To determine the possibility of predicting viewer’s internal states using the hidden Markov model, several features of eye movements were introduced to the model. Performance was measured using the data from a set of eye movement features recorded during recall tests which consisted of observations of three levels of task difficulty. The features were the temporal appearances of fixations and s...

This paper describes the use of phonological knowledge to enhance current audio word spotting technology based on Hidden Markov Model. It reports on the result of an word-spotting experiment done on an audio data recorded from a live conference. The result of the experiment demonstrates the positive contribution of phonological knowledge towards audio word-spotting.

Head nods and head shakes are non-verbal gestures used often to communicate intent, emotion and to perform conversational functions. We describe a vision-based system that detects head nods and head shakes in real time and can act as a useful and basic interface to a machine. We use an infrared sensitive camera equipped with infrared LEDs to track pupils. The directions of head movements, deter...

(CAAR) is a consortium of researchers from six universities working in partnership with Department of Defense laboratories and industry. CAAR is funded by the Office of Naval Research through a 1997 Department of Research Initiative. Abstract Almost all prior work on modelling the dependance of acoustic emissions on tool wear have concentrated on the effect of wear-level on the sound. We give j...

陳江村 羅瑞麟 張智星 國立清華大學 資訊工程系 新竹市光復路二段 101 號 E-mail : {jtchen,roro,jang}@wayne.cs.nthu.edu.tw TEL: (03)5715131-3582 摘要: 在此報告中,我們實作了一個結合隱藏式馬可夫模型(Hidden Markov Model, HMM) 為基礎的 HTK(HMM Toolkit)和網頁資料檢索技術的線上新聞語音資料檢索系 統。一般的網頁資料檢索(如 google)須使用者輸入相關文字,才得以文字比對 方式進行檢索。在此我們則嘗試加入語音辨識的技術讓使用者更易進行檢索。本 系統分成新聞前處理及語音查詢兩階段。在辨識內容固定,高準確度的辨識結果 下,本系統特別適用於手機、PDA、嵌入式系統等小型、不易以手操作輸入的裝 置。本系統亦經清大盲友會的盲人朋友試用,反應十分良好。 關鍵詞:語音辨識、資料檢...

In this paper we describe an approach to resolve strategic games in which players can assume different types along the game. Our goal is to infer which type the opponent is adopting at each moment so that we can increase the player’s odds. To achieve that we use Markov games combined with hidden Markov model. We discuss a hypothetical example of a tennis game whose solution can be applied to an...

In this paper we present CELI's participation in Evalita 2011 FLaIT task. Based on Markov model reasoning, our system obtained the highest precision in comparison to the other participants.