Musical timbre style transfer with diffusion model.

In this work, we focus on solving the problem of timbre transfer in audio samples. The goal is to transfer the source audio's timbre from one instrument to another while retaining as much of the other musical elements as possible, including loudness, pitch, and melody. While image-to-image style transfer has been used for timbre and style transfer in music recording, the current state of the findings is unsatisfactory.

Research and application of surface heat treatment for CO continuous laser ablation of polymeric methyl methacrylate materials.

Based on the influence of a filamentous laser Gaussian heat source and its movement speed on Polymeric Methyl Methacrylate materials (PMMA sheets), the physical model of heat transfer of PMMA materials by CO continuous laser ablation was established. Numerical simulation research on heat transfer in CO continuous laser processing of PMMA sheets was carried out by applying the heat transfer model, and experiments on continuous laser processing of PMMA sheets were conducted on the basis of the numerical simulation results. Theoretical and experimental research indicated that under relevant conditions, when the laser power was 20 W, the maximum surface temperature of PMMA sheet was approximately 520 K, which was higher than the melting temperature of the PMMA material, achieving the transformation of the PMMA material from solid to liquid phase in the laser ablation area.

Personalized movie recommendations based on deep representation learning.

Personalized recommendation is a technical means to help users quickly and efficiently obtain interesting content from massive information. However, the traditional recommendation algorithm is difficult to solve the problem of sparse data and cold-start and does not make reasonable use of the user-item rating matrix. In this article, a personalized recommendation method based on deep belief network (DBN) and softmax regression is proposed to address the issues with traditional recommendation algorithms.