- Read more about Blind Speech Separation based on Complex Spherical k-Mode Clustering
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We present an algorithm for clustering complex-valued unit length vectors on the unit hypersphere, which we call complex spherical k-mode clustering, as it can be viewed as a generalization of the spherical k-means algorithm to normalized complex-valued vectors. We show how the proposed algorithm can be derived from the Expectation Maximization algorithm for complex Watson mixture models and prove its applicability in a blind speech separation (BSS) task with real-world room impulse response measurements.
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- Read more about Neural Network based Spectral Mask Estimation for Acoustic Beamforming
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We present a neural network based approach to acoustic beamform- ing. The network is used to estimate spectral masks from which the Cross-Power Spectral Density matrices of speech and noise are estimated, which in turn are used to compute the beamformer co- efficients. The network training is independent of the number and the geometric configuration of the microphones. We further show that it is possible to train the network on clean speech only, avoid- ing the need for stereo data with separated speech and noise. Two types of networks are evaluated.
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- Read more about NMF-based source separation utilizing prior knowledge on encoding vector
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- Read more about Variable Span Filtering for Speech Enhancement
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In this work, we consider enhancement of multichannel speech recordings. Linear filtering and subspace approaches have been considered previously for solving the problem. The current linear filtering methods, although many variants exist, have limited control of noise reduction and speech distortion. Subspace approaches, on the other hand, can potentially yield better control by filtering in the eigen-domain, but traditionally these approaches have not been optimized explicitly for traditional noise reduction and signal distortion measures.
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- Read more about NMF-based source separation utilizing prior knowledge on encoding vector
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- Read more about On The Importance of Harmonic Phase Modification for Improved Speech Signal Reconstruction
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- Read more about IMPROVED MULTI-MICROPHONE NOISE REDUCTION PRESERVING BINAURAL CUES
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Poster.pdf
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- Read more about ACOUSTIC SOURCE SEPARATION USING THE SHORT-TIME QUATERNION FOURIER TRANSFORMS OF PARTICLE VELOCITY SIGNALS
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Quaternion Fourier transforms (QFT) provide a powerful tool for the analysis of signals obtained from vector probes. Acoustic particle velocity is one such signal which can be measured with specially designed microphone arrays. This paper presents a time-frequency source separation method based on the short-time quaternion Fourier transform of acoustic particle velocity signals and the agglomerative k-plane clustering of the vector part of the resulting representation. Two example cases, one with a single and one with two interfering sources are presented.
icasspposter.pdf
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- Read more about USING CONDITIONAL RESTRICTED BOLTZMANN MACHINES FOR SPECTRAL ENVELOPE MODELING IN SPEECH BANDWIDTH EXTENSION
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