In this paper, a voice conversion approach that combines two distinct ideas is proposed to improve the converted-voice quality. The first idea is to map spectral features, e.g. discrete cepstrum coefficients (DCC), with segmental Gaussian mixture models (GMMs). That is, a single GMM of a large number of mixture components is replaced here with several voice-content specific GMMs each consisting...

Voice conversion refers to the adaptation of the characteristics of a source speaker's voice to those of a target speaker. Gaussian mixture models (GMM) have been found to be efficient in the voice conversion task. The GMM parameters are estimated from a training set with the goal to minimize the mean squared error (MSE) between the transformed and target vectors. Obviously, the quality of the ...

background: health?related quality of life (hrql) and voice handicap index (vhi) of laryngectomies seem to be relevant regarding voice rehabilitation. the aim of this study is to assess the impact on hrql and vhi of laryngectomies, following voice rehabilitation. materials and methods: a retrospective study done at the ear, nose, and throat department of the emergency county hospital. sixty?fiv...

In this paper, we present a novel voice conversion method using model-based speech synthesis that can be used for some applications where prior knowledge or training data is not available from the source speaker. In the proposed method, training data from a target speaker is used to build a GMM-based speech model and voice conversion is then performed for each utterance from the source speaker ...

In most state-of-the-art voice conversion systems, speech quality of converted utterances is still unsatisfactory. In this paper, STRAIGHT analysis-synthesis framework is used to improve the quality. A smoothed GMM and MAP adaptation is proposed for spectrum conversion to avoid the overly smooth phenomenon in the traditional GMM method. Since frames are processed independently, the GMM based tr...

In the traditional voice conversion, converted speech is generated using statistical parametric models (for example Gaussian mixture model) whose parameters are estimated from parallel training utterances. A well-known problem of the statistical parametric methods is that statistical average in parameter estimation results in the over-smoothing of the speech parameter trajectories, and thus lea...

Absract--Voice conversion involves transformation of speaker characteristics in a speech uttered by a speaker called source speaker to generate a speech having voice characteristics of a desired speaker called the target speaker. Voice conversion is used in many applications namely dubbing, to enhance the quality of the speech, text-to-speech synthesizers, online games, multimedia, music, cross...

Voice conversion (VC) emerged as a significant domain of research in the field speech synthesis recent years due to its emerging application voice-assistive technologies, such automated movie dubbing speech-to-singing conversion, name few. VC deals with vocal style one speaker another while keeping linguistic contents unchanged. Nowadays, generative adversarial network (GAN) models are widely u...

Voice conversion (VC) is an area of speech processing that deals with the conversion of the perceived speaker identity. In other words, the speech signal uttered by a first speaker, the source speaker, is modified to sound as if it was spoken by a second speaker, referred to as the target speaker. The most obvious use case for voice conversion is text-to-speech (TTS) synthesis where VC techniqu...

As one of the techniques enabling individual singers to produce the varieties of voice timbre beyond their own physical constraints, a statistical voice timbre control technique based on the perceived age has been developed. In this technique, the perceived age of a singing voice, which is the age of the singer as perceived by the listener, is used as one of the intuitively understandable measu...