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Merlijn Blaauw and Jordi Bonada
We recently presented a new model for singing synthesis based on a modified version of the WaveNet architecture. Instead of modeling raw waveform, we model features produced by a parametric vocoder that separates the influence of pitch and timbre. This a...
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Elie Azeraf, Emmanuel Monfrini and Wojciech Pieczynski
Practitioners have used hidden Markov models (HMMs) in different problems for about sixty years. Moreover, conditional random fields (CRFs) are an alternative to HMMs and appear in the literature as different and somewhat concurrent models. We propose tw...
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Zhe Yang, Yi Huang, Yaqin Chen, Xiaoting Wu, Junlan Feng and Chao Deng
Controllable Text Generation (CTG) aims to modify the output of a Language Model (LM) to meet specific constraints. For example, in a customer service conversation, responses from the agent should ideally be soothing and address the user?s dissatisfactio...
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L. G. Divyanth, D. S. Guru, Peeyush Soni, Rajendra Machavaram, Mohammad Nadimi and Jitendra Paliwal
Applications of deep-learning models in machine visions for crop/weed identification have remarkably upgraded the authenticity of precise weed management. However, compelling data are required to obtain the desired result from this highly data-driven ope...
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Celal Cakiroglu
The current study offers a data-driven methodology to predict the ultimate strain and compressive strength of concrete reinforced by aramid FRP wraps. An experimental database was collected from the literature, on which seven different machine learning (...
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Yajing Xu, Haitao Yang, Si Li, Xinyi Wang and Mingfei Cheng
Visual relationship detection (VRD), a challenging task in the image understanding, suffers from vague connection between relationship patterns and visual appearance. This issue is caused by the high diversity of relationship-independent visual appearanc...
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Wang Xi, Guillaume Devineau, Fabien Moutarde and Jie Yang
Generative models for images, audio, text, and other low-dimension data have achieved great success in recent years. Generating artificial human movements can also be useful for many applications, including improvement of data augmentation methods for hu...
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Huiyuan Wang, Xiaojun Wu, Zirui Wang, Yukun Hao, Chengpeng Hao, Xinyi He and Qiao Hu
Dolphin signals are effective carriers for underwater covert detection and communication. However, the environmental and cost constraints terribly limit the amount of data available in dolphin signal datasets are often limited. Meanwhile, due to the low ...
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Calimanut-Ionut Cira, Martin Kada, Miguel-Ángel Manso-Callejo, Ramón Alcarria and Borja Bordel Sanchez
The road surface area extraction task is generally carried out via semantic segmentation over remotely-sensed imagery. However, this supervised learning task is often costly as it requires remote sensing images labelled at the pixel level, and the result...
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Hyeon Kang, Jang-Sik Park, Kook Cho and Do-Young Kang
Conventional data augmentation (DA) techniques, which have been used to improve the performance of predictive models with a lack of balanced training data sets, entail an effort to define the proper repeating operation (e.g., rotation and mirroring) acco...
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Sandi Baressi ?egota, Vedran Mrzljak, Nikola Andelic, Igor Poljak and Zlatan Car
Machine learning applications have demonstrated the potential to generate precise models in a wide variety of fields, including marine applications. Still, the main issue with ML-based methods is the need for large amounts of data, which may be impractic...
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