نتایج جستجو برای: hidden markov model

تعداد نتایج: 2168524  

Journal: :Expert Syst. Appl. 2003
Wenzhao Tan Gang Rong

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...

2002
Sudhir Varma John S. Baras

(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...

2003
Jiang-Chun Chen Jui-Lin Lo Jyh-Shing Roger Jang

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...

2013
Mario R. F. Benevides Isaque Lima Rafael Nader Pedro Rougemont

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...

2011
Luca Dini Milen Kouylekov Marcella Testa Marco Trevisan

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.

2002
Peter J. Bickel Tobias Rydén

We consider the log-likelihood function of hidden Markov models, its derivatives and expectations of these (such as different information functions). We give explicit expressions for these functions and bound them as the size of the chain increases. We apply our bounds to obtain partial second order asymptotics and some qualitative properties of a special model as well as to extend some results...

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