@article {608, title = {Language-Independent Acoustic Cloning of HTS Voices: An Objective Evaluation}, journal = {Lecture Notes in Artificial Intelligence LNCS/LNAI}, volume = {10007}, year = {2016}, month = {11/2016}, pages = {54-63}, abstract = {In a previous work we presented a method to combine the acoustic characteristics of a speech synthesis model with the linguistic characteristics of another one. This paper presents a more extensive evaluation of the method when applied to cross-lingual adaptation. A large number of voices from a database in Spanish are adapted to Basque, Catalan, English and Galician. Using a state-of-the-art speaker identification system, we show that the proposed method captures the identity of the target speakers almost as well as standard intra-lingual adaptation techniques.}, keywords = {Cross-lingual speaker adaptation, HMM-based speech synthesis, I-vectors, Multilingual synthesis, Polyglot synthesis, Speaker identification, Voice cloning}, issn = {0302-9743}, doi = {10.1007/978-3-319-49169-1_6}, url = {http://link.springer.com/chapter/10.1007/978-3-319-49169-1_6}, author = {C. Magari{\~n}os and D. Erro and Paula L{\'o}pez Otero and Eduardo Rodr{\'\i}guez Banga} }