公开(公告)号：US08666739B2

公开(公告)日：2014-03-04

申请号：US13324414

申请日：2011-12-13

申请人： Hyung Bae Jeon ,  Yun Keun Lee ,  Eui Sok Chung ,  Jong Jin Kim ,  Hoon Chung ,  Jeon Gue Park ,  Ho Young Jung ,  Byung Ok Kang ,  Ki Young Park ,  Sung Joo Lee ,  Jeom Ja Kang ,  Hwa Jeon Song

发明人： Hyung Bae Jeon ,  Yun Keun Lee ,  Eui Sok Chung ,  Jong Jin Kim ,  Hoon Chung ,  Jeon Gue Park ,  Ho Young Jung ,  Byung Ok Kang ,  Ki Young Park ,  Sung Joo Lee ,  Jeom Ja Kang ,  Hwa Jeon Song

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。

公开(公告)号：US20120150539A1

公开(公告)日：2012-06-14

申请号：US13324414

申请日：2011-12-13

申请人： Hyung Bae Jeon ,  Yun Keun Lee ,  Eui Sok Chung ,  Jong Jin Kim ,  Hoon Chung ,  Jeon Gue Park ,  Ho Young Jung ,  Byung Ok Kang ,  Ki Young Park ,  Sung Joo Lee ,  Jeom Ja Kang ,  Hwa Jeon Song

发明人： Hyung Bae Jeon ,  Yun Keun Lee ,  Eui Sok Chung ,  Jong Jin Kim ,  Hoon Chung ,  Jeon Gue Park ,  Ho Young Jung ,  Byung Ok Kang ,  Ki Young Park ,  Sung Joo Lee ,  Jeom Ja Kang ,  Hwa Jeon Song

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。

公开(公告)号：US08219396B2

公开(公告)日：2012-07-10

申请号：US12336208

申请日：2008-12-16

申请人： Hoon-Young Cho ,  Yunkeun Lee ,  Ho-Young Jung ,  Byung Ok Kang ,  Jeom Ja Kang ,  Kap Kee Kim ,  Sung Joo Lee ,  Hoon Chung ,  Jeon Gue Park ,  Hyung-Bae Jeon

发明人： Hoon-Young Cho ,  Yunkeun Lee ,  Ho-Young Jung ,  Byung Ok Kang ,  Jeom Ja Kang ,  Kap Kee Kim ,  Sung Joo Lee ,  Hoon Chung ,  Jeon Gue Park ,  Hyung-Bae Jeon

IPC分类号： G10L15/00

CPC分类号： G10L15/01

摘要： An apparatus for evaluating the performance of speech recognition includes a speech database for storing N-number of test speech signals for evaluation. A speech recognizer is located in an actual environment and executes the speech recognition of the test speech signals reproduced using a loud speaker from the speech database in the actual environment to produce speech recognition results. A performance evaluation module evaluates the performance of the speech recognition by comparing correct recognition results answers with the speech recognition results.

摘要翻译： 用于评估语音识别性能的装置包括用于存储用于评估的N个测试语音信号的语音数据库。 语音识别器位于实际环境中，并且在实际环境中执行使用来自语音数据库的扬声器再现的测试语音信号的语音识别，以产生语音识别结果。 性能评估模块通过将正确的识别结果答案与语音识别结果进行比较来评估语音识别的性能。

公开(公告)号：US20090157399A1

公开(公告)日：2009-06-18

申请号：US12336208

申请日：2008-12-16

申请人： Hoon-Young CHO ,  Yunkeun Lee ,  Ho-Young Jung ,  Byung Ok Kang ,  Jeom Ja Kang ,  Kap Kee Kim ,  Sung Joo Lee ,  Hoon Chung ,  Jeon Gue Park ,  Hyung-Bae Jeon

发明人： Hoon-Young CHO ,  Yunkeun Lee ,  Ho-Young Jung ,  Byung Ok Kang ,  Jeom Ja Kang ,  Kap Kee Kim ,  Sung Joo Lee ,  Hoon Chung ,  Jeon Gue Park ,  Hyung-Bae Jeon

IPC分类号： G10L15/00

CPC分类号： G10L15/01

摘要： An apparatus for evaluating the performance of speech recognition includes a speech database for storing N-number of test speech signals for evaluation. A speech recognizer is located in an actual environment and executes the speech recognition of the test speech signals reproduced using a loud speaker from the speech database in the actual environment to produce speech recognition results. A performance evaluation module evaluates the performance of the speech recognition by comparing correct recognition results answers with the speech recognition results.

摘要翻译： 用于评估语音识别性能的装置包括用于存储用于评估的N个测试语音信号的语音数据库。 语音识别器位于实际环境中，并且在实际环境中执行使用来自语音数据库的扬声器再现的测试语音信号的语音识别，以产生语音识别结果。 性能评估模块通过将正确的识别结果答案与语音识别结果进行比较来评估语音识别的性能。

公开(公告)号：US08249867B2

公开(公告)日：2012-08-21

申请号：US12242819

申请日：2008-09-30

申请人： Hoon Young Cho ,  Yun Keun Lee ,  Jeom Ja Kang ,  Byung Ok Kang ,  Kap Kee Kim ,  Sung Joo Lee ,  Ho Young Jung ,  Hoon Chung ,  Jeon Gue Park ,  Hyung Bae Jeon

发明人： Hoon Young Cho ,  Yun Keun Lee ,  Jeom Ja Kang ,  Byung Ok Kang ,  Kap Kee Kim ,  Sung Joo Lee ,  Ho Young Jung ,  Hoon Chung ,  Jeon Gue Park ,  Hyung Bae Jeon

IPC分类号： G10L15/20

CPC分类号： G10L15/20 ,  G10L21/0272 ,  G10L2021/02166

摘要： A microphone-array-based speech recognition system using a blind source separation (BBS) and a target speech extraction method in the system are provided. The speech recognition system performs an independent component analysis (ICA) to separate mixed signals input through a plurality of microphone into sound-source signals, extracts one target speech spoken for speech recognition from the separated sound-source signals by using a Gaussian mixture model (GMM) or a hidden Markov Model (HMM), and automatically recognizes a desired speech from the extracted target speech. Accordingly, it is possible to obtain a high speech recognition rate even in a noise environment.

摘要翻译： 提供了一种基于麦克风阵列的语音识别系统，该系统使用盲源分离（BBS）和目标语音提取方法。 语音识别系统执行独立分量分析（ICA）以将通过多个麦克风输入的混合信号分离成声源信号，通过使用高斯混合模型从分离的声源信号中提取用于语音识别的一个目标语音（ GMM）或隐马尔可夫模型（HMM），并且从所提取的目标语音中自动识别期望的语音。 因此，即使在噪声环境中也可以获得高的语音识别率。

公开(公告)号：US20090150146A1

公开(公告)日：2009-06-11

申请号：US12242819

申请日：2008-09-30

申请人： Hoon Young CHO ,  Yun Keun Lee ,  Jeom Ja Kang ,  Byung Ok Kang ,  Kap Kee Kim ,  Sung Joo Lee ,  Ho Young Jung ,  Hoon Chung ,  Jeon Gue Park ,  Hyung Bae Jeon

发明人： Hoon Young CHO ,  Yun Keun Lee ,  Jeom Ja Kang ,  Byung Ok Kang ,  Kap Kee Kim ,  Sung Joo Lee ,  Ho Young Jung ,  Hoon Chung ,  Jeon Gue Park ,  Hyung Bae Jeon

IPC分类号： G10L15/20

CPC分类号： G10L15/20 ,  G10L21/0272 ,  G10L2021/02166

摘要： A microphone-array-based speech recognition system using a blind source separation (BBS) and a target speech extraction method in the system are provided. The speech recognition system performs an independent component analysis (ICA) to separate mixed signals input through a plurality of microphone into sound-source signals, extracts one target speech spoken for speech recognition from the separated sound-source signals by using a Gaussian mixture model (GMM) or a hidden Markov Model (HMM), and automatically recognizes a desired speech from the extracted target speech. Accordingly, it is possible to obtain a high speech recognition rate even in a noise environment.

摘要翻译： 提供了一种基于麦克风阵列的语音识别系统，该系统使用盲源分离（BBS）和目标语音提取方法。 语音识别系统执行独立分量分析（ICA）以将通过多个麦克风输入的混合信号分离成声源信号，通过使用高斯混合模型从分离的声源信号中提取用于语音识别的一个目标语音（ GMM）或隐马尔可夫模型（HMM），并且从所提取的目标语音中自动识别期望的语音。 因此，即使在噪声环境中也可以获得高的语音识别率。