2026-04-17T06:48:59Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/1246612025-07-17T02:27:32Zcom_2072_1033col_2072_452950

00925njm 22002777a 4500 dc Oller Moreno, Sergio author Moreno Bilbao, M. Asunción author Bonafonte Cávez, Antonio author 2010 This paper deals with the creation of multiple voices from a Hidden Markov Model based speech synthesis system (HTS). More than 150 Catalan synthetic voices were built using Hidden Markov Models (HMM) and speaker adaptation techniques. Training data for building a Speaker-Independent (SI) model were selected from both a general purpose speech synthesis database (FestCat;) and a database design ed for training Automatic Speech Recognition (ASR) systems (Catalan SpeeCon database). The SpeeCon database was also used to adapt the SI model to different speakers. Using an ASR designed database for TTS purposes provided many different amateur voices, with few minutes of recordings not performed in studio conditions. This paper shows how speaker adaptation techniques provide the right tools to generate multiple voices with very few adaptation data. A subjective evaluation was carried out to assess the intelligibility and naturalness of the generated voices as well as the similarity of the adapted voices to both the original speaker and the average voice from the SI model. Peer Reviewed Postprint (published version) Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la parla i del senyal acústic Automatic speech recognition Speech synthesis HMM Adaptation Reconeixement automàtic de la parla Synthesis using speaker adaptation from speech recognition DB