Standardising Pronunciation for a Grapheme-to-Phoneme Converter for F aroese (2023)

Abstract: Pronunciation dictionaries allow computational modelling of the pronunciation of words in a certain language and are widely used in speech technologies, especially in the fields of speech recognition and synthesis. On the other hand, a grapheme-to-phoneme tool is a generalization of a pronunciation dictionary that is not limited to a given and finite vocabulary. In this paper, we present a set of standardized phonological rules for the Faroese language; we introduce FARSAMPA, a machine-readable character set suitable for phonetic transcription of Faroese, and we present a set of grapheme-to-phoneme models for Faroese, which are publicly available and shared under a creative commons license. We present the G2P converter and evaluate the performance. The evaluation shows reliable results that demonstrate the quality of the data.

## introduction pronunciation dictionaries are important components in speech technology (i.e. for asr and tts). they are used to link orthographic forms with their pronunciations. there are many kinds of pronunciation d ictionaries; some that only provide a standard pronunciation @xcite , and some that also provide dialectal variants @xcite . however, dictionaries are always going to be limited to their entries; it is therefore that one would train grapheme-to-phoneme (g2p) models on pronunciation dictionaries and use those models to automatically transcribe unknown words @xcite . in recent years, there has been steady progress in faroese speech technology, and the work is ongoing (e.g. @xcite @xcite . a faroese pronunciation dictionary was created for the first faroese asr project, ravnur and published in 2022 as part of a basic language resource kit (blark) for faroese @xcite 1 . a blark is defined as the minimal collection of language resources needed to develop language technology for a specific language @xcite . however, the blark is not limited to asr, but can be used to develop a wide range of lt for faroese. the dictionary from the ravnur project uses the variation spoken in the capital of the faroe islands as a standard (an arbitrary choice as discussed in section 5). when creating the grapheme-to-phoneme (g2p) models, it was decided to expand the dictionary into two different pronunciation dictionaries based on dialectal difference, one central and one east. this way, we could cover more ground and open up the possibility to expand the work further in the future. because this was the first open source faroese dictionary of its kind, ravnur also had to create a faroese sampa alphabet (called farsampa here) to use for the pronunciations. the process and decisions made when creating farsampa and the faroese pronunciation dictionary have never been published until now. we therefore set out to describe the work that went behind creating these fundamental language resources and how we adapted them to create a reliable g2p model. in section 2, we present farsampa. section 3 outlines some of the most common graphemeto-phoneme conversions of faroese, while section 4 presents the standardization of phonetic variation for the g2p. in section 5, we discuss faroese dialectal variation and the decision to make two different pronunciation dictionaries to train g2p models on. finally, we introduce our g2p models that have been trained on the two pronunciation dictionaries, present an evaluation, and conclude. ## farsampa -faroese sampa 3 this section introduces farsampa: a machinereadable character set suitable for phonetic transcription of faroese. this character set is a phonetic alphabet consisting of an inventory of ascii symbols mapped onto symbols of ipa (the international phonetic alphabet). the inventory content is based on faroese phonetic and phonological knowledge and research (e.g. @xcite , and transcription conventions for faroese were considered when creating the alphabet. all phonemes in the g2p tool introduced in this article are written in farsampa, as the lexical data of the tool is transcribed in farsampa. see the primary purpose of farsampa is to make phonetic transcriptions machine-readable and ready for automatic processing, and even though the value of characters is arbitrary to a machine, we need to keep in mind that phonetic transcription also entails a manual element and needs to be somewhat human-readable as well. the designation of characters to phones was based on simplicity, efficiency, and intuition. the basic guidelines foot_2 are summed up as follows: sampa from the ravnur project is not originally published under the name farsampa, but we will use farsampa to refer to the faroese sampa in this article. not all allophones are represented, as that level of detail does not benefit accuracy or efficiency of language technology purposes. four unvoiced allophones of the sonorant phonemes /m, n, n, l/ are included, as they are acoustically very different from their voiced counterparts. the only diacritic included with its own character is the preaspiration /h/. postaspiration and other relevant diacritics for faroese (e.g. voiced/unvoiced) are integrated in the character system and not denoted via symbols of their own (e.g. @xcite only differ by postaspiration, [m] and [m] only differ by voicing). ## phonological rules of faroese in this section, we will outline some of the most common grapheme-to-phoneme conversions of (central) faroese. for dialectal variation, see section 5. the conversions are based on @xcite . almost all of the rules listed have exceptions, and there are other phonological rules as well. for a more thorough overview, see @xcite . furthermore, the phonetics of faroese are generally understudied @xcite , and therefore, many phonological conditions have not been sufficiently studied or described. some of these phonological conditions will be discussed as well. ## representing pronunciation variations in one form for developing the g2p-tool, we used the open source pronunciation dictionary from project ravnur @xcite . however, we only use one single pronunciation per word. the original dictionary had many entries with multiple pronunciations, and for this project of developing the g2p-tool we had to prioritize just one of them. being a descriptive dictionary, some words were assigned multiple pronunciations due to language variation (differences in dialect, sociolect or other lects) and assimilation of different kinds. in cases of dialectal variations, the pronunciations of the central dialect were chosen, as the different dialects are represented through separate dictionaries. in cases of other variation with no research to base the decision on, the choice was based on (by the faroese linguist) perceived frequency of the forms, choosing the more frequent as the primary -knowing the limitations of this method. quite many of the word forms with multiple pronunciations were due to homographs. as the dictionary version for the g2p tool only operates with the values of orthography and pronunciation and no grammatical or semantic information, homographic word forms that belong to different lexemes melt into one, with their respective pronunciations being registered as pronunciation variations of the same form. as this tool strictly focuses on the relationship between graphs and phones, the semantics and grammar to differentiate homographic word forms are of course obsolete, but the omission of these values also presents challenges. choosing one pronunciation over another in these cases, where both forms are considered to be valid in faroese language, blurs the depiction of the linguistic reality, but is necessary for this linear conversion tool and might even increase accuracy of the tool. in cases of multiple pronunciations due to homographs, one pronunciation has been chosen to be primary based on the main criteria of frequency and second phonological heritage (detailed below), having functionality and error rates of the tool in mind. frequency derived from searches in available corpora or web-search-based frequency was not always sufficient due to the relatively small volume of the resources, many of them not tagged, making it difficult to distinguish homographic forms. in these cases, other frequency measures were also taken into account: ## two dictionaries for faroese the original dictionary from the ravnur project is based on the dialect of the capital in the faroe islands. even though there is no official standard dialect for faroese @xcite , there is believed to be some kind of central faroese based partly on the dialect of the capital and partly on the written language @xcite . however, in working with this g2p tool, we wanted to have greater diversity and decided to make two versions of the original dictionary reflecting two different dialect areas. the two dialect areas are the central dialect area, where the capital is located, called central henceforth, and part of the northwest dialect area, called east henceforth (see figure 1 ). the central dialect area has the largest number of inhabitants, and the east dialect area has the second highest number of inhabitants. combined, these two dialect areas comprise around 71% of the population foot_7 . the islands in the northwest area are for several reasons classified as being the same dialect area in the most recent dialect classification @xcite . however, there is one important phonetic difference between the westernmost islands and the more central and eastern islands in that dialect area, and therefore, the westernmost part of the dialect area is not included in our east dictionary (the dotted line in figure 1 marks the two parts of the northwest dialect area). this phonetic difference is the pronunciation of the digraph ei. for the same reason, we have given this dictionary the name east. this way, it is possible to make west, northern and southern dictionaries as well, should the possibility present itself. in section 3, we presented the general phonological rules for (central) faroese. in the following section, we will outline the main dialectal differences between the central and the east dictionaries. for further information on dialectal differences in faroese, see @xcite and petersen (2022). ## g2p the "faroese g2p models" is a set of two models trained with the software tool "sequitur-g2p" (for details on sequitur-g2p, see @xcite , which is a trainable grapheme-to-phoneme tool developed at rwth aachen university ( https://www.rwth-aachen.de/ ) by maximilian bisani. one of the models is for central faroese and the other is for the east variant. the set also includes two files with the corresponding repertory of phonemes for the central (central.phones) and the east (east.phones) variants. ## conclusion a standardized pronunciation dictionary of good quality is crucial for the development of spoken language technologies. this work describes the definition, development and the establishment of a faroese pronunciation dictionary and a grapheme-to-phoneme tool to go along with it. this work is also important in understanding spoken faroese and can be used to study regional differences in accents and dialects. it is clear that this will form a basis of further studies of faroese and development of spoken language technologies such as asr and tts.