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Designing a Speech Corpus for Estonian Unit Selection Synthesis

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Designing a Speech Corpus for Estonian Unit Selection Synthesis Designing a Speech Corpus for Estonian Unit Selection Synthesis Liisi Piits Meelis Mihkla Institute of the Estonian Language Institute of the Estonian Language Roosikrantsi 6, Tallinn 10119, Estonia Roosikrantsi 6, Tallinn 10119, Estonia [email protected] [email protected] Tõnis Nurk Indrek Kiissel Institute of the Estonian Language Institute of the Estonian Language Roosikrantsi 6, Tallinn 10119, Estonia Roosikrantsi 6, Tallinn 10119, Estonia [email protected] [email protected] its entirety provides the acoustic basis for such Abstract synthesis, the development of an optimal corpus represents an essential task of corpus-based syn- The article reports the development of a thesis. A system with a good selection module and speech corpus for Estonian text-to-speech a high-quality speech corpus may yield output synthesis based on unit selection. Intro- speech of extremely high quality, even if the signal duced are the principles of the corpus as processing module is rather simple (Bozkurt et al., well as the procedure of its creation, from 2002). text compilation to corpus analysis and text Considering an optimal database for Estonian recording. Also described are the choices text-to-speech synthesis it should obviously con- made in the process of producing a text of tain phonetically rich sentences and different pho- 400 sentences, the relevant lexical and nological structures of Estonian. The corpus words morphological preferences, and the way to should also include all Estonian diphones. The first the most natural sentence context for the database for Estonian speech synthesis consisted of words used. ca 1700 diphones (Mihkla et al., 1998). The ex- perience accumulated during the creation of that 1 Introduction database came in handy while developing our cor- Text-to-speech synthesis means that synthetic pus. Aim was a speech corpus that would not be speech is automatically generated from a written too big (up to 60 minutes), yet representative text. The understandability and naturalness of out- enough from phonetic and phonological aspects, put speech depends on linguistic preprocessing of containing many numbers and years, alongside the input text, the prosody generator, signal proc- with frequent Estonian words and expressions. essing and the quality of the speech database used. Even though a necessity for repeat recordings to It has been argued - and proved in practice - that complement the corpus cannot be ruled out en- the large number of concatenation points make the tirely, material should serve for synthesis of an synthetic speech sound unnatural, even if the spec- arbitrary text as well as for limited domain applica- tral discontinuities have been minimized by care- tions. fully smoothing the concatenation points, consider- ing phonetic criteria (Donovan and Woodland 2 Text corpus development 1999). The idea of corpus-based, or unit-selection The first decision to be made concerned the size of synthesis is that the corpus is searched for maxi- the corpus. This meant a compromise between the mally long phonetic strings to match the sounds to minimum and maximum sizes. A maximum size be synthesized. As compared to diphone or would mean a greater probability of the corpus triphone synthesis, corpus-based speech tends to containing the biggest possible units to match the elicit considerably higher ratings of naturalness in text to be synthesized- from sound strings to words auditory tests (Nagy et al., 2003). As the corpus in or even phrases. Unfortunately, big databases have Joakim Nivre, Heiki-Jaan Kaalep, Kadri Muischnek and Mare Koit (Eds.) NODALIDA 2007 Conference Proceedings, pp. 367–371 Liisi Piits, Meelis Mihkla, Tõnis Nurk and Indrek Kiissel been found complicated to maintain and even more cally allowed by the rules of Estonian word struc- complicated to annotate (Breen and Jackson, ture, yet not realized. For example, the diphone üf 1998). Moreover, segmentation and tagging of can be found in the 2nd quantity degree, as in the corpus units is a cumbersome and time-consuming loanword küfoos ’kyphosis’, but for the 3rd- process - it has been found that a one-minute cor- quantity diphone üf : a nonsense word * süf:fi had to pus takes 1000 minutes to mark up (Mihkla et al., be made up, as the theoretically possible diphone 1998). This is why we decided to make the corpus cannot be derived from its 2nd-quantity equivalent. as small as possible, yet containing as much rele- The number of such nonsense strings included in vant material as possible. the corpus was 18. In sentences we generally tried to disperse the 2.1 Stage 1: diphones words with a marked structure among the un- It was decided that the smallest searchable unit of marked ones. Most of the nonsense strings, how- the corpus would be a diphone. Therefore it was ever, were given a concentrated presentation in important to ensure that the corpus contains all di- special sentences: e.g. *Puls:s *kõõ:l’is seda phones possible in Estonian. We already had a *võõ:ba ehk* mõõ:du. word list, compiled for an earlier synthesizer based At the end of Stage 1 the corpus contained 178 on diphone selection, featuring all diphones occur- sentences, with 1244 words all told. ring in Estonian (Mihkla et al., 1998). Most of 2.2 Stage 2: words and phrases those words were taken as the basis for the new corpus. However, as the words had not been in- While diphone is a minimal unit of the corpus, a cluded in the list in their natural sentence context, word or even a phrase is seen as a unit of maximal our first task was to provide a sentence context for length. The aim of stage 2 was to supply sentences them. containing the most frequent Estonian words and So, Stage 1 of the corpus development started phrases. As the synthesizer is meant for texts with- with combining the list words to make meaningful out domain limitations the corpus vocabulary was sentences. During that process one had to keep a to cover a wide selection of spheres. The words watchful eye on the pronounceability of words and were selected from Frequency Dictionary of Stan- sentences, considering sentence length as well as dard Estonian (Kaalep and Muischnek, 2002), word structure. Both too long and too short sen- which is based on texts from media and fiction. tences were to be avoided. For English sentences it The aim was to make an addition of 1000 most has been argued that too short sentences (less than frequent words. Frequency measurement is com- 5 words) have a deviant prosody, while too long plicated due to Estonian morphology. The numer- ones (more than 15 words) tend to elicit more mis- ous cases of stem alternation and agglutination are takes when read out (Kominek and Black, 2003). the reason why a word may have many forms. A As Estonian is a more synthetic language than noun, for example, may yield 28 word forms, each English we did not stick to the five-word limit, of a different grammatical meaning. As generally ending up at seven words in an average sentence. most of the forms are made up of a word stem and Among the sound combinations and syllable various grammatical morphemes it was found suf- types of a natural language there are some that are ficient to include just the stem of a high-frequency easy to pronounce and some others that are not. word, which could take certain grammatical mor- The latter, being more demanding on speech or- phemes also present in the corpus. The word forms gans, are used less frequently. Such sound se- contained in the corpus were to cover all para- quences and syllable types are called marked ones digms of declinable as well as conjugable words. (Hint, 1998). As the word list was meant to include Also, the formative variants containing different all diphones possible in Estonian it contained not allomorphs were to be represented. only frequent words but also the rare words with Besides agglutinative formation there was in- marked structure. There were even some diphones flection to be reckoned with. In Estonian, meaning not allowed by Estonian phonotactics, but they had can also be conveyed by stem alternation. Grada- to be included because of their occurrence in for- tional words have at least two stem variants, both eign words. In addition, the list contained some taking different grammatical markers and endings. nonsense words with sound combinations theoreti- Therefore, different stem variants also needed to be 368 Designing a Speech Corpus for Estonian Unit Selection Synthesis included, if at all possible, e.g. haka -ta 'to begin' The gray cells stand for diphones missing from and hakka -b ' begins ', mees 'man Nom. Sg.' and the corpus, however possible theoretically. As Es- mehe 'man Gen. Sg.', krooni 'crown Gen. Sg.' and tonian is fond of active compounding we had also kroo:ni 'crown. Part. Sg' . to consider such sound combinations as might Besides grammatical markers and endings the emerge at compound boundary. So some additional corpus was provided with words containing the words (mostly compounds) were found to fill in most productive derivational suffixes like in: the gray cells. The crossed cells stand for diphones moodusta mine ' formation' , must lanna 'gypsy theoretically impossible in Estonian, or at least woman' , võist kond 'team' , raha ndus 'finance' etc . impossible to find by the means available. The nominative and genitive forms of cardinal As our corpus was meant to be as rich as possi- and ordinal numerals were also included, and the ble phonetically and phonologically we had to in- most frequent place names - not only Estonian clude many sound combinations that were less fre- ones, but also some foreign toponyms salient in the quent, yet vital for TTS.
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