3 accepted papers
In this paper, we propose several approaches for neutral to Lombard speech conversion. We study in particular the influence of different recurrent neural network architectures where their main hyper-parameters are carefully selected using a bandit-based approach. We also apply the Continuous Wavelet…
In this paper, we propose a speech intelligibility enhancement method for typical in-car applications in noisy environments. While traditional speech enhancement algorithms aim at increasing the Signal to Noise Ratio (SNR), the goal here is to increase intelligibility by applying dedicated voice tra…
In this paper, we propose a novel approach aiming at improving the intelligibility of speech in the context of in-car applications. Speech produced in noisy environments is subject to the Lombard effect which gathers a number of voice transformation effects compared to the speech produced in calm en…