On the monodromy of the moduli space of Calabi-Yau threefolds coming from eight planes in P3\mathbb{P}^3

It is a fundamental problem in geometry to decide which moduli spaces of polarized algebraic varieties are embedded by their period maps as Zariski open subsets of locally Hermitian symmetric domains. In the present work we prove that the moduli space of Calabi-Yau threefolds coming from eight planes in $\mathbb{P}^3$ does {\em not} have this property. We show furthermore that the monodromy group of a good family is Zariski dense in the corresponding symplectic group. Moreover, we study a natural sublocus which we call hyperelliptic locus, over which the variation of Hodge structures is naturally isomorphic to wedge product of a variation of Hodge structures of weight one. It turns out the hyperelliptic locus does not extend to a Shimura subvariety of type III (Siegel space) within the moduli space. Besides general Hodge theory, representation theory and computational commutative algebra, one of the proofs depends on a new result on the tensor product decomposition of complex polarized variations of Hodge structures.Comment: 26 page

A robust sequential hypothesis testing method for brake squeal localisation

This contribution deals with the in situ detection and localisation of brake squeal in an automobile. As brake squeal is emitted from regions known a priori, i.e., near the wheels, the localisation is treated as a hypothesis testing problem. Distributed microphone arrays, situated under the automobile, are used to capture the directional properties of the sound field generated by a squealing brake. The spatial characteristics of the sampled sound field is then used to formulate the hypothesis tests. However, in contrast to standard hypothesis testing approaches of this kind, the propagation environment is complex and time-varying. Coupled with inaccuracies in the knowledge of the sensor and source positions as well as sensor gain mismatches, modelling the sound field is difficult and standard approaches fail in this case. A previously proposed approach implicitly tried to account for such incomplete system knowledge and was based on ad hoc likelihood formulations. The current paper builds upon this approach and proposes a second approach, based on more solid theoretical foundations, that can systematically account for the model uncertainties. Results from tests in a real setting show that the proposed approach is more consistent than the prior state-of-the-art. In both approaches, the tasks of detection and localisation are decoupled for complexity reasons. The localisation (hypothesis testing) is subject to a prior detection of brake squeal and identification of the squeal frequencies. The approaches used for the detection and identification of squeal frequencies are also presented. The paper, further, briefly addresses some practical issues related to array design and placement. (C) 2019 Author(s)

Combined single-microphone wiener and MVDR filtering based on speech interframe correlations and speech presence probability

For single-microphone noise reduction, a minimum variance distortionless response (MVDR) filter has been recently proposed based on speech correlations of consecutive time frames. This filter is able to keep speech distortion low but compared to conventional approaches achieves less noise reduction. Further, when only having access to the noisy speech, more artifacts in the background noise are audible due to estimation errors of the speech interframe correlations, especially in time-frequency regions where speech is not dominant. Therefore, in this paper we propose to apply the MVDR filter where speech is dominant and the singlechannel Wiener filter otherwise, using a weighting based on the speech presence probability. In addition, we modify the decision-directed approach to estimate the a priori SNR in a more robust way for short analysis frames. Experimental results show that the proposed scheme achieves a better speech quality compared to the MVDR filter and the single-channel Wiener filter

A general framework for incorporating time-frequency domain sparsity in multi-channel speech dereverberation

status: publishe