Voice Conversion Based on Cross-Domain Features Using Variational Auto Encoders

An effective approach to non-parallel voice conversion (VC) is to utilize deep neural networks (DNNs), specifically variational auto encoders (VAEs), to model the latent structure of speech in an unsupervised manner. A previous study has confirmed the ef- fectiveness of VAE using the STRAIGHT spectra for VC. How- ever, VAE using other types of spectral features such as mel- cepstral coefficients (MCCs), which are related to human per- ception and have been widely used in VC, have not been prop- erly investigated. Instead of using one specific type of spectral feature, it is expected that VAE may benefit from using multi- ple types of spectral features simultaneously, thereby improving the capability of VAE for VC. To this end, we propose a novel VAE framework (called cross-domain VAE, CDVAE) for VC. Specifically, the proposed framework utilizes both STRAIGHT spectra and MCCs by explicitly regularizing multiple objectives in order to constrain the behavior of the learned encoder and de- coder. Experimental results demonstrate that the proposed CD- VAE framework outperforms the conventional VAE framework in terms of subjective tests.Comment: Accepted to ISCSLP 201

The Role of Input in Acquisition of Tone Sandhi Rules in Mandarin Chinese

PACLIC 20 / Wuhan, China / 1-3 November, 200

Do Degradation of Urban Greenery and Increasing Land Prices Often Come along with Urbanization?

In the wake of urbanization, driven by a variety of individual and socio-economic merits, human’s basic residential needs and standard of living may be compromised in the urban areas, as the population agglomerates. However, the knowledge of the associations of urbanization with urban greenery and residential land prices is still in the pursuing process. This empirical research aims to contribute whether the degradation of essential living conditions is a trade-off for the pursued urban life. Hence, Taiwan is selected as the case to analyze the associated relations primarily between 1976 and 2016. The research methods involve descriptive statistics, the panel data analysis, and the cluster analysis. The panel data analysis demonstrates that degraded urban greenery and increasing residential land prices came along with the urbanization in Taiwan between 2001 and 2016. Policy implications include rethinking of the building coverage rate for renewed buildings for more plant-friendly ground, the adoption of building setback policy for more accessible mid-air mini-parks, and avoiding residential units as an investment commodity

Improving Collaborative Drawing using HTML5

This research looks into improving online web-based collaborative drawing using HTML5. Although many systems have been developed over a number of years, none of the applications released have been satisfactory for many artists; the core drawing experience was too different from a stand-alone drawing applications. Stand-alone drawing applications have better freedom of control with functions like undo and allow artists to work efficiently with hotkeys. The advent of the HTML5 Canvas Element and Websockets in recent browsers has provided new opportunities for collaborative online interaction. This research used an incremental development approach to build a prototype HTML5 drawing application providing new functionality for online collaborative drawing. The project was supported by two experienced artists throughout investigation, design, implementation and testing. The project artists helped validate design decisions and evaluate the implementation. As a result, a robust HTML5 collaborative drawing application was built. The prototype contains core drawing functionality that existing applications did not. Features include: undo and redo, free canvas transformation, complex hotkey interaction, custom canvas size support, colour wheel, and layers. All these features work smoothly in a fully synchronized network environment under a client-server model. The collaboration system uses an authoritative server structure with local prediction and re-synchronization to hide latency. Although the result is only a prototype, the evaluations from the project artists were very positive. Once more functionality targeted towards social interaction is built, the prototype will be ready for mass public testing. Although there are some issues caused by the immaturity of HTML5 technology, this project affirms its capability for collaborative web applications

Life Tables of Bactrocera cucurbitae (Coquillett) (Diptera: Tephritidae): with a Mathematical Invalidation for Applying the Jackknife Technique to the Net Reproductive Rate

Life table data for the melon fly, Bactrocera cucurbitae (Coquillett), reared on cucumber (Cucumis sativus L.) were collected under laboratory and simulated field conditions. Means and standard errors of life table parameters were estimated for two replicates using the jackknife technique. At 25ºC, the intrinsic rates of increase (_r_) found for the two replicates were 0.1354 and 0.1002 day-1, and the net reproductive rates (_R_~0~) were 206.3 and 66.0 offspring, respectively. When the cucumbers kept under simulated field conditions were covered with leaves, the _r_ and _R_~0~ for the two replicates were 0.0935 and 0.0909 day-1, 17.5 and 11.4 offspring, respectively. However, when similar cucumbers were left uncovered, the _r_ and _R_~0~ for the two replicates were 0.1043 and 0.0904 day-1, and 27.7 and 10.1 offspring, respectively. Our results revealed that considerable variability between replicates in both laboratory and field conditions is possible; this variability should be taken into consideration in data collection and application of life tables. Mathematical analysis has demonstrated that applying the jackknife technique results in unrealistic pseudo-_R_~0~ and overestimation of its variance. We suggest that the jackknife technique should not be used for the estimation of variability of _R_~0~

Robust Sufficient Dimension Reduction via α\alpha-Distance Covariance

We introduce a novel sufficient dimension-reduction (SDR) method which is robust against outliers using $\alpha$-distance covariance (dCov) in dimension-reduction problems. Under very mild conditions on the predictors, the central subspace is effectively estimated and model-free advantage without estimating link function based on the projection on the Stiefel manifold. We establish the convergence property of the proposed estimation under some regularity conditions. We compare the performance of our method with existing SDR methods by simulation and real data analysis and show that our algorithm improves the computational efficiency and effectiveness

Time-moving Metaphors and Ego-moving Metaphors: Which Is Better Comprehended by Taiwanese?

PACLIC 21 / Seoul National University, Seoul, Korea / November 1-3, 200