Yi-Chiao Wu

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We propose a flexible framework for spectral conversion (SC) that facilitates training with unaligned corpora. Many SC frameworks require parallel corpora, phonetic alignments, or explicit frame-wise correspondence for learning conversion functions or for synthesizing a target spectrum with the aid of alignments. However, these requirements gravely limit(More)
This paper describes a novel exemplar-based spectral conversion (SC) system developed by the AST (Academia Sinica, Taipei) team for the 2016 voice conversion challenge (vcc2016). The key feature of our system is that it integrates the locally linear embedding (LLE) algorithm, a manifold learning algorithm that has been successfully applied for the(More)
Building a voice conversion (VC) system from non-parallel speech corpora is challenging but highly valuable in real application scenarios. In most situations, the source and the target speakers do not repeat the same texts or they may even speak different languages. In this case, one possible, although indirect, solution is to build a generative model for(More)
This paper presents a novel postfiltering approach based on the locally linear embedding (LLE) algorithm for speech enchantment (SE). The aim of the proposed LLE-based postfiltering approach is to further remove the residual noise components from the SE-processed speech signals through a spectral conversion process, thereby increasing the signal-to-noise(More)
In this paper, we propose a dictionary update method for Non-negative Matrix Factorization (NMF) with high dimensional data in a spectral conversion (SC) task. Voice conversion has been widely studied due to its potential applications such as personalized speech synthesis and speech enhancement. Exemplar-based NMF (ENMF) emerges as an effective and probably(More)
Intelligent human-robot interface helps a mobile robot to extract external information and interact with a user. User identification information allows a robot to generate appropriate behaviors and make personalized human-robot interaction (PHRI) more natural and safe. Most of service robots move around in various application settings, and biometric(More)
This paper presents a novel difference compensation postfiltering approach based on the locally linear embedding (LLE) algorithm for speech enhancement (SE). The main goal of the proposed post-filtering approach is to further suppress residual noises in SE-processed signals to attain improved speech quality and intelligibility. The proposed system can be(More)
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