首页> 外国专利> ABNORMAL SOUND DETECTION DEVICE, ABNORMALITY DEGREE CALCULATION DEVICE, ABNORMAL SOUND GENERATION DEVICE, ABNORMAL SOUND DETECTION LEARNING DEVICE, ABNORMAL SIGNAL DETECTION DEVICE, ABNORMAL SIGNAL DETECTION LEARNING DEVICE, AND METHODS AND PROGRAMS THEREFOR

ABNORMAL SOUND DETECTION DEVICE, ABNORMALITY DEGREE CALCULATION DEVICE, ABNORMAL SOUND GENERATION DEVICE, ABNORMAL SOUND DETECTION LEARNING DEVICE, ABNORMAL SIGNAL DETECTION DEVICE, ABNORMAL SIGNAL DETECTION LEARNING DEVICE, AND METHODS AND PROGRAMS THEREFOR

机译:异常声音检测装置,异常度计算装置,异常声音产生装置,异常声音检测学习装置,异常信号检测装置,异常信号检测学习装置及其方法和程序

摘要

To provide an anomalous sound detection training technique by which a feature amount extraction function for detecting anomalous sound can be generated irrespective of whether training data for anomalous signals is available or not. An anomalous sound detection training apparatus includes: a first function updating unit 3 that updates a feature amount extraction function and an feature amount inverse transformation function, which are input, based on an optimization index of a variational autoencoder; an acoustic feature extraction unit 4 that extracts an acoustic feature of normal sound based on training data for normal sound; a normal sound model updating unit 5 that updates a normal sound model by using the acoustic feature that is extracted; a threshold updating unit 6 that obtains a threshold ϕρ corresponding to a false positive rate p, which has a predetermined value, by using the training data for normal sound and the feature amount extraction function that is input; and a second function updating unit 8 that updates the feature amount extraction function that is updated, based on a Neyman-Pearson-type optimization index defined by the threshold ϕρ that is obtained, and repeatedly performs processing of each of the above-mentioned units.
机译:为了提供一种异常声音检测训练技术,通过该技术可以生成用于检测异常声音的特征量提取功能,而不管用于异常信号的训练数据是否可用。一种异常声音检测训练设备,包括:第一函数更新单元3,其基于变分自动编码器的优化指标来更新输入的特征量提取函数和特征量逆变换函数;以及声学特征提取单元4,其基于用于正常声音的训练数据来提取正常声音的声学特征;普通声音模型更新单元5,其通过使用所提取的声学特征来更新普通声音模型;阈值更新单元6通过使用用于正常声音的训练数据和输入的特征量提取函数来获得与具有预定值的假阳性率p相对应的阈值ϕ ρ。第二功能更新单元8,其基于由所获得的阈值ϕ ρ所定义的内曼-皮尔逊型优化指标来更新所更新的特征量提取函数,并重复执行上述每个单元。

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