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- A new synthetic aperture radar (SAR) image filter method is proposed based on hidden Markov model (HMM). 在小波域隱Markov模型(HMM)的基礎上提出一種新的合成孔徑雷達(SAR)圖像的濾波方法。
- This paper proposes a novel contour tracking algorithm based on Hidden Markov Model (HMM) and optic flow. 提出了一個(gè)新穎的基于隱馬爾科夫模型與光流的輪廓線(xiàn)跟蹤算法。
- In this thesis, we use both Hidden Markov Model (HMM) and Weight Array Model (WAM) to predict the splice sites. 本文基于隱Markov模型(HMM)和權重陣列模型(WAM)兩種方法來(lái)預測剪接位點(diǎn)。
- This paper presents a Chinese named entity recognition system that integrates the Hidden Markov Model (HMM) and rules which are automatic extracted from the training corpus. 本文實(shí)現的中文命名實(shí)體識別系統采用了隱馬爾可夫模型(Hidden Markov Model,HMM)與自動(dòng)規則提取相結合的方法。
- The substance of this magisterial thesis is the research and improvement of speaker recognition which is based on the VQ (Vector Quantization) and HMM (Hidden Markov Model). 本論文主要內容是基于矢量量化(VQ) 和隱馬爾可夫模型（HMM）的說(shuō)話(huà)人識別算法的研究和改進(jìn)。
- Proposes a hybrid approach for phoneme recognition based on combination of improved counter-propagation (CP) neural network and hidden Markov model (HMM). 提出了一種基于改進(jìn)對偶傳播 (CP) 神經(jīng)網(wǎng)絡(luò )與隱馬爾可夫模型 (HMM) 相結合的混合音素識別方法。
- In order to use duration information in Language IDentification (LID) efficiently, the inhomogeneous Hidden Markov Model (HMM) with general topological structure is proposed, and is used to identify the language between Mandarin and English also. 為了充分利用語(yǔ)音信號中的段長(cháng)信息,該文提出了一種具有一般拓撲結構的非齊次隱含Markov模型(Hidden Markov Model,HMM),并將其應用于中、英文語(yǔ)種辨識(Language IDentification,LID)系統。
- The whole process was divided into two steps.First to use the hidden Markov model for part-of-speech tagging, and then made use of match rules to amend and convert the result of the HMM step. 整個(gè)識別過(guò)程主要分成兩個(gè)步驟，首先使用隱馬爾可夫模型進(jìn)行詞性標注，然后利用具有優(yōu)先級別的匹配規則對第一步的結果進(jìn)行修正和轉換。
- A new approach for hidden Markov model (HMM) training based on an improved maximum mutual information (MMI) criterion was presented and HMM parameter adjustment rules were induced. 摘要提出一種改進(jìn)的最大互信息(MMI)準則函數并把它應用于隱馬爾可夫模型(HMM)的參數估計，重新推導了HMM的迭代公式。
- In this paper a method of continuous speech recognition based on hidden Markov models (HMM) and vector quantization (VQ) is discussed. 本文討論基于隱馬爾可夫模型(HMM)和矢量量化(VQ)的連續語(yǔ)音識別方法。
- The use of hidden Markov models(HMM) for faces is motivated by their partial invariance to variations in scaling and by the structure of faces. 隱馬爾可夫模型(HMM)在人臉識別中的運用是由HMM在圖像定標變化過(guò)程中的局部恒定性和人臉的結構所決定的。
- non-homogeneous hidden Markov model (HMM) 非齊次隱馬爾可夫模型
- This paper presents a hybrid model of Continuous Density Hidden Markov Model (CDHMM) and the Multi-Layer Perceptron (MLP). 本文提出了一種由連續隱馬爾可夫模型（CDHMM）與多層感知器（MLP）構成的混合模型，并將該模型應用于語(yǔ)音孤立詞識別。
- It produces Mongolian translation from the single language material through use of dictionary-based model and Hidden Markov Model. 基于HMM模型的蒙古文生成方法采用詞典驅動(dòng)模型和HMM模型從單語(yǔ)料生成蒙古文譯文。
- Second, we discuss the three base question of Hidden Markov Model, induce two new algorithms, named mend Baum-Welch and mend Viterbi. 其次，本文在研究了隱馬爾可夫模型的基礎上，對其三個(gè)基本問(wèn)題進(jìn)行了比較細致的論證，并引入改進(jìn)Viterbi算法。
- The continuous density hidden Markov model(CDHMM) is adopted, Viterbi and Baum-Welch reestimation algorithms is utilized to train and recognize the speech signals. 采用連續HMM模型，利用Baum-Welth重估、Viterbi算法進(jìn)行訓練和識別，實(shí)現系統軟件設計。
- Then sub-state maximum likelihood and combining transition sub-state maximum likelihood (CTSSML) for parellel sub-state hidden Markov model are also presented. 在此基礎上，提出了兩種用于平行子狀態(tài)隱馬爾可夫模型的識別解碼策略-子狀態(tài)最大似然解碼和聯(lián)合轉移子狀態(tài)最大似然解碼。
- Through the combination of Hidden Markov Model POS tagging and the smoothing algorithm, we obtain a tagging precision of 86%, and a disambiguation of 82%. 在實(shí)現基于隱馬爾可夫模型的詞性標注同時(shí)，結合平滑算法，標注正確率達到86%25，排歧正確率達到82%25；
- Hidden Markov Models are introduced to the area of ship-radiated noise recognition. 將隱馬爾可夫模型引入到艦船噪聲目標識別中。
- By hidden Markov model, it combined with a prior segmentation model which is independent to noise feature as the compensation for the mismatch of acoustic model to enhance the robust performance. 然后,假設音節長(cháng)度序列符合一階馬爾科夫過(guò)程,經(jīng)過(guò)歸一化處理后,求出了切分的先驗概率公式,得到了貝葉斯方法的切分模型。
