A system, device and method for assessing a fit quality of an earpiece while in use in a noisy environment. The earpiece having an external microphone for capturing an outer-ear audio signal and an internal microphone for capturing an inner-ear audio signal. The fit quality being assessed by estimating a filter according to the captured inner-ear and outer-ear audio signals, and determining a fit quality according to identified coefficients of the estimated filter. A system, device and method for assessing a seal quality of an earpiece while in use in a quiet environment. The earpiece having a loudspeaker for emitting a sound stimulus towards the ear canal and an internal microphone for capturing an audio signal inside the ear canal. The seal quality being assessed by estimating a transfer function according the emitted and captured sound stimulus, and determining at least one seal-quality indicator according to a signal magnitude of the transfer function.

A method and a system for vision-based defect detection are proposed. The method includes the following steps. A test audio signal is outputted to a device-under-test (DUT), and a response signal of the DUT with respect to the test audio signal is received to generate a received audio signal. Signal processing is performed on the received audio signal to generate a spectrogram, and whether the DUT has an unacceptable defect with respect to the predefined auditory standard is determined by analyzing a distribution of signal strength according to the spectrogram.

Methods implemented in a system utilizing computing programs for a speaker and a listener in conversation are provided. Aspects include (i) a reminder provisioner for a speaker which is triggered according to speed, pitch or volume of the speaker's speech, (ii) a speech training provisioner for a speaker, and (iii) an application which records and plays back difficult conversation to understand.

The present invention provides a method for processing audio data, comprising the steps of providing input audio data containing a mixture of audio data including first audio data of a first musical timbre and second audio data of a second musical timbre different from said first musical timbre, decomposing the input audio data to provide decomposed data representative of the first audio data, transforming the decomposed data to obtain third audio data.

An information processing method includes, in response to determining that an application is in a video mode, acquiring a video image in real time through a camera group of an electronic device and acquiring a video sound in real time through a microphone group of the electronic device; displaying the video image; mapping an audio manipulation area that includes an operation response area of a sound source in an acquisition area of the camera group; obtaining an input operation for the operation response area; and, in response to the input operation, adjusting a sound collection effect of the sound source corresponding to the operation response area.

A detection device and a detection system that detect a whistle sound to estimate the distance to the sound source are provided. The detection device (1) includes a detector (20) that detects a sound wave; storage (30) that contains characteristic information indicating frequencies of a fundamental and harmonics of a whistle sound and levels of the harmonics relative to the fundamental; a frequency analysis unit (41) that determines a frequency spectrum of a sound wave detected by the detector; a determination unit (45) that determines whether the frequency spectrum has peaks of the fundamental and the harmonics and how many times the peaks of the harmonics from the fundamental exceed a preset minimum level; and a distance estimation unit (46) that estimates a distance to a sound source of a whistle sound detected by the detector, based on a relationship between propagation distances and attenuations of a sound wave as well as information on the levels included in the characteristic information and the result of determination by the determination unit.

An electronic device includes: a wireless communication circuit; a power management circuit; and a control circuit , and the control circuit may: in a state where the electronic device connects a first communication with a first audio output device by using the wireless communication circuit, or is electrically connected with the first audio output device by using the power management circuit, operate in a connection standby mode or in an advertise mode by using a first wireless communication address of the first audio output device; receive a signal for finding the first audio output device from an external electronic device, based on the first wireless communication address; and transmit a signal for letting the first audio output device output a notification to the first audio output device through the first communication, or transmit the signal to the first audio output device through the electrical connection.

Embodiments described herein generally relate to measuring and evaluating a test signal generated by a device under test (DUT). In particular, the test signal generated by the DUT may be compared to a reference signal and scored based on the comparison. For example, a method may include: capturing a test signal from a device under test; splicing the test signal into a plurality of test audio files based on a plurality of frequency bins; at each frequency bin, comparing each of the plurality of test audio files to a corresponding reference audio file from among a plurality of reference audio files, the plurality of reference audio files being associated with a reference signal; and calculating a performance score of the device under test based on the comparisons.

A method for establishing a defect detection model and an electronic apparatus are provided. A first classification model is established based on a training sample set including a plurality of training samples. The training samples are respectively input to the first classification model to obtain a classification result of each training sample. A plurality of outlier samples that are classified incorrectly are obtained from the training samples based on the classification result. A part of outlier samples that are classified incorrectly is deleted from the training samples, and the remaining training samples are used as an optimal sample set. A second classification model is established based on the optimal sample set so as to perform a defect detection through the second classification model.

Techniques for adaptive cross-correlation are discussed. A first signal is received from a first audio sensor associated with a vehicle and a second signal is received from a second audio sensor associated with the vehicle. Techniques may include determining, based at least in part on the first signal, a first transformed signal in a frequency domain. Additionally, the techniques include determining, based at least in part on the second signal, a second transformed signal in the frequency domain. A parameter can be determined based at least in part on a characteristic associated with at least one of the vehicle, an environment proximate the vehicle, or one or more of the first or second signal. Cross-correlation data can be determined based at least in part on one or more of the first transformed signal, the second transformed signal, or the parameter.