身心障礙者輔具之研製

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姓名

黃超群(Chao-Chun Huang) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

身心障礙者輔具之研製
(The Study of Auxiliary Equipments for the Spinal Cord Injuries and the Blind)

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摘要(中)

摘要
對一般人士來說，透過滑鼠和鍵盤來操作電腦是相當方便的事情，不幸地，對於身心障礙人士卻沒有辦法享受到這種方便的互動。如何改善這個狀況是個刻不容緩的任務。對於人類來說，語音是一種自然的溝通方式，對於沒辦法使用這些控制介面的人士，使用語音操作來控制電腦是個不錯的取代方式。目前，應用於語音辨識上，主要有下列三種方法，(1) 動態時間校正(DTW)演算法，(2) 隱藏Markov模型(HMM)，和(3) 模糊類神經方法(neuro-fuzzy approaches)。當然，這些方法都有個別的優缺點，在本篇論文中，我們提出了一個新的方法，結合了Kohonen的自我組織特徵映射圖網路(SOM)和一個圖樣比對方式，來應用於辨識單詞語音上。我們使用這個新的語音辨識方法來實現了一個聲控滑鼠介面，使得使用者能夠以語音命令來操作滑鼠。
在本論文中我們也發展了一個點字樂譜自動化製作的整合環境。透過此整合環境，使用者可以將所要學習的樂譜，先經掃描器轉至電腦檔案中，然後，藉由辨識程式辨識在被掃描的樂譜上的所有音樂符號，最後再將辨識結果轉換成點字樂譜檔案，並將點字樂譜檔案以語音呈現給使用者。藉由此整合環境，我們可大量減少人工製作的費用以及縮短製作時間，以便為國內視覺障礙人士製作大量的點字樂譜。

摘要(英)

Abstract:
For able-bodies people, access to computers can be taken for granted because conventional computer interfaces (e.g. a keyboard and a mouse) are designed with the able-bodies in mind. Unfortunately, people with physical disabilities cannot enjoy the benefits provided by computers on equal term. Therefore, how to lower or even tear down the barriers between computers and users with disabilities is a very demanding task. Since speech is a natural communication means for human being, the voice-operation feature is the idea control method for the large number of disabled people who cannot use conventional computer interfaces. Currently, there are three different approaches to speech recognition such as (1) dynamic time warping (DTW) algorithm, (2) hidden Markov model (HMM), and (3) neuro-fuzzy approaches. Each has its own merits and disadvantages. In this thesis, a new method that combines Kohonen’s self-organizing feature map and a simple pattern matching method is proposed for isolated word recognition. Based on this new recognition method a voice-controlled mouse is implemented to allow the user to issue voice commands to move the cursor and/or click the buttons.
In this thesis, we also develop an integrated environment for automatically manufacturing Braille music scores. Under this integrated environment, users can first use a scanner to scan music scores into a computer, run the recognition software to recognize musical symbols on scanned music scores, and then transform the recognized results into Braille music scores. By using the proposed integrated environment, we can greatly reduce the labor fees and shorten the time for manufacturing a large amount of Braille music scores for the blind in Taiwan.

關鍵字(中)

★ 聲控電腦
★ 語音辨識
★ 點字樂譜

關鍵字(英)

★ voice control Human-Computer Interface
★ Braille music scores
★ speech recognize

論文目次

目錄
第一章緒論 1
1.1 引言 1
1.2 研究動機 3
1.3 論文架構 5
第二章聲控式電腦人機介面 6
2.1語音處理的方式 6
2.2語音特徵參數的擷取 10
2.2.1 特徵參數的擷取 10
2.3自我組織特徵映射圖網路 13
2.3.1自我組織特徵映射圖演算法 14
2.3.2參數的選擇 18
2.3.3細調自我組織特徵映射圖 21
2.4自我組織特徵映射圖網路訓練方式 23
2.4.1網路初始化 23
2.5語音特徵比對的方式 27
2.6以自我映射組織圖(SOM-based)處理語音辨識與動態時間校準(DTW-based)之比較 29
第三章點字樂譜之製作 31
3.1引言 31
3.2樂譜影像輸入系統 32
3.3光學樂譜辨識系統 33
3.4點字符號資料庫 33
3.5轉譯程式 36
3.6語音輸出 43
3.7結果與討論 43
第四章結論與展望 48
參考文獻 50
圖目錄
圖2.1 語音辨識系統:訓練階段和辨識階段。 9
圖2.2 端點偵測:目的是為了將一段語音的開始或結尾中沒有聲音訊號的部分移除。 11
圖2.3以二維矩陣方式排列的類神經元陣列。 15
圖2.4鄰域函數之型式 (a)正方形的鄰域函數；(b)六邊形的鄰域函數。 19
圖2.5高斯型式之鄰域函數。 20
圖2.6以網格點設定法來初始化特徵映射圖。 27
圖2.7 得勝者情形圖表:相同的語音”上”彼此的得勝者輸出情形。 28
圖2.8 對第一組的第一個語音的相似度結果﹕其中A,B,C與D代表為四組訓練集，而1..9則是表示9種不同的語音單詞，最下面的11這一列是同一組中的最大值。 29
圖2.9聲控電腦操作介面：藉由輸入的語音命令來控制滑鼠移動於螢幕小鍵盤上，並決定所擊發動作(左，右鍵等…)。 30
圖3.1 點字樂譜自動化製作的整合環境所包含的四個子系統。 33
圖3.2 點字符號表示法的差異處：和絃的表示方式不同。 35
圖3.3、點字樂譜資料庫：儲存的資料型態。 36
圖3.4 音符、點字符號與對應之文字符號示意圖。 37
圖3.5透過MidiConverter可將MIDI檔轉換成文字檔。(a) MidiConverter所提供的轉換介面；(b) MIDI檔案的文字檔型態。 42
圖3.6轉譯程式的流程圖。 43
圖3.7播放程式介面：使用方向鍵來控制播放的樂譜。 45
圖3.8 安裝程式執行畫面。 46
圖3.9 ODBC相關設定，資料來源名稱”TtoBdata”。 47
圖3.10 實驗結果： (a)一組旋律、(b)該旋律MIDI檔案的文字檔、(c)經過轉換程式處理後的結果，需要點字字型才能觀看真實的點字符號結果。 49

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指導教授

蘇木春(Mu-Chun Su)

審核日期

2002-7-18

推文