A Double Joint Bayesian Approach for J-Vector Based Text-dependent Speaker Verification

J-vector has been proved to be very effective in text-dependent speaker verification with short-duration speech. However, the current state-of-the-art back-end classifiers, e.g. joint Bayesian model, cannot make full use of such deep features. In this paper, we generalize the standard joint Bayesian approach to model the multi-faceted information in the j-vector explicitly and jointly. In our generalization, the j-vector was modeled as a result derived by a generative Double Joint Bayesian (DoJoBa) model, which contains several kinds of latent variables. With DoJoBa, we are able to explicitly build a model that can combine multiple heterogeneous information from the j-vectors. In verification step, we calculated the likelihood to describe whether the two j-vectors having consistent labels or not. On the public RSR2015 data corpus, the experimental results showed that our approach can achieve 0.02\% EER and 0.02\% EER for impostor wrong and impostor correct cases respectively

Abelian and non-abelian anyons in integer quantum anomalous Hall effect and topological phase transitions via superconducting proximity effect

We study the quantum anomalous Hall effect described by a class of two-component Haldane models on square lattices. We show that the latter can be transformed into a pseudospin triplet p+ip-wave paired superfluid. In the long wave length limit, the ground state wave function is described by Halperin's (1,1,-1) state of neutral fermions analogous to the double layer quantum Hall effect. The vortex excitations are charge e/2 abelian anyons which carry a neutral Dirac fermion zero mode. The superconducting proximity effect induces `tunneling' between `layers' which leads to topological phase transitions whereby the Dirac fermion zero mode fractionalizes and Majorana fermions emerge in the edge states. The charge e/2 vortex excitation carrying a Majorana zero mode is a non-abelian anyon. The proximity effect can also drive a conventional insulator into a quantum anomalous Hall effect state with a Majorana edge mode and the non-abelian vortex excitations.Comment: 6 pages, 4 figures, accepted by Phys. Rev.

Digital Transformation, Operating Capacity and Firm Performance: Empirical Evidence from the Chinese Stock Market

In the context of the digital economy, digital technologies such as big data, artificial intelligence, cloud computing and so on continue to promote enterprise value creation. This paper takes the annual reports of listed companies in Shanghai and Shenzhen A-shares from 2015 to 2021 as the object, constructs digital transformation indexes based on Word2Vec machine learning technology, and empirically analyzes the relationship between digital transformation, enterprise operating capacity and company performance. The study finds that: the higher the degree of digital transformation, the stronger the operating capacity of enterprises; the improvement of enterprise operating capacity can significantly enhance company performance; digital transformation will strengthen the positive effect of operating capacity on company performance. The study's findings not only reveal the moderating role of digital transformation in the relationship between enterprise operating capacity and company performance but also provide theoretical and empirical evidence for a comprehensive and objective evaluation of the implementation effect of digital transformation. Keywords: digital transformation, operating capacity, company performance, text analysis DOI: 10.7176/EJBM/15-16-01 Publication date:September 30th 202