Guner, EkremDemiroğlu, Cenk2016-07-262016-07-2620122165-0608http://hdl.handle.net/10679/4279https://doi.org/10.1109/SIU.2012.6204745Due to copyright restrictions, the access to the full text of this article is only available via subscription.The HMM-based TTS (HTS) approach has been increasingly getting more attention from the TTS research community. One of the advantage is the lack of spurious errors that are observed in the unit selection scheme. Another advantage of the HTS system is the small memory footprint requirement which makes it attractive for embedded devices. Here, we propose a novel hybrid statistical unit selection TTS system for agglutinative languages that aims at improving the quality of the baseline HTS system while keeping the memory footprint small. The intelligibility and quality scores of the baseline system are comparable to the MOS scores of English reported in the Blizzard Challenge tests. Listeners preferred the hybrid system over the baseline system in the A/B preference tests.turrestrictedAccessconferenceObject1410.1109/SIU.2012.6204745Hidden Markov modelsNatural language processingSpeech intelligibilitySpeech synthesis2-s2.0-84863465087