Voice conversion methods based on frequency war** followed by amplitude scaling have
been recently proposed. These methods modify the frequency axis of the source spectrum in …

In this paper, we present novel speaking-aid systems based on one-to-many eigenvoice
conversion (EVC) to enhance three types of alaryngeal speech: esophageal speech …

Recently, deep and/or recurrent neural networks (DNNs/RNNs) have been employed for
voice conversion, and have significantly improved the performance of converted speech …

The voice quality (identity) of singing voices is usually fixed in each singer. To overcome this
limitation and enable singers to freely change their voice quality using signal-processing …

Media conversion of image, text, speech, etc., generally requires a large amount of parallel
data for training a conversion model. Recently, methods for training the model using no or a …

This study proposes a voice conversion-based approach to personalized text-to-speech
(TTS) synthesis. The conversion functions, trained using a small parallel corpus with source …

This paper proposes a novel approach to parallel-data-free and many-to-many voice
conversion (VC). As 1-to-1 conversion has less flexibility, researchers focus on many-to …

This paper proposes a novel approach to construct a Deep Neural Network (DNN) based
voice conversion (VC) system, where DNNs are integrated with speaker eigenspace. The …

This paper focuses on the automatic modification of the degree of articulation (hypo and
hyperarticulation) of an existing standard neutral voice in the framework of HMM-based …

As the annoying blocking or ghost artifacts tend to appear in the conventional compression
approaches either in the JPEG or JPEG2000 standards at low bitrate, the concept of the …