This paper studies the use of transformation-based speaker adaptation in improving the performance of large vocabulary continuous speech recognition systems. We present a formulation of the adaptation procedure that is simpler than existing methods. Our experiments demonstrate that speaker normalization continues to be important even after signi cant amounts of speaker adaptation. An automatic ...

This paper investigates the effect of a transfer functionbased voice transformation on automatic speaker recognition system performance. We focus on increasing the impostor acceptance rate, by modifying the voice of an impostor in order to target a specific speaker. This paper follows previous works where we demonstrate that, if someone has a knowledge on the speaker recognition method used, it...

This paper proposes a constrained stochastic feature transformation algorithm for robust speaker verification. The algorithm computes the feature transformation parameters based on the statistical difference between a test utterance and a composite GMM formed by combining the speaker and background models. The transformation is then used to transform the test utterance to fit the clean speaker ...

A novel speech feature generation-based acoustic model training method for robust speaker-independent speech recognition is proposed. For decades, speaker adaptation methods have been widely used. All of these adaptation methods need adaptation data. However, our proposed method aims to create speaker-independent acoustic models that cover not only known but also unknown speakers. We achieve th...

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

This paper presents a voice transformation algorithm which modifies the speech of a source speaker such that it is perceived as if spoken by a target speaker. A novel method which is based on dynamic programming approach is proposed. The designed system obtains speaker-specific codebooks of line spectral frequencies (LSFs) for both source and target speakers. Those codebooks are used to train a...

When the reference speakers are represented by Gaussian mixture model (GMM), the conventional approach is to accumulate the frame likelihoods over the whole test utterance and compare the results as in speaker identi®cation or apply a threshold as in speaker veri®cation. In this paper we describe a method, where frame likelihoods are transformed into new scores according to some non-linear func...

In this paper we propose bottleneck features of deep neural network for distant-talking speaker identification. The accuracy of distant-talking speaker recognition is significantly degraded under reverberant environment. Feature mapping or feature transformation has been shown efficacy in channel-mismatch speaker recognition. Bottleneck feature derived from multilayer network, which is a nonlin...

Voice transformation is the process of transforming the characteristics of speech uttered by a source speaker, such that a listener would believe the speech was uttered by a target speaker. Training F0 contour generation models for speech synthesis requires a large corpus of speech. If it were possible to adapt the F0 contour of one speaker to sound like that of another speaker, using a small, ...

Whispered speech is an alternative speech production mode from neutral speech, which is used by talkers intentionally in natural conversational scenarios to protect privacy and to avoid certain content from being overheard or made public. Due to the profound differences between whispered and neutral speech in vocal excitation and vocal tract function, the performance of automatic speaker identi...