視窗九五上的國語單音節大詞彙辨認系統之製作

Abstract

本論文是在視窗95的作業系統環境下，以聲霸卡作為聲音輸入的設備，不 附加DSP卡輔助計算，建構在配備Pentium-133個人電腦上的國語單音節大 詞彙辨認系統，採用遞迴式類神經網路辨認方法．研究的重點在於適當地 安排系統流程，利用錄音時間同步執行求取參數程序，並採用遞迴式類神 經網路配合有限狀態機，作音節邊界判定，以此控制系統的運作．在前處 理程序中，引入多工處理，使得平均每秒的語音資料，等待到辨認完成所 需的時間，由0.867秒減少到0.721秒，獲得16.7% 的改進．實驗結果是對 一到五字詞的辨認率分別是20.6%, 51.6%, 88.4%, 95.2%, 及100%． The design and implementation of an RNN-based speech recognizer forlarge-vocabulary isolated Mandarin word on a Pentium PC wih SoundBlaster add-on card and Windows95 environment is present in this thesis. It can be functionally divided into two parts: pre- processingand word recognition. In pre-processing, a small RNN is first used todiscriminate input speech from the background silence. Driven by theoutput of th RNN, a finite state machine is then used to determine all word boundaries. State-dependent constraints are then added to eliminate some computations of feature extraction. This can relievethe load of CPU. After entering the state of the end of utternce, word recognition using an RNN base-syllable recognizer and an RNN tone recognizer is then performed to determine the best N candidatesof word. It is noted that the pre-processing is run in real-time.So, an average waiting time of 0.876 seconds for word recognitioncan be achieved. Recognition rates of 20.6%, 51.6%, 88.4%, 95.2% and100% are obtained for one- to five-syllabic words, respectively.