Huawei Technologies Co., Limited

Huawei Technologies Duesseldorf Gmbh

Kainan Chen

Peter Grosche

Jürgen Geiger

Karim Helwani

Wenyu Jin

Mohammad Taghizadeh

Juergen Geiger

A device for estimating Direction of Arrival (DOA) of sound from Q&#x2265;1 sound sources is provided. The device is configured to obtain a phase difference matrix, which includes measured phase difference values, each of the measured phase difference values being a measured value of a phase difference between two microphone units for a frequency bin in a range of frequencies of the sound. The device is further configured to generate a replicated phase difference matrix by replicating the measured phase difference values to other potential sinusoidal periods, calculate a DOA value for each phase difference value in the replicated phase difference matrix, and determine, as Q DOA results, the Q most prominent peak values in a histogram generated based on the calculated DOA values.

Device and method for estimating direction of arrival

A device estimates direction of arrival (DOA) of sound fromsound sources received by P microphones, wherein P&#x2265;&#x3e;1. The device is configured to transform the output signals of the microphones into the frequency domain and compute a covariance matrix for each of N frequency bins in a range of frequencies of the sound. Further, the device is configured to calculate an adapted covariance matrix from each of the covariance matrices for wide-band merging, calculate an accumulated covariance matrix from the N adapted covariance matrices, and estimate the DOA for each of the sound sources based on the accumulated covariance matrix. In order to calculate an adapted covariance matrix from a covariance matrix, the device is configured to spectrally decompose the covariance matrix and obtain a plurality of eigenvectors, rotate each obtained eigenvector, and construct each rotated eigenvector back to the shape of the covariance matrix.

Device and method for estimating direction of arrival of sound from a plurality of sound sources

The proposed method for localizing a target sound source from a plurality of sound sources, wherein a multi-channel recording signal of the plurality of sound sources comprises a plurality of microphone channel signals, comprises converting each microphone channel signal into a respective channel spectrogram in a time-frequency domain, blindly separating the channel spectrograms to obtain a plurality of separated source signals, identifying, among the plurality of separated source signals, the separated source signal that best matches a target source model, estimating, based on the identified separated source signal, a binary mask reflecting where the target sound source is active in the channel spectrograms in terms of time and frequency, applying the binary mask on the channel spectrograms to obtain masked channel spectrograms, and localizing the target sound source from the plurality of sound sources based on the masked channel spectrograms.

Localization algorithm for sound sources with known statistics

An apparatus configured to obtain a plurality of phase differences is provided. Each phase difference represents a difference in phase between a spectral component in a first sound signal and a corresponding spectral component in a second sound signal, to estimate an aliasing frequency. Phase differences in frequency bands above the aliasing frequency are expected to be wrapped, and to unwrap the plurality of phase differences in dependence on the estimated aliasing frequency. A phase difference obtained from spectral components that are comprised in one frequency band is unwrapped independently of any phase difference obtained from spectral components that are comprised in another frequency band.

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Munich, Germany

Kainan Chen