Abstract

synthesis the input text is converted into such form that the low level synthesizer can produce the output speech. The three basic methods for low level synthesis are the formant, concatenative, and articulatory synthesis. The formant synthesis is based on the modeling of the resonances in the vocal tract and is perhaps the most commonly used during the last decades. However, the concatenative synthesis which is based on playing pre-recorded samples from natural speech is becoming more popular. The most accurate method is articulatory synthesis which models the human speech production system directly, but it is also the most difficult approach. Since the quality of synthetic speech is improving steadily, the application field is also expanding rapidly. Different methodologies for Concatenative Synthesis are there like TDPSOLA, PSOLA, MBROLA and ESNOLA. The Nepali text to speech synthesis system described here is based on Concatenative technique that uses Epoch Synchronous Non Overlap Add Method (ESNOLA) where the speech signal dictionary is created by cutting the pre-recorded natural speech such that the speech segments begin and ends all at the positive zero crossing to eliminate mismatch or distortion during concatenation. The system uses partneme as the smallest signal units for concatenation. ESNOLA technique provides the complete control on implementation of intonation and prosody [2, 10]. It allows judicious selection of signal segment so that smaller fundamental parts of the phonemes may be used as units reducing both the number and the size of the signal elements in the dictionary. Further the methodology of concatenation provides adequate processing for proper matching between different segments during concatenation. The use of special type of basic signal segment makes the size of signal dictionary very small so that there is a possibility of its implementation in low-cost, general-purpose electronic devices.

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