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The term of “World Englishes” describes the current state of English and one of their main characteristics is a large diversity of pronunciation, called accents. In our previous studies, we developed several techniques to realize effective clustering and visualization of the diversity. For this aim, the accent gap between two speakers has to be quantified independently of extra-linguistic factors...
This paper proposes a novel approach to construct a Deep Neural Network (DNN) based voice conversion (VC) system, where DNNs are integrated with speaker eigenspace. The proposed network consists of multiple DNNs and each of them converts input features to features corresponding to a base of eigenspace. Training of these DNNs is achieved with the assistance of Eigenvoice GMM (EVGMM). Experimental evaluations...
In this paper, we present a systematic study of the vulnerability of automatic speaker verification to a diverse range of spoofing attacks. We start with a thorough analysis of the spoofing effects of five speech synthesis and eight voice conversion systems, and the vulnerability of three speaker verification systems under those attacks. We then introduce a number of countermeasures to prevent spoofing...
This paper presents the first version of a speaker verification spoofing and anti-spoofing database, named SAS corpus. The corpus includes nine spoofing techniques, two of which are speech synthesis, and seven are voice conversion. We design two protocols, one for standard speaker verification evaluation, and the other for producing spoofing materials. Hence, they allow the speech synthesis community...
This paper describes a novel approach to construct a mapping function between a given speaker pair using probability density functions (PDF) of matrix variate. In voice conversion studies, two important functions should be realized: 1) precise modeling of both the source and target feature spaces, and 2) construction of a proper transform function between these spaces. Voice conversion based on Gaussian...
Generation process model of fundamental frequency (F0) contours is known to represent global movements of F0's keeping a clear relation with linguistic information of utterances. While HMM-based speech synthesis can generate a good quality of speech, problems, which arise from frame-by-frame processing, are pointed out. These problems are expected to be solved by incorporating the model constraints...
Acoustic event detection systems supporting heterogeneous sets of events face the problem of having to characterize them when they have different acoustic properties (transient, stationary, both, etc.), observing this fact even within the acoustic event itself. Moreover, managing large feature vectors with features characterizing different properties of the signal is always difficult. This paper introduces...
This paper combines a parameter generation algorithm and a model optimization approach with the model-integration-based voice conversion (MIVC). We have proposed probabilistic integration of a joint density model and a speaker model to mitigate a requirement of the parallel corpus in voice conversion (VC) based on Gaussian Mixture Model (GMM). As well as the other VC methods, MIVC also suffers from...
This paper describes an improved method for the framework of structure-to-speech conversion we proposed previously. This framework aims at building a speaking machine by simulating infants' language acquisition. Most of the speech synthesizers take a phoneme sequence as input and convert it to speech sounds, i.e. reading machines. Infants initially acquire speech communication capacity without phonemes...
Voice conversion can be reduced to a problem to find a transformation function between the corresponding speech sequences of two speakers. Perhaps the most voice conversions methods are GMM-based statistical mapping methods. However, the classical GMM-based mapping is frame-to-frame, and cannot take account of the contextual information existing over a speech sequence. It is well known that HMM yields...
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