In this paper, several experiments on F0 transformation within the voice conversion framework are presented. The conversion system is based on a probabilistic transformation of line spectral frequencies and residual prediction. Three probabilistic methods of instantaneous F0 transformation are described and compared. Moreover, a new modification of inter-speaker residual prediction is proposed ...

This study combines a Gaussian mixture model support vector machine (GMM-SVM) system with a nonlinear feature transformation, discriminatively trained to extract speaker specific features from MFCCs. Separation of the speaker information component and non-speaker related information in the speech signal is accomplished using a regularized siamese deep network (RSDN). RSDN learns a hidden repres...

In conventional Gaussian Mixture Model – Universal Background Model (GMM-UBM) text-independent speaker verification applications, the discriminability between speaker models and the universal background model (UBM) is crucial to system’s performance. In this paper, we present a method based on heteroscedastic linear discriminant analysis (HLDA) that can enhance the discriminability between spea...

This paper proposes a novel speaker-independent (SI) modeling for spontaneous speech data from multiple speakers. The SI acoustic model parameters are estimated by individual training for inter-speaker variability and for intraspeaker phonetically related variation in order to obtain a more accurate acoustic model. The linear transformation technique is used for the speaker normalization to ext...

Dysarthria is a speech motor disorder usually resulting in a substantive decrease in speech intelligibility by the general population. In this study, we have significantly improved the intelligibility of dysarthric vowels of one speaker from 48% to 54%, as evaluated by a vowel identification task using 64 CVC stimuli judged by 24 listeners. Improvement was obtained by transforming the vowels of...

Original scientific paper Confidence measures are expected to give a measure of reliability on the result of a speech/speaker recognition system. Most commonly used confidence measures are based on posterior word or phoneme probabilities which can be obtained from the output of the recognizer. In this paper we introduced a linear interpretation of posterior probability based confidence measure ...

Remote speaker verification services typically rely on the system to have access to the users recordings, or features derived from them, and also a model of the users voice. This conventional scheme raises several privacy concerns. In this work, we address this privacy problem in the context of a speaker verification system using a factor analysis based front-end extractor, the so-called i-vect...

Speaker adaptation techniques have emerged as very effective and practical methods to improve ASR performance on a test speaker with only limited speech data from the speaker. We explore the use of adaptation techniques on a new Voicemail database and present some theoretical extensions of the Cluster Transformation (CT) technique. Our experiments on 40 hours of voicemail data and four clusters...

In the past few years state-of-the-art text-dependent speaker verification technology has improved significantly in terms of the ability to accept target speakers and reject imposters. As a result, the use of speaker verification systems for real world security is increasing. Real world usage of speaker verification technology raises the issue of spoofing attacks. As part of our efforts for dev...