Teza doctorat (pdf) - Universitatea Tehnică
Teza doctorat (pdf) - Universitatea Tehnică Teza doctorat (pdf) - Universitatea Tehnică
O. Buza, G. Toderean, J. Domokos, A. Zs. Bodo, Construction of a Syllable-Based Text-To-Speech System for Romanian Also a region of voiced discontinuity corresponding to intermediate frequencies associated with plosive consonants like /C/ or /G/, occurring when these consonants are splitting a sequence of vowels. 6. Voiced Jump (VJ) Is a region similar with voiced region V, but it has no periodicity. It is due to the balance of vocal signal only above or underlying median zero line. This region has no vowel or other phoneme correspondence in speech signal, but a transition or co-articulation. 7. Irregular Region (IR) This is a region in which one can find plosive consonants like /C/, /G/ or /P/. Usually it comes after a silence region, it has a short duration and a frequency band intermediate between vowels and fricative consonants. 8. High Density transition (HD) Is a transition region with high frequency values, which could indicate emergency of fricative consonants. Signal is not integrated in C or US classes because of positive or negative balance relative to median zero value. 9. Transition (T) This is an intermediate region between voiced and unvoiced and which has no the characteristics of IR or HD classes. 10. Unvoiced Consonant (C) For Romanian language, this class contains fricative consonants /S/, /Ş/, /Ţ/, /F/, /Z/, /J/, /H/, and non-fricatives /Ce/, /Ci/, /Ge/, /Gi/ . For detecting these classes, median amplitude MA(n), number of zero-cross points NTZ, signal energy E(n) have been used as section 2 describes in (1)-(4), and also short-term Fourier coefficients for detection of VP and HD special cases. 3.4. PHONETIC SEGMENTATION Phonetic segmentation is the process of associating phonetic symbols with the speech signal. This process is very usefull when we want to develop an acoustic database from a large speech corpus. Phonetic segmentation gives the capability of detecting and separating phonetic units from speech, units that will be used in achieving the output acoustic chain sequence through concatenation. 308
O. Buza, G. Toderean, J. Domokos, A. Zs. Bodo, Construction of a Syllable-Based Text-To-Speech System for Romanian State of the art on this field exposes some different methods for automated or semi- automated phonetic segmentation of speech signal: iterative methods with training stages (as HMM segmentation or region frontiers refinement), methods based on association rules, statistical methods (like segmentation based on generalized likelihoods GLR), a.o. Phonetic sgmentation method proposed by the authors is a method based on association rules, which realises a correspondence between phonetic groups taken from an input stream and distinct types of regions detected from the speech signal. Segmentation algorithm parses the input text and tries to find the best match for each phonetic group with one or more regions of speech signal. Input text is first written into a special phonetic transcription, using a simple look-after table, which includes phoneme and word transitions. Transcripted text is splitted into a sequence of phonetic groups. Special association rules will establish a correspondence with specific regions detected from speech signal. For associating phonetic groups with sequences of regions, as further in our approach, we have used LEX parser generator. We have written a set of association rules, each rule specifying a phonetic pattern for associating a particular group with a sequence of regions, and also specifying a condition to be verified in order to make that association. Each condition outlines: type of region, minimal and maximal duration, type of association: unique region or sequence of regions. Figure 7 presents association between a phonetic group i i i G F F ,..., F 309 i , where Fk i are 1 , 2 phonetic symbols, and a sequence of regions i i i SR REG REG ,..., REG correspondence rule Ri : Gi COND_REGi . Text Rules Signal … … … REG1 i F1 i N , by the meaning of a 1 , 2 F2 i … Fk i … … R1: G1 Cond_Reg1 Ri: Gi Cond_Regi Rn: Gn Cond_Regn REG2 i Figure 7. Association between phonetic groups and signal regions Gi … REGN i … N k
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O. Buza, G. Toderean, J. Domokos, A. Zs. Bodo, Construction of a Syllable-Based Text-To-Speech System for Romanian<br />
Also a region of voiced discontinuity corresponding to intermediate frequencies associated<br />
with plosive consonants like /C/ or /G/, occurring when these consonants are splitting a<br />
sequence of vowels.<br />
6. Voiced Jump (VJ)<br />
Is a region similar with voiced region V, but it has no periodicity. It is due to the balance of<br />
vocal signal only above or underlying median zero line. This region has no vowel or other<br />
phoneme correspondence in speech signal, but a transition or co-articulation.<br />
7. Irregular Region (IR)<br />
This is a region in which one can find plosive consonants like /C/, /G/ or /P/. Usually it<br />
comes after a silence region, it has a short duration and a frequency band intermediate<br />
between vowels and fricative consonants.<br />
8. High Density transition (HD)<br />
Is a transition region with high frequency values, which could indicate emergency of<br />
fricative consonants. Signal is not integrated in C or US classes because of positive or<br />
negative balance relative to median zero value.<br />
9. Transition (T)<br />
This is an intermediate region between voiced and unvoiced and which has no the<br />
characteristics of IR or HD classes.<br />
10. Unvoiced Consonant (C)<br />
For Romanian language, this class contains fricative consonants /S/, /Ş/, /Ţ/, /F/, /Z/, /J/,<br />
/H/, and non-fricatives /Ce/, /Ci/, /Ge/, /Gi/ .<br />
For detecting these classes, median amplitude MA(n), number of zero-cross points NTZ,<br />
signal energy E(n) have been used as section 2 describes in (1)-(4), and also short-term Fourier<br />
coefficients for detection of VP and HD special cases.<br />
3.4. PHONETIC SEGMENTATION<br />
Phonetic segmentation is the process of associating phonetic symbols with the speech<br />
signal. This process is very usefull when we want to develop an acoustic database from a large<br />
speech corpus. Phonetic segmentation gives the capability of detecting and separating phonetic<br />
units from speech, units that will be used in achieving the output acoustic chain sequence through<br />
concatenation.<br />
308
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