Automatic pronunciation prediction for text-to-speech synthesis of dialectal arabic in a speech-to-speech translation system

Sankaranarayanan Ananthakrishnan, Stavros Tsakalidis, Rohit Prasad, Prem Natarajan, Aravind Namandi Vembu
2012 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
Text-to-speech synthesis (TTS) is the final stage in the speech-tospeech (S2S) translation pipeline, producing an audible rendition of translated text in the target language. TTS systems typically rely on a lexicon to look up pronunciations for each word in the input text. This is problematic when the target language is dialectal Arabic, because the statistical machine translation (SMT) system usually produces undiacritized text output. Many words in the latter possess multiple pronunciations;
more » ... he correct choice must be inferred from context. In this paper, we present a weakly supervised pronunciation prediction approach for undiacritized dialectal Arabic in S2S systems that leverages automatic speech recognition (ASR) to obtain parallel training data for pronunciation prediction. Additionally, we show that incorporating source language features derived from SMT-generated automatic word alignment further improves automatic pronunciation prediction accuracy.
doi:10.1109/icassp.2012.6289032 dblp:conf/icassp/AnanthakrishnanTPNV12 fatcat:n443k2xijzfxtezn6gkkox7hse