A corpus-based concatenative speech synthesis system for Turkish

Speech synthesis is the process of converting written text into machine-generated synthetic speech. Concatenative speech synthesis systems form utterances by concatenating pre-recorded speech units. Corpus-based methods use a large inventory to select the units to be concatenated. In this paper, we design and develop an intelligible and natural sounding corpus-based concatenative speech synthesis system for the Turkish language. The implemented system contains a front-end comprised of text analysis, ,phonetic analysis, and optional use of transplanted prosody. The unit selection algorithm is based on commonly used Viterbi decoding algorithm of the best-path in the network of the speech units using spectral discontinuity and prosodic mismatch objective cost measures. The back-end is the speech waveform generation based on the harmonic coding of speech and overlap-and-add mechanism. Harmonic coding enabled us to compress the unit inventory size by a factor of three. In this study, a Turkish phoneme set has been designed and a pronunciation lexicon for root words has been constructed. The importance of prosody in unit selection has been investigated by using transplanted prosody. A Turkish Diagnostic Rhyme Test (DRT) word list that can be used to evaluate the intelligibility of Turkish Text-to-Speech (TTS) systems has been compiled. Several experiments have been performed to evaluate the quality of the synthesized speech and we obtained 4-2 Mean Opinion Score (MOS) in the listening tests for our system, which is the first unit selection based system published for Turkish.