不需平行語料而基於共振峰與線頻譜頻率映對之語者特質轉換系統

A Voice Conversion System based on Formant and LSF Mapping without Using Parallel Corpus

語者特質轉換的研究已有廣泛的運用，早期使用的向量量化碼本對照，與目前被廣為使用的高斯混合模型，都會使用經動態時軸校準的平行對應語句作訓練。近年來已有減少使用訓練語料與使用非平行句的語料進行語者特質轉換的方法。本論文提出一個不採用平行句的訓練方法，而依據語者音節共振峰映對，並結合線頻譜頻率映對，進行語者特質轉換。

Voice conversion has been used in many applications. The methods based on vector quantization codebook and Gaussian mixture models need dynamic time warping on parallel sentence corpus for generating mapping functions. Recent study tries to use less training data, and even without parallel sentence corpus. This paper presents a voice conversion method without using parallel sentence corpus. It applies the formant mapping and line spectral frequency mapping to accomplish a voice conversion system.