1) Continuous Densities Hidden Markov Model
连续密度HMM
1.
In the systum, syllables disregarding tones are the recognition units, Continuous Densities Hidden Markov Models (CDHMM) and syllable duration probability are incorporated in.
我们用LPC倒谱,△倒谱,归一化能量作特征,以汉语无调音节为识别基元,采用连续密度HMM,引入音长概率,对多人的汉语连续语句进行识别,获得初步结果。
2) the continuous Gaussian mixture HMM
连续高斯混合密度HMM
1.
By dividing consonant and vowel of Chinese syllable,we establish a speech distinction system of Chinese pronouncing accuracy using the continuous Gaussian mixture HMM.
细化声韵母,对反映普通话发音准确度的声韵过渡段建立连续高斯混合密度HMM的普通话发音标准度评价系统。
4) continuously varying density
连续变密度
5) continuous density gradient
连续密度梯度
6) Continuous Parameter HMM
连续参数HMM初始化
补充资料：非密度制约因素(见密度制约因素)
非密度制约因素(见密度制约因素)
l焦非密度制约因素见生态因素、密度制约后
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条