Algorithm and implementation of automatic phonemic transcription for Polish

Kłosowski, Piotr

doi:10.1109/spa.2016.7763631

Cited by 6 publications

(9 citation statements)

References 22 publications

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“…The first set of grapheme-to-phoneme conversion rules for Polish was developed by Maria Steffen-Batóg and presented in her set of monographs dedicated to automatic grapheme-to-phoneme conversion of texts in Polish [36,37]. The knowledge contained in these publications was the basis for developing the grapheme-to-phoneme conversion algorithm for Polish implemented by the author in the Python programming language [48]. According to Maria Steffen-Batóg, all grapheme-to-phoneme conversion rules relating to each orthographic letter can be stored in a matrix called the grapheme-to-phoneme conversion rule-table for the letter in question.…”

Section: Conversion Rulesmentioning

confidence: 99%

“…The grapheme-to-phoneme conversion rules are the foundation of the grapheme-tophoneme conversion algorithm implemented here [48]. The conversion algorithm defines how the function F(α) = β works and determines the method for obtaining sequences of phonemic β k letters on the basis of orthographic sequences α k and their contexts.…”

Section: Conversion Algorithmmentioning

confidence: 99%

“…On the basis of Batóg's work [36,37], the author of this paper implemented the graphemeto-phoneme conversion rules for Polish in the Python programming language [49]. The implementation includes 975 conversion rules covering all 35 letters and special characters [48] of Polish orthography. Although many words have multiple correct pronunciations, the rules implemented here in this way produce only one (the most basic) pronunciation for any given word.…”

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confidence: 99%

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A Rule-Based Grapheme-to-Phoneme Conversion System

Kłosowski

2022

Applied Sciences

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This article presents a rule-based grapheme-to-phoneme conversion method and algorithm for Polish. It should be noted that the fundamental grapheme-to-phoneme conversion rules have been developed by Maria Steffen-Batóg and presented in her set of monographs dedicated to the automatic grapheme-to-phoneme conversion of texts in Polish. The author used previously developed rules and independently developed the grapheme-to-phoneme conversion algorithm.The algorithm has been implemented as a software application called TransFon, which allows the user to convert any text in Polish orthography to corresponding strings of phonemes, in phonemic transcription. Using TransFon, a phonemic Polish language corpus was created out of an orthographic corpus. The phonemic language corpusallows statistical analysis of the Polish language, as well as the development of phoneme- and word-based language models for automatic speech recognition using statistical methods. The developed phonemic language corpus opens up further opportunities for research to improve automatic speech recognition in Polish. The development of statistical methods for speech recognition and language modelling requires access to large language corpora, including phonemic corpora. The method presented here enables the creation of such corpora.

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Section: Conversion Rulesmentioning

confidence: 99%

Section: Conversion Algorithmmentioning

confidence: 99%

mentioning

confidence: 99%

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A Rule-Based Grapheme-to-Phoneme Conversion System

Kłosowski

2022

Applied Sciences

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“…According to the grapheme-to-phoneme conversion rules for Polish, described in the literature [29][30][31][32], the grapheme-to-phoneme conversion for Polish has been implemented in the Python programming language, as automatic grapheme-to-phoneme conversion application named TransFon [33]. The implementation includes 975 grapheme-to-phoneme conversion rules for 35 orthographic letters in Polish, additionally conversion rules for special characters and automatic grapheme-tophoneme conversion algorithm [33].…”

Section: Grapheme-to-phoneme Conversionmentioning

confidence: 99%

“…The implementation includes 975 grapheme-to-phoneme conversion rules for 35 orthographic letters in Polish, additionally conversion rules for special characters and automatic grapheme-tophoneme conversion algorithm [33]. Block diagram of the grapheme-to-phoneme conversion algorithm for a single orthographic word is presented in Fig.…”

Section: Grapheme-to-phoneme Conversionmentioning

confidence: 99%

Statistical analysis of orthographic and phonemic language corpus for word-based and phoneme-based Polish language modelling

Kłosowski

2017

J AUDIO SPEECH MUSIC PROC.

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This article presents the original results of Polish language statistical analysis, based on the orthographic and phonemic language corpus. Phonemic language corpus for Polish was developed by using automatic grapheme-to-phoneme conversion of the source orthographic language corpus, obtained from the National Corpus of Polish (NCP). The corpus contains the most frequently used Polish words, written with the use of phonemic notation. Performed statistical analysis of Polish language based on phonemic language corpus, includes frequency of occurrence calculation of the orthographic and phonemic language components, as well as their sequence. Statistical language data, obtained as a result of performed statistical analysis, enable to develop statistical word-based and phoneme-based language models for Polish. Applying these language models can effectively contribute to efficiency improvement of automatic speech recognition for Polish.

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A Multi-Layer Transcription Model – concept outline

Śledziński

2023

linpo

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This paper discusses the assumptions of a Multi-Layer Transcription Model (hereinafter: MLTM). The solution presented is an advanced grapheme-to-phoneme (G2P) conversion method that can be implemented in technical applications, such as automatic speech recognition and synthesis systems. The features of MLTM also facilitate the application of text-to-transcription conversion in linguistic research. The model presented here is the basis for multi-step processing of the orthographic representation of words with those being transcribed gradually. The consecutive stages of the procedure include, among other things, identification of multi-character phonemes, voicing status change, and consonant clusters simplification. The multi-layer model described in this paper makes it possible to assign individual phonetic processes (for example assimilation), as well as other types of transformation, to particular layers. As a result, the set of rules becomes more transparent. Moreover, the rules related to any process can be modified independently of the rules connected with other forms of transformation, provided that the latter have been assigned to a different layer. These properties of the multi-layer transcription model in question provide crucial advantages for the solutions based on it, such as their flexibility and transparency. There are no assumptions in the model about the applicable number of layers, their functions, or the number of rules defined in each layer. A special mechanism used for the implementation of the MLTM concept enables projection of individual characters onto either a phonemic or a phonetic transcript (obtained after processing in the final layer of the MLTM-based system has been completed). The solution presented in this text has been implemented for the Polish language, however, it is not impossible to use the same model for other languages.

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Algorithm and implementation of automatic phonemic transcription for Polish

Cited by 6 publications

References 22 publications

A Rule-Based Grapheme-to-Phoneme Conversion System

A Rule-Based Grapheme-to-Phoneme Conversion System

Statistical analysis of orthographic and phonemic language corpus for word-based and phoneme-based Polish language modelling

A Multi-Layer Transcription Model – concept outline

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