篇名 |
自動化校長即席演講評分系統建置之初探
|
---|---|
並列篇名 | A Prelimary Study for Automatic Scoring System in Oral Presentation |
作者 | 謝名娟、蔡明學、李祈均 |
中文摘要 | 為了因應大型評量的需要,自動化的口語評量系統為目前評量發展的新趨勢。近年來,自動化評分系統已逐漸應用於教育測驗、課程教學、心理計量等領域,本研究擬透過行為特徵處理的方式(behavioral signal processing),來建置一套結合音訊、視訊之自動化口語評分系統。樣本為儲訓校長,演說內容為教學、校務等相關議題。本研究提出多模態計算架構,結合培訓計畫的音訊與視訊資料,並透過詞袋模型(bag of words)與費雪矢量編碼(Fisher-vector encoding),以建置自動即席演講評分系統。研究顯示,只要蒐集到的樣本在口語表現上的變異性夠大,即能有效促進機器學習的效果。此外,由本研究的實驗可看出,機器和真人的評分,甚至會高於真人評分者彼此間的相關性。然而,未來在增進系統的辨識率方面,可透過加入文本資料、處理音視訊錄製過程中的雜訊、蒐集更多演講樣本、評分者的評分等,來提高自動化系統的準確率。 |
英文摘要 | Automatic scoring system is the current trend for large scale assessment. Automatic scoring system has became a popular research tool in the field of educational assessment, curriculum teaching and psychological measurement. In this work, we employ behavioral signal processing (BSP)-based methodology to develop a computational framework that can automate the scoring process of pre-service school principals' oral presentations given at the yearly training program. Using the audio-video feature extraction approach with session-level representation techniques based on bag-ofword and Fisher-vector encoding, we can then characterize each pre-service school principal's multimodal behavior during an impromptu speech examination for automatic scoring. For the future study, we will include lexical content and annotation; collect more samples and raters which could potentiallyimprove the accuracy of this system. |
起訖頁 | 125-149 |
關鍵詞 | 口語評量、自動化評分系統、機器學習、automatic scoring system、machine learning、oral evaluation |
刊名 | 測驗學刊 |
期數 | 201806 (65:2期) |
出版單位 | 心理出版社 |
該期刊 下一篇
| Yes/No Angoff標準設定結果之效度檢核:應用群聚分析分類法 |