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公开(公告)号：US20180158463A1
公开(公告)日：2018-06-07
申请号：US15835318
申请日：2017-12-07
Applicant: INTERACTIVE INTELLIGENCE GROUP, INC.
Inventor： Zhenhao Ge , Ananth N. Iyer , Srinath Cheluvaraja , Ram Sundaram , Aravind Ganapathiraju
CPC classification number: G10L17/04 , G10L17/00 , G10L17/18 , G10L25/45 , G10L2025/937
Abstract: A method for classifying speakers includes: receiving, by a speaker recognition system including a processor and memory, input audio including speech from a speaker; extracting, by the speaker recognition system, a plurality of speech frames containing voiced speech from the input audio; computing, by the speaker recognition system, a plurality of features for each of the speech frames of the input audio; computing, by the speaker recognition system, a plurality of recognition scores for the plurality of features; computing, by the speaker recognition system, a speaker classification result in accordance with the recognition scores; and outputting, by the speaker recognition system, the speaker classification result.
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公开(公告)号：US10755718B2
公开(公告)日：2020-08-25
申请号：US15835318
申请日：2017-12-07
Applicant: INTERACTIVE INTELLIGENCE GROUP, INC.
Inventor： Zhenhao Ge , Ananth N. Iyer , Srinath Cheluvaraja , Ram Sundaram , Aravind Ganapathiraju
Abstract: A method for classifying speakers includes: receiving, by a speaker recognition system including a processor and memory, input audio including speech from a speaker; extracting, by the speaker recognition system, a plurality of speech frames containing voiced speech from the input audio; computing, by the speaker recognition system, a plurality of features for each of the speech frames of the input audio; computing, by the speaker recognition system, a plurality of recognition scores for the plurality of features; computing, by the speaker recognition system, a speaker classification result in accordance with the recognition scores; and outputting, by the speaker recognition system, the speaker classification result.
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Patent Agency Ranking
3.发明授权System and method for learning alternate pronunciations for speech recognition 有权用于学习语音识别的交替发音的系统和方法公开(公告)号：US09489943B2
公开(公告)日：2016-11-08
申请号：US14515607
申请日：2014-10-16
Applicant: Interactive Intelligence Group, Inc.
Inventor： Zhenhao Ge , Vivek Tyagi , Aravind Ganapathiraju , Ananth Nagaraja Iyer , Scott Allen Randal , Felix Immanuel Wyss
IPC: G10L15/187 , G06F17/28 , G09B19/04 , G10L15/06 , G09B19/06
CPC classification number: G10L15/063 , G06F17/2735 , G06F17/28 , G09B19/04 , G09B19/06 , G10L15/14 , G10L15/187 , G10L2015/081
Abstract: A system and method for learning alternate pronunciations for speech recognition is disclosed. Alternative name pronunciations may be covered, through pronunciation learning, that have not been previously covered in a general pronunciation dictionary. In an embodiment, the detection of phone-level and syllable-level mispronunciations in words and sentences may be based on acoustic models trained by Hidden Markov Models. Mispronunciations may be detected by comparing the likelihood of the potential state of the targeting pronunciation unit with a pre-determined threshold through a series of tests. It is also within the scope of an embodiment to detect accents.
Abstract translation: 公开了用于学习语音识别的替代发音的系统和方法。 通过发音学习可以覆盖另类名称发音，这些发音先前未被一般发音词典涵盖。 在一个实施例中，在单词和句子中检测电话级和音节级错误可以基于由隐马尔可夫模型训练的声学模型。 可以通过一系列测试来比较目标语音单元的潜在状态与预定阈值的可能性来检测微分。 检测重音也属于实施例的范围。
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4.发明申请System and Method for Learning Alternate Pronunciations for Speech Recognition 有权学习用于语音识别的替代发音的系统和方法公开(公告)号：US20170032780A1
公开(公告)日：2017-02-02
申请号：US15291353
申请日：2016-10-12
Applicant: Interactive Intelligence Group, Inc.
Inventor： Zhenhao Ge , Vivek Tyagi , Aravind Ganapathiraju , Ananth Nagaraja Iyer , Scott Allen Randal , Felix Immanuel Wyss
CPC classification number: G10L15/063 , G06F17/2735 , G06F17/28 , G09B19/04 , G09B19/06 , G10L15/14 , G10L15/187 , G10L2015/081
Abstract: A system and method for learning alternate pronunciations for speech recognition is disclosed. Alternative name pronunciations may be covered, through pronunciation learning, that have not been previously covered in a general pronunciation dictionary. In an embodiment, the detection of phone-level and syllable-level mispronunciations in words and sentences may be based on acoustic models trained by Hidden Markov Models. Mispronunciations may be detected by comparing the likelihood of the potential state of the targeting pronunciation unit with a pre-determined threshold through a series of tests. It is also within the scope of an embodiment to detect accents.
Abstract translation: 公开了用于学习语音识别的替代发音的系统和方法。 通过发音学习可以覆盖另类名称发音，这些发音先前未被一般发音词典涵盖。 在一个实施例中，在单词和句子中检测电话级和音节级错误可以基于由隐马尔可夫模型训练的声学模型。 可以通过一系列测试来比较目标语音单元的潜在状态与预定阈值的可能性来检测微分。 检测重音也属于实施例的范围。
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5.发明申请System and Method for Learning Alternate Pronunciations for Speech Recognition 有权学习用于语音识别的替代发音的系统和方法公开(公告)号：US20150106082A1
公开(公告)日：2015-04-16
申请号：US14515607
申请日：2014-10-16
Applicant: Interactive Intelligence Group, Inc.
Inventor： Zhenhao Ge , Vivek Tyagi , Aravind Ganapathiraju , Ananth Nagaraja Iyer , Scott Allen Randal , Felix Immanuel Wyss
IPC: G10L15/187 , G06F17/28 , G09B19/04 , G06F17/27
CPC classification number: G10L15/063 , G06F17/2735 , G06F17/28 , G09B19/04 , G09B19/06 , G10L15/14 , G10L15/187 , G10L2015/081
Abstract: A system and method for learning alternate pronunciations for speech recognition is disclosed. Alternative name pronunciations may be covered, through pronunciation learning, that have not been previously covered in a general pronunciation dictionary. In an embodiment, the detection of phone-level and syllable-level mispronunciations in words and sentences may be based on acoustic models trained by Hidden Markov Models. Mispronunciations may be detected by comparing the likelihood of the potential state of the targeting pronunciation unit with a pre-determined threshold through a series of tests. It is also within the scope of an embodiment to detect accents.
Abstract translation: 公开了用于学习语音识别的替代发音的系统和方法。 通过发音学习可以覆盖另类名称发音，这些发音先前未被一般发音词典涵盖。 在一个实施例中，在单词和句子中检测电话级和音节级错误可以基于由隐马尔可夫模型训练的声学模型。 可以通过一系列测试来比较目标语音单元的潜在状态与预定阈值的可能性来检测微分。 检测重音也属于实施例的范围。
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公开(公告)号：US10535000B2
公开(公告)日：2020-01-14
申请号：US15727498
申请日：2017-10-06
Applicant: INTERACTIVE INTELLIGENCE GROUP, INC.
Inventor： Zhenhao Ge , Ananth Nagaraja Iyer , Srinath Cheluvaraja , Aravind Ganapathiraju
Abstract: A method for training a neural network of a neural network based speaker classifier for use in speaker change detection. The method comprises: a) preprocessing input speech data; b) extracting a plurality of feature frames from the preprocessed input speech data; c) normalizing the extracted feature frames of each speaker within the preprocessed input speech data with each speaker's mean and variance; d) concatenating the normalized feature frames to form overlapped longer frames having a frame length and a hop size; e) inputting the overlapped longer frames to the neural network based speaker classifier; and f) training the neural network through forward-backward propagation.
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公开(公告)号：US09767792B2
公开(公告)日：2017-09-19
申请号：US15291353
申请日：2016-10-12
Applicant: Interactive Intelligence Group, Inc.
Inventor： Zhenhao Ge , Vivek Tyagi , Aravind Ganapathiraju , Ananth Nagaraja Iyer , Scott Allen Randal , Felix Immanuel Wyss
CPC classification number: G10L15/063 , G06F17/2735 , G06F17/28 , G09B19/04 , G09B19/06 , G10L15/14 , G10L15/187 , G10L2015/081
Abstract: A system and method for learning alternate pronunciations for speech recognition is disclosed. Alternative name pronunciations may be covered, through pronunciation learning, that have not been previously covered in a general pronunciation dictionary. In an embodiment, the detection of phone-level and syllable-level mispronunciations in words and sentences may be based on acoustic models trained by Hidden Markov Models. Mispronunciations may be detected by comparing the likelihood of the potential state of the targeting pronunciation unit with a pre-determined threshold through a series of tests. It is also within the scope of an embodiment to detect accents.
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