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The present application discloses a method for determining a same audio, an apparatus, a device, a storage medium, and a program product thereof. The method comprises: acquiring a first target audio and a second target audio to be compared; performing slicing processing on the first target audio and the second target audio to obtain a plurality of first audio segments corresponding to the first target audio and a plurality of second audio segments corresponding to the second target audio; generating a first audio fingerprint corresponding to each first audio segment based on audio features of the first audio segment, and generating a second audio fingerprint corresponding to each second audio segment based on audio features of the second audio segment; and determining audio similarity between the first target audio and the second target audio in different audio segments according to the first audio fingerprint and the second audio fingerprint.

A method for enhancing the detection of fraudulent audio data is provided that includes capturing audio data of a user speaking during an authentication transaction, dividing the audio data into segments, determining a quality control vector for each segment, and determining whether each segment is of adequate quality. Moreover, the method includes calculating a voice replay score and a voice cloning detection score for each adequate quality segment, and determining, by a trained machine learning model operated by the electronic device, a weight for each adequate quality segment. Furthermore, the method includes applying the weight determined for each adequate quality segment to the voice replay and voice cloning scores calculated for the respective adequate quality segment, calculating a decision score, and comparing the decision score against a threshold value. In response to determining the decision score satisfies the threshold value, determining the captured audio data is genuine.

The toy bell (1) comprises: - a bell-shaped body (2) having an internal cavity; - a clapper element (4) associated within the bell-shaped body (2); and - an anti-removal safety system (5) of the clapper element (4).

A method of processing audio is provided. The method includes determining modulated filter bank, MFB, domain broad band gains for fading an audio signal in accordance with a time domain target gain, so that application of the broad band gains in the MFB domain emulates application of the target gain in the time domain. Determining the broad band gains includes computing the broad band gains using the target gain, an MFB analysis prototype filter, and an MFB synthesis prototype filter. Also provided are corresponding apparatus, programs, and computer-readable storage media.

A system and method for detecting anomalous sound are disclosed. The method includes receiving a spectrogram of an audio signal with elements defined by values in a time-frequency domain of the spectrogram. Each of the values corresponds to an element of the spectrogram that is identified by a coordinate in the time-frequency domain. The time-frequency domain of the spectrogram is partitioned into a context region and a target region. The context region and the target region are processed by a neural network using an attentive neural process to recover values of the spectrogram for elements with coordinates in the target region. The recovered values of the elements of the target region are compared with values of elements of the partitioned target region. An anomaly score is determined based on the comparison. The anomaly score is used for performing a control action.

An information processing system according to the present disclosure comprises: an acquisition unit that acquires first musical piece data; and a presentation unit that presents information indicating similarity of the first musical piece data to second musical piece data being existing musical piece data. The presentation unit causes a screen including a display of a first mode indicating the degree of similarity of each of a plurality of items for evaluating the similarity to the musical piece data to be displayed.

本申请公开了一种机器人心理特征分阶段约束控制方法，步骤为：划分机器人的心理成长阶段；在机器人运行过程中，实时采集人机交互数据和环境数据；根据采集的数据与预设的判断数据进行对比，匹配机器人的工作场景并确定当前所处的心理成长阶段；调用当前心理成长阶段配置的心理特征参数和约束规则，对机器人约束控制；获取机器人的交互反馈数据，对当前心理成长阶段所对应的约束参数进行动态适配优化。本申请的有益效果：通过实时采集交互数据、环境数据，动态判断机器人的心理成长阶段，并根据用户反馈持续优化约束参数，实现机器人心理特征的动态适配，满足不同用户、不同场景的交互需求。

Eine Aufgabenunterstützungseinrichtung (2) umfasst: eine Aufgabenidentifizierungseinheit (10), die eine Aufgabe als ein Unterstützungsziel identifiziert; und eine Textinformationserwerbungseinheit (13), die Textinformationen über ein Aufgabengeräusch, das ein Geräusch ist, das die von der Aufgabenidentifizierungseinheit (10) identifizierte Aufgabe anzeigt, erwirbt.

A sound source localization method and apparatus. The method comprises: acquiring audio signals of a sound source to be localized collected by microphones (mic1, mic2, mic3, and mic4) in a plurality of microphone arrays (S201); and localizing said sound source on the basis of the audio signals and weight information corresponding to the plurality of microphone arrays (S202). Therefore, said sound source is localized by partitioning microphones into more optimal microphone arrays and providing corresponding weight information, which can effectively reduce localization calculation errors and improve the localization accuracy.

本发明涉及语料采集控制技术领域，尤其涉及一种基于智能算法的语料自动采集及质量控制方法及系统，通过获取语料属性信息构建状态表征并生成对抗采集策略，执行后提取盲区语料，选取边界语料并采集，构建特征映射确定关联语料，将质量标注值传播至关联语料得到修正质量值，将效用测量值传播至边界语料得到预测效用值，最后融合质量与效用值执行语料质量控制，提高了语料采集的全面性和语料质量控制的准确性。