Recurrent DNNs and its Ensembles on the TIMIT Phone Recognition Task

In this paper, we have investigated recurrent deep neural networks (DNNs) in combination with regularization techniques as dropout, zoneout, and regularization post-layer. As a benchmark, we chose the TIMIT phone recognition task due to its popularity and broad availability in the community. It also simulates a low-resource scenario that is helpful in minor languages. Also, we prefer the phone recognition task because it is much more sensitive to an acoustic model quality than a large vocabulary continuous speech recognition task. In recent years, recurrent DNNs pushed the error rates in automatic speech recognition down. But, there was no clear winner in proposed architectures. The dropout was used as the regularization technique in most cases, but combination with other regularization techniques together with model ensembles was omitted. However, just an ensemble of recurrent DNNs performed best and achieved an average phone error rate from 10 experiments 14.84 % (minimum 14.69 %) on core test set that is slightly lower then the best-published PER to date, according to our knowledge. Finally, in contrast of the most papers, we published the open-source scripts to easily replicate the results and to help continue the development.Comment: Submitted to SPECOM 2018, 20th International Conference on Speech and Compute

Geometric structures on the tangent bundle of the Einstein spacetime

We describe conditions under which a spacetime connection and a scaled Lorentzian metric define natural symplectic and Poisson structures on the tangent bundle of the Einstein spacetime

How Anti-Introspectionist is Theory Theory?

Introspection is often seen as criterion to distinguish between theory theory (TT) and simulation theory (ST). Many empirical arguments against ST rely upon the thesis that ST is introspectionist and that it presupposes the Cartesian dictum that the mind is transparent to itself. According to Perner 1999 the capacity to introspect is so important for ST that it can be seen as the criterion that distinguishes ST from TT: "These two positions and their sub-varieties differ as to whether they presuppose or explain the ability to introspect. Theory theory is extremely anti-introspectionist. Traditional simulation is based on the ability to introspect one's own mental states." (Perner 1999

The posssibilities of railway transport utilizing as a backbone network of integrated passenger transport systems

The aspects of utilizing of railway transport as a backbone network of integrated passenger transport systems are solved in the contribution. The basic requirements on this railway transport service are specified in the contribution. The main attention is focused on creating of line structure of the integrated transport systems. The location of interchange points is also accented in the contribution. The theoretical presumptions are also illustrated in the way of convenient practical examples