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The aim of this project was to develop and implement an English languageText-to-Speech synthesis system. This involved a study of mechanisms of humanspeech production, a review of techniques in speech synthesis, and analysis oftests used to evaluate the effectiveness of synthesized speech. It wasdetermined that a diphone synthesis system was the most effective choice forthe scope of this project. A method of automatically identifying and extractingdiphones from prompted speech was designed, allowing for the creation of adiphone database by a speaker in less than 40 minutes. CMUdict was used todetermine the pronunciation of known words. A system for smoothing thetransitions between diphone recordings was designed and implemented. CMUdictwas then used to train a maximum-likelihood prediction system to determine thecorrect pronunciation of unknown English language alphabetic words. Then, aPart Of Speech tagger was designed to find the lexical class of words within asentence.  A method of altering the pitch, duration, and volume of the produced voiceover time was designed, being a combination of the TD-PSOLA algorithm and anovel approach referred to as Unvoiced Speech Duration Shifting. This minimisesdistortion of the voice when shifting the pitch or duration, while maximisingcomputational efficiency by operating in the time domain. This approach wasused to add correct lexical stress to vowels within words. A text tokenisationsystem was developed to handle arbitrary text input, allowing pronunciation ofnumerical input tokens and use of appropriate pauses for punctuation. Methodsfor further improving sentence level speech naturalness were discussed.Finally, the system was tested with listeners for its intelligibility andnaturalness.

Techniques and Challenges in Speech Synthesis