Acoustic echo and noise canceller for personal hands-free video IP phone

This paper presents implementation and evaluation of a proposed acoustic echo and noise canceller (AENC) for videotelephony-enabled personal hands-free Internet protocol (IP) phones. This canceller has the following features: noise-robust performance, low processing delay, and low computational complexity. The AENC employs an adaptive digital filter (ADF) and noise reduction (NR) methods that can effectively eliminate undesired acoustic echo and background noise included in a microphone signal even in a noisy environment. The ADF method uses the step-size control approach according to the level of disturbance such as background noise; it can minimize the effect of disturbance in a noisy environment. The NR method estimates the noise level under an assumption that the noise amplitude spectrum is constant in a short period, which cannot be applied to the amplitude spectrum of speech. In addition, this paper presents the method for decreasing the computational complexity of the ADF process without increasing the processing delay to make the processing suitable for real-time implementation. The experimental results demonstrate that the proposed AENC suppresses echo and noise sufficiently in a noisy environment; thus, resulting in natural-sounding speech

Low Temperature Age-Hardening of Al-12mass % Zn-0.5mass % Cu Alloy

Effect of addition of a small amount of copper to Al- 12mass % Zn binary alloy on the process of low temperature aging is studied by hardness test and transmission electron microscopy. Age hardening rate after quenching from various temperatures is slowed down by addition of 0.5mass % copper to the binary alloy. The hardness obtained after long aging, however, is increased a little by the addition of copper. The extent of soft surface layer formed by aging in the copper-added alloy is nearly equal to that obtained in the binary alloy

Clusters in Low-Concentrated Al-Mg Alloy

The state above the solubility temperature of GP zones of Al-3mass % Mg alloy, which has a tendency for precipitation and preprecipitation at low temperature, was studied by resistivity measurement. Homogenization treatment at high temperature reduced Mg atoms in the surface layer. After quenching from 623K, the specimen was annealed sequentially at various temperatures above the GP zone solvus. The stationary resistivity obtained in annealing at a temperature was the same irrespective of the starting state and increased with decreasing annealing temperature. No precipitation was observed in the annealing. The results are not in favor of the segregation of Mg atoms to the dislocation loops but of the short range clustering

Toward Unlimited Self-Learning Monte Carlo with Annealing Process Using VAE's Implicit Isometricity

Self-learning Monte Carlo (SLMC) methods are recently proposed to accelerate Markov chain Monte Carlo (MCMC) methods by using a machine learning model.With generative models having latent variables, SLMC methods realize efficient Monte Carlo updates with less autocorrelation. However, SLMC methods are difficult to directly apply to multimodal distributions for which training data are difficult to obtain. In this paper, we propose a novel SLMC method called the ``annealing VAE-SLMC" to drastically expand the range of applications. Our VAE-SLMC utilizes a variational autoencoder (VAE) as a generative model to make efficient parallel proposals independent of any previous state by applying the theoretically derived implicit isometricity of the VAE. We combine an adaptive annealing process to the VAE-SLMC, making our method applicable to the cases where obtaining unbiased training data is difficult in practical sense due to slow mixing. We also propose a parallel annealing process and an exchange process between chains to make the annealing operation more precise and efficient. Experiments validate that our method can proficiently obtain unbiased samples from multiple multimodal toy distributions and practical multimodal posterior distributions, which is difficult to achieve with the existing SLMC methods.Comment: 24 pages,12 figure