首页> 外国专利> ANOMALOUS SOUND DETECTION APPARATUS, DEGREE-OF-ANOMALY CALCULATION APPARATUS, ANOMALOUS SOUND GENERATION APPARATUS, ANOMALOUS SOUND DETECTION TRAINING APPARATUS, ANOMALOUS SIGNAL DETECTION APPARATUS, ANOMALOUS SIGNAL DETECTION TRAINING APPARATUS, AND METHODS AND PROGRAMS THEREFOR

ANOMALOUS SOUND DETECTION APPARATUS, DEGREE-OF-ANOMALY CALCULATION APPARATUS, ANOMALOUS SOUND GENERATION APPARATUS, ANOMALOUS SOUND DETECTION TRAINING APPARATUS, ANOMALOUS SIGNAL DETECTION APPARATUS, ANOMALOUS SIGNAL DETECTION TRAINING APPARATUS, 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,异常声音检测训练装置,异常信号检测装置,异常信号检测训练方法和装置,异常信号检测装置,异常信号检测方法和装置

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 ρ, 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 ,通过使用正常声音和特征的训练数据,获得与具有预定值的假阳性率ρ相对应的阈值φρ输入的金额提取函数;第二功能更新单元 8 ,其基于由阈值φρ定义的Neyman-Pearson型优化索引来更新已更新的特征量提取功能。获得并重复执行每个上述单元的处理。

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