Method for estimating language model weight and system for the same
    1.
    发明授权
    Method for estimating language model weight and system for the same 失效
    用于估计语言模型权重和系统的方法

    公开(公告)号:US08666739B2

    公开(公告)日:2014-03-04

    申请号:US13324414

    申请日:2011-12-13

    IPC分类号: G10L15/00

    CPC分类号: G10L15/065 G10L15/187

    摘要: Method of the present invention may include receiving speech feature vector converted from speech signal, performing first search by applying first language model to the received speech feature vector, and outputting word lattice and first acoustic score of the word lattice as continuous speech recognition result, outputting second acoustic score as phoneme recognition result by applying an acoustic model to the speech feature vector, comparing the first acoustic score of the continuous speech recognition result with the second acoustic score of the phoneme recognition result, outputting first language model weight when the first coustic score of the continuous speech recognition result is better than the second acoustic score of the phoneme recognition result and performing a second search by applying a second language model weight, which is the same as the output first language model, to the word lattice.

    摘要翻译: 本发明的方法可以包括接收从语音信号转换的语音特征向量,通过对接收的语音特征向量应用第一语言模型来执行第一搜索,并且将字格的字格和第一声分数输出为连续语音识别结果,输出 第二声学分数作为音素识别结果,通过对语音特征向量应用声学模型,将连续语音识别结果的第一声学分数与音素识别结果的第二声学分数进行比较,当第一个coustic分数输出第一语言模型权重时, 连续语音识别结果比音素识别结果的第二声分数更好,并且通过将与输出第一语言模型相同的第二语言模型权重应用于单词格来进行第二搜索。

    METHOD FOR ESTIMATING LANGUAGE MODEL WEIGHT AND SYSTEM FOR THE SAME
    2.
    发明申请
    METHOD FOR ESTIMATING LANGUAGE MODEL WEIGHT AND SYSTEM FOR THE SAME 失效
    用于估算语言模型重量和系统的方法

    公开(公告)号:US20120150539A1

    公开(公告)日:2012-06-14

    申请号:US13324414

    申请日:2011-12-13

    IPC分类号: G10L15/00

    CPC分类号: G10L15/065 G10L15/187

    摘要: Method of the present invention may include receiving speech feature vector converted from speech signal, performing first search by applying first language model to the received speech feature vector, and outputting word lattice and first acoustic score of the word lattice as continuous speech recognition result, outputting second acoustic score as phoneme recognition result by applying an acoustic model to the speech feature vector, comparing the first acoustic score of the continuous speech recognition result with the second acoustic score of the phoneme recognition result, outputting first language model weight when the first coustic score of the continuous speech recognition result is better than the second acoustic score of the phoneme recognition result and performing a second search by applying a second language model weight, which is the same as the output first language model, to the word lattice.

    摘要翻译: 本发明的方法可以包括接收从语音信号转换的语音特征向量,通过对接收的语音特征向量应用第一语言模型来执行第一搜索,并且将字格的字格和第一声分数输出为连续语音识别结果,输出 第二声学分数作为音素识别结果,通过对语音特征向量应用声学模型,将连续语音识别结果的第一声学分数与音素识别结果的第二声学分数进行比较,当第一个coustic分数输出第一语言模型权重时, 连续语音识别结果比音素识别结果的第二声分数更好,并且通过将与输出第一语言模型相同的第二语言模型权重应用于单词格来进行第二搜索。

    Viterbi decoder and speech recognition method using same using non-linear filter for observation probabilities
    6.
    发明授权
    Viterbi decoder and speech recognition method using same using non-linear filter for observation probabilities 有权
    维特比解码器和语音识别方法使用非线性滤波器进行观察概率

    公开(公告)号:US08332222B2

    公开(公告)日:2012-12-11

    申请号:US12506719

    申请日:2009-07-21

    IPC分类号: G10L15/00

    CPC分类号: G10L15/08 G10L15/142

    摘要: A Viterbi decoder includes: an observation vector sequence generator for generating an observation vector sequence by converting an input speech to a sequence of observation vectors; a local optimal state calculator for obtaining a partial state sequence having a maximum similarity up to a current observation vector as an optimal state; an observation probability calculator for obtaining, as a current observation probability, a probability for observing the current observation vector in the optimal state; a buffer for storing therein a specific number of previous observation probabilities; a non-linear filter for calculating a filtered probability by using the previous observation probabilities stored in the buffer and the current observation probability; and a maximum likelihood calculator for calculating a partial maximum likelihood by using the filtered probability. The filtered probability may be a maximum value, a mean value or a median value of the previous observation probabilities and the current observation probability.

    摘要翻译: 维特比解码器包括:观测向量序列生成器,用于通过将输入语音转换为观察向量序列来生成观察向量序列; 局部最优状态计算器,用于获得具有与当前观察向量最大相似度的部分状态序列作为最佳状态; 观测概率计算器,用于获得在最佳状态下观察当前观测矢量的概率作为当前观测概率; 用于在其中存储特定数量的先前观察概率的缓冲器; 用于通过使用存储在缓冲器中的先前观察概率和当前观察概率来计算滤波概率的非线性滤波器; 以及最大似然计算器,用于通过使用滤波的概率来计算部分最大似然。 滤波概率可以是先前观测概率和当前观测概率的最大值,平均值或中值。

    SPEECH RECOGNITION SYSTEM AND METHOD
    9.
    发明申请
    SPEECH RECOGNITION SYSTEM AND METHOD 有权
    语音识别系统和方法

    公开(公告)号:US20100161326A1

    公开(公告)日:2010-06-24

    申请号:US12506705

    申请日:2009-07-21

    IPC分类号: G10L15/20

    摘要: A speech recognition system includes: a speed level classifier for measuring a moving speed of a moving object by using a noise signal at an initial time of speech recognition to determine a speed level of the moving object; a first speech enhancement unit for enhancing sound quality of an input speech signal of the speech recognition by using a Wiener filter, if the speed level of the moving object is equal to or lower than a specific level; and a second speech enhancement unit enhancing the sound quality of the input speech signal by using a Gaussian mixture model, if the speed level of the moving object is higher than the specific level. The system further includes an end point detection unit for detecting start and end points, an elimination unit for eliminating sudden noise components based on a sudden noise Gaussian mixture model.

    摘要翻译: 语音识别系统包括:速度级分类器,用于通过在语音识别的初始时间使用噪声信号来测量移动物体的移动速度,以确定移动物体的速度水平; 第一语音增强单元,如果移动对象的速度水平等于或低于特定水平,则通过使用维纳滤波器来增强语音识别的输入语音信号的声音质量; 以及第二语音增强单元,如果移动对象的速度水平高于特定水平,则通过使用高斯混合模型来增强输入语音信号的声音质量。 该系统还包括用于检测起点和终点的终点检测单元,用于基于突发噪声高斯混合模型消除突发噪声分量的消除单元。