Browsing by Author "Mohammadi, Amir"
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Eigenvoice speaker adaptation with minimal data for statistical speech synthesis systems using a MAP approach and nearest-neighbors
Mohammadi, Amir; Sarfjoo, Seyyed Saeed; Demiroğlu, Cenk (IEEE, 2014-12)Statistical speech synthesis (SSS) systems have the ability to adapt to a target speaker with a couple of minutes of adaptation data. Developing adaptation algorithms to further reduce the number of adaptation utterances ... -
Finding relevant features for statistical speech synthesis adaptation
Bruneau, P.; Parisot, O.; Mohammadi, Amir; Demiroğlu, Cenk; Ghoniem, M.; Tamisier, T. (European Language Resources Association, 2014-05)Statistical speech synthesis (SSS) models typically lie in a very high-dimensional space. They can be used to allow speech synthesis on digital devices, using only few sentences of input by the user. However, the adaptation ... -
Hybrid nearest-neighbor/cluster adaptive training for rapid speaker adaptation in statistical speech synthesis systems
Mohammadi, Amir; Demiroğlu, Cenk (International Speech Communication Association, 2013)Statistical speech synthesis (SSS) approach has become one of the most popular methods in the speech synthesis field. An advantage of the SSS approach is the ability to adapt to a target speaker with a couple of minutes ... -
Nearest neighbor approach in speaker adaptation for HMM-based speech synthesis
Mohammadi, Amir; Demiroğlu, Cenk (IEEE, 2013)Statistical speech synthesis (SSS) approach has become one of the most popular and successful methods in the speech synthesis field. Smooth speech transitions, without the spurious errors that are observed in unit selection ... -
Speaker adaptation with minimal data in statistical speech synthesis systems
Mohammadi, Amir (2014-09)Statistical speech synthesis (SSS) systems have the ability to adapt to a target speaker with a couple of minutes of adaptation data. Developing adaptation algorithms to further reduce the number of adaptation utterances ... -
Spoofing attacks to i-vector based voice verification systems using statistical speech synthesis with additive noise and countermeasure
Özbay, Mustafa Caner; Khodabakhsh, Ali; Mohammadi, Amir; Demiroğlu, Cenk (IEEE, 2016)Even though improvements in the speaker verification (SV) technology with i-vectors increased their real-life deployment, their vulnerability to spoofing attacks is a major concern. Here, we investigated the effectiveness ... -
Spoofing voice verification systems with statistical speech synthesis using limited adaptation data
Khodabakhsh, Ali; Mohammadi, Amir; Demiroğlu, Cenk (Elsevier, 2017-03)State-of-the-art speaker verification systems are vulnerable to spoofing attacks using speech synthesis. To solve the issue, high-performance synthetic speech detectors (SSDs) for attack methods have been proposed recently. ...
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