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公开(公告)号：US20150112678A1
公开(公告)日：2015-04-23
申请号：US14586169
申请日：2014-12-30
Applicant: DOMINIC FRANK JULIAN BINKS , SACHA KRSTULOVIC , CHRISTOPHER JAMES MITCHELL
IPC: G10L17/26 , G10L21/0216 , G10L15/02
Abstract: Broadly speaking, embodiments of the present invention provide a device, systems and methods for capturing sounds, generating a sound model (or “sound pack”) for each captured sound, and identifying a detected sound using the sound model(s). Preferably, a single device is used to capture a sound, store sound models, and to identify a detected sound using the stored sound models.
Abstract translation: 概括而言，本发明的实施例提供了用于捕获声音的装置，系统和方法，为每个捕获的声音产生声音模型（或“声音包”），以及使用声音模型识别检测到的声音。 优选地，使用单个设备来捕获声音，存储声音模型，并且使用所存储的声音模型来识别检测到的声音。
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Patent Agency Ranking
公开(公告)号：US20110218952A1
公开(公告)日：2011-09-08
申请号：US13128588
申请日：2009-11-26
Applicant: Christopher James Mitchell
Inventor： Christopher James Mitchell
CPC classification number: G10L17/26 , G06N99/005 , G10L15/02 , G10L21/0216 , G10L25/48
Abstract: We describe a digital sound identification system, the system comprising: non-volatile memory for storing a Markov model; stored program memory storing processor control code; a sound data input; a processor coupled to said sound data input, to said working memory, and to said stored program memory for executing said processor control code, and wherein said processor control code comprises code to: input, from said sound data input, first sample sound data for a first sound to be identified, said first sample sound data defining first sample frequency domain data, said first sample frequency domain data defining an energy of said first sample in a plurality of frequency ranges; generate a first set of mean and variance values for at least a first Markov model of said first sample sound from said first sample frequency domain data; store said first Markov model in said non-volatile memory; input interference sound data defining interference frequency domain data; adjust said mean and variance values of said first Markov model using said interference frequency domain data; input third sound data defining third sound frequency domain data; determine a probability of said third sound frequency domain data fitting at least said first Markov model; and output sound identification data dependent on said probability.
Abstract translation: 我们描述一种数字声音识别系统，该系统包括：用于存储马尔可夫模型的非易失性存储器; 存储程序存储器存储处理器控制代码; 声音数据输入; 耦合到所述声音数据输入的处理器，所述工作存储器和用于执行所述处理器控制代码的所述存储的程序存储器，并且其中所述处理器控制代码包括代码：从所述声音数据输入端输入第一样本声音数据， 要识别的第一声音，所述第一采样声音数据定义第一采样频域数据，所述第一采样频域数据定义多个频率范围中的所述第一采样的能量; 从所述第一样本频域数据生成所述第一样本声音的至少第一马尔科夫模型的第一组平均值和方差值; 在所述非易失性存储器中存储所述第一马尔可夫模型; 定义干扰频域数据的输入干扰声音数据; 使用所述干扰频域数据调整所述第一马尔可夫模型的所述均值和方差值; 输入定义第三声频域数据的第三声音数据; 确定所述第三声频域数据拟合至少所述第一马尔可夫模型的概率; 并输出取决于所述概率的声音识别数据。
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公开(公告)号：US10586543B2
公开(公告)日：2020-03-10
申请号：US14586169
申请日：2014-12-30
Applicant: Dominic Frank Julian Binks , Sacha Krstulović , Christopher James Mitchell
Abstract: Broadly speaking, embodiments of the present invention provide a device, systems and methods for capturing sounds, generating a sound model (or “sound pack”) for each captured sound, and identifying a detected sound using the sound model(s). Preferably, a single device is used to capture a sound, store sound models, and to identify a detected sound using the stored sound models.
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公开(公告)号：US20160283967A1
公开(公告)日：2016-09-29
申请号：US14777894
申请日：2014-03-21
Applicant: Christopher James Mitchell
Inventor： Christopher James Mitchell
CPC classification number: G06Q30/0231 , G06Q30/0226 , G10L25/51 , H04R29/00
Abstract: A mobile device comprising a software application configured to detect the sound of a product use event; provide a user reward using said software application in response to said detection; capture data relating to said product use event; and provide said captured data to a remote computer system for analysis.
Abstract translation: 一种移动设备，包括被配置为检测产品使用事件的声音的软件应用程序; 响应于所述检测提供使用所述软件应用程序的用户奖励; 捕获与所述产品使用事件有关的数据; 并将所述捕获的数据提供给远程计算机系统用于分析。
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公开(公告)号：US08918343B2
公开(公告)日：2014-12-23
申请号：US13128588
申请日：2009-11-26
Applicant: Christopher James Mitchell
Inventor： Christopher James Mitchell
IPC: G06F15/18 , G10L17/26 , G06N99/00 , G10L15/02 , G10L21/0216
CPC classification number: G10L17/26 , G06N99/005 , G10L15/02 , G10L21/0216 , G10L25/48
Abstract: A digital sound identification system for storing a Markov model is disclosed. A processor is coupled to a sound data input, working memory, and a stored program memory for executing processor control code to input sound data for a sound to be identified. The sample sound data defines a sample frequency domain data energy in a range of frequency. Mean and variance values for a Markov model of the sample sound are generated. The Markov model is stored in the non-volatile memory. Interference sound data defining interference frequency domain data is inputted. The mean and variance values of the Markov model using the interference frequency domain data are adjusted. Sound data defining other sound frequency domain data are inputted. A probability of the other sound frequency domain data fitting the Markov model is determined. Finally, sound identification data dependent on the probability is outputted.
Abstract translation: 公开了一种用于存储马尔可夫模型的数字声音识别系统。 处理器耦合到声音数据输入，工作存储器和存储的程序存储器，用于执行处理器控制代码以输入要识别的声音的声音数据。 样本声音数据定义频率范围内的采样频域数据能量。 产生样本声音的马尔可夫模型的均值和方差值。 马尔可夫模型存储在非易失性存储器中。 输入定义干扰频域数据的干扰声音数据。 调整使用干扰频域数据的马尔科夫模型的均值和方差值。 输入定义其他声频域数据的声音数据。 确定其他声频域数据拟合马尔可夫模型的概率。 最后，输出取决于概率的声音识别数据。
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公开(公告)号：US20150106095A1
公开(公告)日：2015-04-16
申请号：US14533837
申请日：2014-11-05
Applicant: CHRISTOPHER JAMES MITCHELL
Inventor： CHRISTOPHER JAMES MITCHELL
IPC: G10L17/26 , G10L21/0216 , G10L15/02
CPC classification number: G10L25/51 , G06F17/18 , G08B13/00 , G08B13/16 , G10L15/02 , G10L15/142 , G10L15/20 , G10L25/57 , G10L25/63
Abstract: A digital sound identification system for storing a Markov model is disclosed. A processor is coupled to a sound data input, working memory, and a stored program memory for executing processor control code to input sound data for a sound to be identified. The sample sound data defines a sample frequency domain data energy in a range of frequency. Mean and variance values for a Markov model of the sample sound are generated. The Markov model is stored in the non-volatile memory. Interference sound data defining interference frequency domain data is inputted. The mean and variance values of the Markov model using the interference frequency domain data are adjusted. Sound data defining other sound frequency domain data are inputted. A probability of the other sound frequency domain data fitting the Markov model is determined. Finally, sound identification data dependent on the probability is outputted.
Abstract translation: 公开了一种用于存储马尔可夫模型的数字声音识别系统。 处理器耦合到声音数据输入，工作存储器和存储的程序存储器，用于执行处理器控制代码以输入要识别的声音的声音数据。 样本声音数据定义频率范围内的采样频域数据能量。 产生样本声音的马尔可夫模型的均值和方差值。 马尔可夫模型存储在非易失性存储器中。 输入定义干扰频域数据的干扰声音数据。 调整使用干扰频域数据的马尔科夫模型的均值和方差值。 输入定义其他声频域数据的声音数据。 确定其他声频域数据拟合马尔可夫模型的概率。 最后，输出取决于概率的声音识别数据。
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