This paper proposes speaking-aid systems based on one-to-many eigenvoice conversion (EVC) for enhancing three types of alaryngeal speech: esophageal speech; electrolaryngeal speech; and body-conducted silent electrolaryngeal speech. Although alaryngeal speech allows laryngectomees to utter speech sounds, it suffers from lack of naturalness and speaker individuality. To improve the sound quality...

A cross-lingual voice conversion system aims at modifying the timbral structure of recorded sentences from a source speaker, in order to obtain processed sentences which are perceived as the same sentences uttered by a target speaker. This work presents the cross-lingual voice conversion problem as a network of related sub-problems and discuss several techniques for solving each of these sub-pr...

Voice conversion involves transforming segments of speech from a source speaker to make them to be perceived as if spoken by a target speaker. Generally, this process involves the estimation of vocal tract parameters and an excitation signal that match the target speaker. The work presented here proposes an algorithm for estimating the excitation residuals of the target speaker using a weighted...

This paper describes an evaluation of many-to-one voice conversion (VC) algorithmsconverting an arbitraryspeaker’s voice into a particular target speaker’s voice. These algorithmseffectively generatea conversionmodel for a new source speaker using multiple parallel data sets of many pre-storedsource speakers and the single target speaker. We conducted experimental evaluations for demonstrating ...

Emotional voice conversion aims at converting speech from one emotion state to another. This paper proposes to model timbre and prosody features using a deep bidirectional long shortterm memory (DBLSTM) for emotional voice conversion. A continuous wavelet transform (CWT) representation of fundamental frequency (F0) and energy contour are used for prosody modeling. Specifically, we use CWT to de...

Most of the current voice conversion systems model the joint density of source and target features using a Gaussian mixture model. An inherent property of this approach is that the source and target features have to be properly aligned for the training. It is intuitively clear that the accuracy of the alignment has some effect on the conversion quality but this issue has not been thoroughly stu...

Emotional Voice Conversion (EVC) technology aims to transfer emotional state in speech while keeping the linguistic information and speaker identity unchanged. Prior studies on EVC have been limited perform conversion for a specific or predefined set of multiple speakers seen training stage. When encountering arbitrary that may be unseen during (outside used training), existing methods capabili...

The objective of voice conversion system is to formulate the mapping function which can transform the source speaker characteristics to that of the target speaker. In this paper, we propose the General Regression Neural Network (GRNN) based model for voice conversion. It is a single pass learning network that makes the training procedure fast and comparatively less time consuming. The proposed ...