This paper presents a new voice conversion algorithm. This algorithm allows voices to be adapted using a small amount of adaptation data. Only a few short adaptation units (phonemes or short words) are needed. The voice conversion is performed using a time-variant digital filter, topological feature maps and a map of filter coefficients. The filter coefficients of the time-variant filter are se...

This paper presents a novel technique for voice conversion by solving a two-factor task using bilinear models. The spectral content of the speech represented as line spectral frequencies is separated into so-called style and content parameterizations using a framework proposed in [1]. This formulation of the voice conversion problem in terms of style and content offers a flexible representation...

Voice conversion is a process which modifies speech produced by one speaker so that it sounds as if it is uttered by another speaker. In this paper a new voice conversion system is presented. The system requires parallel training data. By using linear prediction analysis, speech is described with line spectral frequencies and the corresponding residua. LSFs are converted together with instantan...

This paper presents a new voice conversion algorithm. This algorithm allows voices to be adapted using a small amount of adaptation data. Only a few short adaptation units (phonemes or short words) are needed. The voice conversion is performed using a time-variant digital filter, topological feature maps and a map of filter coefficients. The filter coefficients of the time-variant filter are se...

So far, all conventional voice conversion approaches are text-dependent, i.e., they need equivalent training utterances of source and target speaker. Since several recently proposed applications call for renouncing this requirement, in this paper, we present an algorithm which finds corresponding time frames within text-independent training data. The performance of this algorithm is tested by m...

Voice conversion is a process where the essence of speaker’s identity seamlessly transferred to another speaker, all while preserving content their speech. This usage accomplished using algorithms that blend speech processing techniques, such as analysis, speaker classification, and vocoding. The cutting-edge voice technology characterized by deep neural networks effectively separate from lingu...