This paper deals with pitch estimation of spoken Devnagari vowels from the original speech signals. Devnagari vowels are playing the vital role in pronunciation of any word. Each vowel is classified as starting, middle and end according to the duration of occurrences in the word. The Devnagari script having 12-vowels and 34-consonants are used in some Indian language like Marathi. The Devnagari vowels are categorised into 5-types such as short vowels, long vowels, conjunct vowels, nasal vowel and visarg vowel. The Pitch frequency is estimated from the features of speech signals via pitch detection algorithm through autocorrelation and cepstral methods. These vowels are recorded through PRAAT tools with noisy environment. The pitch estimation of original pitch frequency hasbeen calculated in statistical manner (Mean and standard deviation). The implementation, experiments and result discussions are also existence.These results which have been appropriate match with both techniques.
Abstract-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 generation 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.
This paper describes pitch estimation of Marathi spoken numbers which are extracted the features from various speech signals. The speech frequencies of Marathi spoken numbers are acquired by various male and female speakers. The pitch frequencies are normalized using PRAAT tool. The pitch contours are compared with pitch detector. The autocorrelation and cepstral methods are used to estimate speech frequency. Pitch detection is calculated by statistical methods and similarity is measured by Euclidian distance. The pitch frequency results found to be satisfactory. The average mean of frequency varies from 1.48 to 2.03 and standard deviation varies from 0.84 to 1.38 in Hz.
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