Estonian isolated-word text-to-speech synthesiser (2025)

Abstract: This paper presents the development and evaluation of an Estonian isolated-word text-to-speech (TTS) synthesiser. Unlike conventional TTS systems that convert continuous text into speech, this system focuses on the synthesis of isolated words, which is crucial for applications such as pronunciation training, speech therapy, and (learners’) dictionaries. The system addresses two key challenges: generating natural prosody for isolated words and context-free disambiguation of homographs. We conducted a perception test to evaluate the performance of the TTS system in terms of pronunciation accuracy. We used 16 pairs of homographs that differ in palatalisation and 16 pairs of homographs that differ in quantity. Given that all the test items were correctly recognised by a majority of the evaluators, the performance of the synthesiser can be considered very good.

## introduction text-to-speech synthesis (tts) is typically used to convert texts and sentences into speech. however, there are many applications that require the speech synthesis of isolated words: pronunciation training applications, speech and language therapy applications, (learners') dictionaries, etc. such applications additionally require a careful and correct pronunciation of the synthesised words. to achieve this, the tts system must fulfill two additional requirements beyond the general requirements for tts systems. first, the training data must contain a sufficient amount of short utterances in order for the system to be able to generate isolated words with a natural utterance prosody. second, the system must allow for a context-free disambiguation of input words that have phonologically different homographs. while the first requirement is unproblematic, the second requirement is a considerable challenge for a language like estonian. estonian possesses a large number of homographs that are mainly due to the absence of orthographic marking for two phonological features of estonian: palatalisation and, in certain cases, third quantity (overlong length degree). this gives rise to two main types of homograph pairs: homographs differing in palatalisation, and homographs differing in second quantity (q2) vs. third quantity (q3). palatalisation in estonian is, on the one hand, a coarticulatory phenomenon, meaning that all alveolar consonants /t, s, n, l/ preceding /i/ or /j/ at the boundary of the primary stressed syllable and the following syllable become palatalised. on the other hand, it is also a phonological phenomenon that distinguishes meaning @xcite . the distinction between second and third quantity results from a difference in the prosodic structure of long stressed syllables, which can occur either in a disyllabic (q2) or monosyllabic (q3) foot @xcite . both palatalisation and quantity distinctions can be challenging for learners of estonian as a second language and thus require attention in language pedagogy applications @xcite . the homograph pairs differing in palatalisation are always (inflectional forms of) different lemmas whereas quantity distinguishes both between homographic lemmas and inflectional forms of the same lemma. for example, the orthographic form tulp represents both /tulpː/ 'signpost.nom.sg' and /tul j pː/ 'tulip.nom.sg', and maitse represents both /mɑitse/ 'taste.nom.sg' and /mɑitːse/ 'taste.gen.sg' or 'taste.imp.2sg'. in addition, numerous words have pronunciation variants differing only in quantity or palatalisation. the estonian combined dictionary (combidic) @xcite contains altogether 756 homographs and pronunciation variants differing in palatalisation, and 22,618 homographs and variants differing in quantity (excluding compounds). while the incorrect pronunciation of these homographs does not necessarily hinder comprehension in context, it does so without context and is particularly problematic in pedagogical applications. a tts system that is able to generate isolated words with a correct pronunciation must thus include a means for disambiguating homographs. current supervised estonian tts systems include morphological parsing and disambiguation as part of their pre-processing pipeline. the standard morphological parser and disambiguator currently used in the estonian tts systems is vabamorf foot_0 @xcite . in addition to part-ofspeech and inflectional categories the parser annotates compound boundaries and the following pronunciation features: third quantity, irregular stress, and palatalisation. morphological parsing is followed by disambiguation; however, disambiguation is based on the probability of tag sequences within sentences and thus cannot be applied to isolated input words. as a result, the probability that an existing supervised tts system generates the desired member of a homograph pair is at chance level. likewise, the disambiguation of homographic input words is infeasible in unsupervised tts systems, which may produce palatalisation, quantity, stress and compound identification errors also in words without homographs. in order to solve this problem, we developed a dedicated estonian tts system for generating isolated words with a correct pronunciation. section 2 describes the development and the features of the system (training data, pre-processing, tts technique, and user interface), section 3 evaluates the performance of the system in terms of the pronunciation accuracy of homographic minimal pairs differing in palatalisation or quantity, section 4 describes the planned and potential use cases of the system, and section 5 presents the conclusion and future steps. ## use cases the isolated-word tts synthesiser allows the user to generate correctly pronounced isolated words and multi-word units by manually specifying the features of quantity, palatalisation, lexical stress and compound structure. the synthesiser generates isolated words with an appropriate utterance prosody and high phonetic quality, being thus suitable for language pedagogical and speech therapeutic purposes. below, we describe three planned or potential use cases of the isolated-word synthesiser. ## conclusions and future work the paper described the development, features, evaluation and use cases of the estonian isolatedword tts synthesiser @xcite and https://elo.eki.ee/yksiksona/ ). the synthesiser allows the user to generate correctly pronounced isolated words and multi-word units by manually specifying the diacritics for third quantity, palatalisation, lexical stress and compound boundaries. the synthesiser generates isolated words with an appropriate utterance prosody and high phonetic quality, being thus suitable for language pedagogical and speech therapeutic applications. future steps include the improvement of the user-friendliness of the user interface. to help users insert the necessary diacritics, automatic tagging of the orthographic input text will be added, with multiple outputs for homographs among which the user can choose. a second line of future work will be the development of a similar tts application for longer texts, enabling the user to correct parsing and disambiguation errors that cause pronunciation errors. finally, we will employ more advanced tts techniques to train additional isolated-word synthesisers.