Vocoder-free End-to-End Voice Conversion with Transformer Network

Mel-frequency filter bank (MFB) based approaches have the advantage of learning speech compared to raw spectrum since MFB has less feature size. However, speech generator with MFB approaches require additional vocoder that needs a huge amount of computation expense for training process. The additional pre/post processing such as MFB and vocoder is not essential to convert real human speech to others. It is possible to only use the raw spectrum along with the phase to generate different style of voices with clear pronunciation. In this regard, we propose a fast and effective approach to convert realistic voices using raw spectrum in a parallel manner. Our transformer-based model architecture which does not have any CNN or RNN layers has shown the advantage of learning fast and solved the limitation of sequential computation of conventional RNN. In this paper, we introduce a vocoder-free end-to-end voice conversion method using transformer network. The presented conversion model can also be used in speaker adaptation for speech recognition. Our approach can convert the source voice to a target voice without using MFB and vocoder. We can get an adapted MFB for speech recognition by multiplying the converted magnitude with phase. We perform our voice conversion experiments on TIDIGITS dataset using the metrics such as naturalness, similarity, and clarity with mean opinion score, respectively.Comment: Work in progres

The Light and Period Variations of the Eclipsing Binary BX Draconis

New CCD photometric observations of BX Dra were obtained for 26 nights from 2009 April to 2010 June. The long-term photometric behaviors of the system are presented from detailed studies of the period and light variations, based on the historical data and our new observations. All available light curves display total eclipses at secondary minima and inverse O'Connell effects with Max I fainter than Max II, which are satisfactorily modeled by adding the slightly time-varying hot spot on the primary star. A total of 87 times of minimum light spanning over about 74 yrs, including our 22 timing measurements, were used for ephemeris computations. Detailed analysis of the O-C diagram showed that the orbital period has changed in combinations with an upward parabola and a sinusoidal variation. The continuous period increase with a rate of +5.65 \times 10^-7 d yr^-1 is consistent with that calculated from the Wilson-Devinney synthesis code. It can be interpreted as a mass transfer from the secondary to the primary star at a rate of 2.74 \times 10^-7 M\odot yr^-1, which is one of the largest rates for contact systems. The most likely explanation of the sinusoidal variation with a period of 30.2 yrs and a semi-amplitude of 0.0062 d is a light-traveltime effect due to the existence of a circumbinary object. We suggest that BX Dra is probably a triple system, consisting of a primary star with a spectral type of F0, its secondary component of spectral type F1-2, and an unseen circumbinary object with a minimum mass of M3 = 0.23 M\odot.Comment: 24 pages, including 5 figures and 9 tables, accepted for publication in PAS

Determinants Of Enforcement Action By The Financial Supervisory Service Of Korea From The Perspective Of Audit Firms

In this study, we examine the determinants of enforcement action by the Financial Supervisory Service of Korea from the perspective of audit firms. Enforcement action is an indication of audit failure. Both client- and audit firm-specific factors are involved in its occurrence. Most published studies of enforcement after audit failure focus on client characteristics because details about audit firms from financial statements and information about organizational structure are not publicly available. However, examining the issues surrounding enforcement from the perspective of audit firms may also be valuable in elucidating the potential determinants of audit failure resulting in enforcement action. Utilizing publicly available data from audit firms in South Korea, we identify several audit firm characteristics as determinants of enforcement action. The results of our empirical analysis reveal that the likelihood of audit failure is positively associated with the ratio of accounts receivable to total assets, the ratio of audit fees to total revenue, the ratio of partners to the total number of CPAs, CEO ownership, and age of audit firms. In addition, the likelihood of audit failure is negatively associated with ownership concentration and profitability. These associations are more pronounced in non-affiliated audit firms than affiliated audit firms. Several useful implications for regulators are described for improving audit quality by means of enforcement action

Miuraea migitae, a new record of the order Bangiales (Bangiophyceae, Rhodophyta) from Korea

Abstract We found specimens of foliose Bangiales from the subtidal zone of Udo, Jeju Island, Korea. In molecular analyses of rbcL sequences, these Korean specimens were almost identical to Miuraea migitae from Osaka, Japan. In the morphological comparison, Korean specimens were consistent with habitat, color, and vegetative characteristics with the description of M. migitae. This is the first record of M. migitae outside the type locality and Nagasaki in Japan. This study confirms that new or unrecorded species of the order Bangiales may be discovered from subtidal habitats

Experimental Study on Coordinated Heading Control of Four Vessels Moored Side by Side

A floating type liquefied natural gas (LNG) bunkering terminal has been under development in Korea since 2014; the terminal is designed to receive LNG from an LNG carrier (LNGC) and transfer it to two other LNG bunkering shuttles (LNGBS) simultaneously. The operational feasibility of the LNG loading and unloading processes has been confirmed. When four vessels are moored side by side with mooring ropes and fenders, their positions must be maintained within the designed allowable criteria. In addition, the floating bunkering terminal (FLBT) has its own mooring system, an internal turret with catenary mooring lines and stern tunnel thrusters to maintain its own position and control the vessel heading. In this study, we investigated the operational feasibility of the FLBT during the LNG loading and unloading operations with four vessel mooring configurations and heading controls. A series of model tests was done in the ocean engineering basin of the Korea Research Institute of Ships and Ocean engineering. The motion responses of the four vessels were determined using an optical measurement system, and the tensile loads on ship-to-ship mooring ropes and the compressive loads on ship-to-ship fenders were measured using one-axis load cells. A white noise test was done and the results were compared with the numerical results for the purpose of validation. Then, four combined environmental conditions were presented both without heading control and with several heading control cases. Finally, we determined the available safe bunkering heading ranges taking into account the tensile loads on the mooring ropes

Adversarial Fine-tuning using Generated Respiratory Sound to Address Class Imbalance

Deep generative models have emerged as a promising approach in the medical image domain to address data scarcity. However, their use for sequential data like respiratory sounds is less explored. In this work, we propose a straightforward approach to augment imbalanced respiratory sound data using an audio diffusion model as a conditional neural vocoder. We also demonstrate a simple yet effective adversarial fine-tuning method to align features between the synthetic and real respiratory sound samples to improve respiratory sound classification performance. Our experimental results on the ICBHI dataset demonstrate that the proposed adversarial fine-tuning is effective, while only using the conventional augmentation method shows performance degradation. Moreover, our method outperforms the baseline by 2.24% on the ICBHI Score and improves the accuracy of the minority classes up to 26.58%. For the supplementary material, we provide the code at https://github.com/kaen2891/adversarial_fine-tuning_using_generated_respiratory_sound.Comment: accepted in NeurIPS 2023 Workshop on Deep Generative Models for Health (DGM4H