Efficient Model for Numerical Text-To-Speech Synthesis System in Marathi, Hindi and English Languages

G. D. Ramteke, R. J. Ramteke
2017 International Journal of Image Graphics and Signal Processing  
The paper proposes a numerical TTSsynthesis system in Marathi, Hindi and English languages. The system is in audible forms based on the sounds generated from several numeric units. A hybrid technique is newly launched for a numerical text-to-speech technology. The technique is divided into different phases. These numerical phases include pre-processing, numeric unit detection, numeric and speech unit matching; speech unit concatenation and speech generation. In order to enhance the syntactic
more » ... eration of audible forms in three languages, two discipline tests were performed. The prosodic test has been obtained for evaluating on the statistical readings. Overall quality issue (OQI) test is a subjective test which is performed by various persons who are aware of three mentioned languages. On the basis of two distinct parameters of OQI test, all scores are positively provided. Initial parameter compromises with listening quality. The second parameter, awareness rate improves a level of the intelligibility. The ultimate satisfactory results of artificial sound generation in three unrelated languages were touched to humankind voice. II. EARLIER TTS-WORK Text-To-Speech (TTS) system is a branch of the speech research field. A number of researchers have been working on the TTS-technology since last few decades. William A. Ainsworth [1] developed the system for conversion English text into spoken form using a small amount of data. The performance of English TTS-system was achieved because most of the longer words in English are uttered on the basis of rules. The results of the system appeared to be encouraging. Bhuvana Narasimhan et al. [5] have proposed the Hindi TTS-model for schwa-deletion using concatenative technique. There were different issues of schwa pronunciation in Hindi: every schwa following the consonant is not produced within the word; the schwa deletion can be blocked for the presence of a morpheme boundary in multimorphemic words. Pamela Chaudhury et al. [9] dealt with the model for Telugu conversion into spoken form. The results of Telugu TTS-system were good for intelligibility and fair for voice quality. But in 2012, Lakshmi Sahu et al. [17] have presented the corpusdriven TTS-system based on concatenative synthesis method for two Indian languages: Hindi and Telugu. The system has been enriched with a couple of voices (male and female). The samples took from North India for Hindi languages and another from South India for Telugu language. Soumya Priyadarsini Panda et al. [22] have dealt with the conversion natural language text into a spoken waveform or artificial production of speech for Odia, Bengali and Hindi languages. The model was based on concatenative speech synthesis algorithm. It worked well for most of the characters in the three Indian languages. Saleh M. Abu-Saud [26] has implemented the ILA-Talk system which was used for the multilingual TTS-system. It composed of the analysis phase which was categorized into two major cases: Case 1 was related to a number of training examples in the number words selected from the dictionary. Case 2 was concerned with the length of the number of characters in the training example. In the previous work [28] , we have developed the TTSwork based on phonetic and voice processing in Marathi and Hindi language. The system was based on unit selection process using synthesis-by-rules for converting Devnagari phonetics into synthesized speech. The model was achieved to understand the phonetics without reading it. In this paper, the numerical TTS-work for Marathi, Hindi and English languages has been extended.
doi:10.5815/ijigsp.2017.03.01 fatcat:gf2uagwp3nbnpc4p5xrzsilz7a