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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 the scope of practical applications of SC due...
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 the simplest choice among all techniques...
The objective of this paper is to implement SPEEX decoding on ARM microprocessor. SPEEX [1] is based on the voice compression algorithm technology of Code Excited Linear Prediction (CELP) [2], which can effectively compress voice and retain the integrity of speech. For hardware part, we give up the high-cost, high-power consumption digital signal processor, and select the STM32 series ARM microprocessor...
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