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Boosting Rule-Based Grapheme-to-Phoneme Conversion with Morphological Segmentation and Syllabification in Bengali

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Speech and Computer (SPECOM 2023)

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Abstract

This paper presents a novel approach to enhance rule-based Bengali grapheme-to-phoneme (G2P) conversion by leveraging morphological segmentation and syllabification techniques. In this approach, input words are first morphologically segmented into valid morphological chunks, each having a different stem and semantic. Applying the G2P rules on each of these chunks, their pronunciations are generated. An intermediate pronunciation for the whole input word is attained by merging these pronunciations. Using syllabification, this intermediate pronunciation is further divided into valid syllabic sequences that offer accurate morphological boundaries. Finally, the final pronunciation is achieved using syllable-specific orthographic rules on these syllabic sequences. The performance of the proposed G2P approach is assessed using measures representing (i) direct accuracy and (ii) enhancements in different speech-related applications. According to the performances noted for the direct accuracy-based measures, the proposed approach predicted the appropriate pronunciations for about 90% cases, especially for compound and inflected words. This performance is around 22% and 10% better than the performance of a rule-based system and a previous state-of-the-art system, respectively. On the other hand, application-based measures guarantee that the generated phone sequences (i) sound natural and (ii) improve the quality of speech synthesis and recognition systems. These quantitative and qualitative assessment plans answered research questions pertinent to speech and linguistics.

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Acknowledgement

We would like to express our sincere gratitude to Mr Prabhat Mukherjee for his contribution in collecting data and generating the pronunciation dictionary and Mr Nilay Roy for his guidance as a linguist. We also acknowledge the collaborative spirit of the students of KIIT University in the evaluation tasks.

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Correspondence to Krishnendu Ghosh .

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Ghosh, K., Mandal, S., Roy, N. (2023). Boosting Rule-Based Grapheme-to-Phoneme Conversion with Morphological Segmentation and Syllabification in Bengali. In: Karpov, A., Samudravijaya, K., Deepak, K.T., Hegde, R.M., Agrawal, S.S., Prasanna, S.R.M. (eds) Speech and Computer. SPECOM 2023. Lecture Notes in Computer Science(), vol 14338. Springer, Cham. https://doi.org/10.1007/978-3-031-48309-7_34

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  • DOI: https://doi.org/10.1007/978-3-031-48309-7_34

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