立的 1300 音節
辨認器,係由一個 以聲韻母模型為基礎的 411 音節隱藏式馬可夫模型
(Hidden Markov Model, HMM)辨認 器以及一個左相關的 HMM 聲調辨認
器結合而成。 為解決基音節與聲調結合時的同步問題 ,我們將每一個
音節視為由 100 類右相關聲母模型、39 類前後文不相關韻母模型以及 2
9 類右相關聲調模型所組合而成,在辨認時,先將 100 類聲母模型、39
類韻母模型以及 29 類聲調模型分別計算狀態觀測機率後,再經由查表
重組合成 1300 音節的模型,用修 正的一階動態規劃演算法進行辨認。
經電話語音測試,使用 159 人的語料訓練及 36 人 的語料測試,獲得
1300 音節的辨認率為 36.40 %, 而 411 音節的辨認率則 47.14 %。
In this thesis, a new method of continuous Mandarin
syllable recognition is studied. The 1431-syllable
recognizer is composed of an initial-final based 411-base-
syllable recognizer and a tone recognizer. It uses 100
right-final-dependent initial HMM models, 39 context-
independent final HMM models and 29 right-tone-dependent
tone HMM models. To cope with the synchronization problem
of combining base-syllable and tone recognizers, in the
recognition process, the observation probabilities of
100-initia l models, 39-final models and 29-tone models are
separately calculated first. The scores for 1431 syllables are
then calculated by a table lookup process. Last, the
recognition process is finished by performing a modified one-
stage dynamic programming. Performance of the method was
examined by simulation using a telephone speech database of
159 training speakers and 36 testing speakers. Accuracy
rates of 36.40 % and 47.14 % were obtained for
recognition of 1431 and 411 syllables, respectively.
URI: http://140.113.39.130/cdrfb3/record/nctu/#NT840435025
http://hdl.handle.net/11536/60776
Appears in Collections:Thesis