Abstract
This paper intends to present a machine readable Romanian language pronunciation dictionary called NaviRo. The dictionary contains 138,500 unique words from the DexOnline dictionary together with their phonetic transcriptions in speech assessment method phonetic alphabet. The development of the pronunciation dictionary and the performed validation tests are also described in the paper. NaviRo pronunciation dictionary is freely available on the project website (http://users.utcluj.ro/~jdomokos/naviro) in plain text, Hidden Markov Model Toolkit and Festival speech synthesis system dictionary format. There are also available for download the used grapheme and phoneme sets and the audio samples for the used phonemes. The use of these resources is completely unrestricted for any research purposes in order to speed up Romanian language speech technology research.
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References
Beldescu, G. (1984). Ortografia actual a limbii romne, Editura tiinific i Enciclopedic.
Bisani, M., & Ney, H. (2008). Joint-sequence models for grapheme-to-phoneme conversion. Speech Communication, 50, 434–451.
Bo-June, H.(P.), & Glass, J. (2008). Iterative language model estimation: Efficient data structure & algorithms. In Proceedings of Interspeech, pp. 841–844.
Boroş, T., Ştefănescu, D., & Ion, R. (2012). Bermuda, a data-driven tool for phonetic transcription of words. In Proceedings of the eighth international conference on language resources and evaluation (LREC), natural language processing for improving textual accessibility (NLP4ITA) workshop, pp. 35–39.
Burileanu D. (2002). Basic research and implementation decisions for a text-to-speech synthesis system in Romanian. International Journal of Speech Technology, 5, 211–225.
Burileanu, D., Sima, M., & Neagu, A. (1999). A phonetic converter for speech synthesis in romanian. In Proceedings of the XIVth congress on phonetic science (ICPhS), vol. 1, San Francisco, pp. 503–506.
Burileanu, C., Popescu, V., Buzo, A., Petrea, C. S., & Ghelmez-Hane, D. (2010). Spontaneous speech recognition for Romanian in spoken dialogue systems. Proceedings of the Romanian Academy, 11 Series A(1), 8391.
Buzo, A., Cucu, H., & Burileanu, C. (2013). Text spotting in large speech databases for under-resourced languages. In Proceedings of the 7th international conference speech technology and human–computer dialogue (SpeD), pp. 77–82.
Cristea, D., & Forăscu, C. (2006). Linguistic resources and technologies for romanian language. Computer Science Journal of Moldova, 14(1), 34–73.
Davel, M., & Barnard, E. (2003). Bootstrapping in language resource generation. In Proceedings of the 13th annual symposium of the pattern recognition association of South Africa (PRASA), pp. 97–100.
Davel, M., & Barnard, E. (2008). Pronunciation prediction with default & refine. Computer Speech and Language, 22, 374–393.
Domokos, J., Buza, O., & Toderean, G. (2011). Automated grapheme-to-phoneme conversion system for Romanian. In Proceedings of the 6th speech technology and human–computer dialogue conference SpeD, 105-110.
Domokos, J., Buza, O., & Toderean, G. (2012). 100K+ words, machine-readable, pronunciation dictionary for the Romanian language. In Proceedings of the 20th European signal processing conference (EUSIPCO), pp. 320–324.
Domokos, J., László, S., Buza, O., & Toderean, G. (2013). Romanian language voice browsing for web applications using grapheme level acoustic modeling. Advanced Engineering Forum, 8–9, 29–36.
Gómez, J. A., & Castro, M. J. (2002). Automatic segmentation of speech at the phonetic level. In Proceedings of the joint IAPR international workshop on structural, syntactic, and statistical pattern recognition, pp. 672–680.
Institutul de Lingvistică Iorgu Iordan. (2005). Alexandru Rosetti al Academiei Române, DOOM—Dicṭionarul Ortografic, Ortoepic ṣi Morfologic al Limbii Române (Ediṭia a II-a, revizuită ṣi adăugită), Editura Univers Enciclopedic, Bucureṣti.
Jitcă, D., Apopei, V., & Grigoraṣ, F. (2002). An ANN-based method to improve the phonetic transcription module of a TTS system for the Romanian language. In CD-ROM proceedings of the European conference on intelligent technologies—ECIT.
Jitcă, D., Teodorescu, H.-N. L., Apopei, V., & Grigoraṣ, F. (2003). An ann-based method to improve the phonetic transcription and prosody modules of a TTS system for the Romanian language. In Proceedings of the 2nd speech technology and human–computer dialogue conference—SpeD, pp. 43–50.
Jurafsky, D., & Martin, J. H. (2008). Speech and language processing: An introduction to natural language processing, computational linguistics and speech recognition (2nd ed.). Englewood Cliffs: Pearson Prentice Hall.
Livescu, K., Fosler-Lussier, E., & Metze, F. (2012). Subword modeling for automatic speech recognition. Past, present and emerging approaches. IEEE Signal Processing Magazine, 29(6), 44–57.
Militaru, D., Gavăt, I., Dumitru, O., Zaharia, T., & Segarceanu, S. (2009). ProtoLOGOS, system for Romanian language automatic speech recognition and understanding (ASRU). In Proceedings of the 5th conference on speech technology and human–computer dialogue (SpeD), pp. 21–32.
Munteanu, D.-P., & Vizitiu, C.-I. (2008). Robust Romanian language automatic speech recognizer based on multistyle training. WSEAS Transactions on Computer Research, 3(2), 98–109.
Ordean, M. A., Ṣaupe, A., Ordean, M., Duma, M., & Silaghi, G. C. (2009). Enhanced rule-based phonetic transcription for the Romanian language. In Proceedings of the 11th international symphosium on symbolic and numeric algorithms for scientific computation (SYNASC), pp. 401–406.
Saon, G., & Chien, J.-T. (2012). Large-vocabulary continuous speech recognition systems a look and some recent advances. IEEE Signal Processing Magazine, 29(6), 18–33.
Sebe, N. (2009). Multimodal interfaces: Challenges and perspectives. Journal of Ambient Intelligence and Smart Environments, 1, 1926.
Sejnowski, T. J., & Rosenberg, C. R. (1987). Parallel networks that learn to pronounce english text. Complex Systems, 1, 145–168.
Stan, A., Yamagishi, J., King, S., & Aylett, M. (2010). The Romanian speech synthesis (RSS) corpus: Building a high quality HMM-based speech synthesis system using a high sampling rate. Speech Communication, 53(3), 442–450.
Stan, A., Bell, P., & King, S. (2012). A grapheme-based method for automatic alignment of speech and text data. In Proceedings of the IEEE workshop on spoken language technology.
Toma, Ṣ.-A., & Munteanu, D. (2009). Rule-based automatic phonetic transcription for the Romanian language. In Proceedings of the first international conference on future computational technologies and applications, pp. 682–686.
Young, S., Evermann, G., Gales, M., Hain, T., Kershaw, D., Liu, X. (A.), et al. (2006). The HTK book(For HTK version 3.4). Cambridge: Cambridge University Engineering Department.
Acknowledgments
This paper was supported by the project “Development and support of multidisciplinary postdoctoral programmes in major technical areas of national strategy of Research—Development—Innovation” 4D-POSTDOC, Contract No. POSDRU/ 89/1.5/S/52603, project co-funded by the European Social Fund through Sectoral Operational Programme Human Resources Development 2007–2013.
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Domokos, J., Buza, O. & Toderean, G. Romanian phonetic transcription dictionary for speeding up language technology development. Lang Resources & Evaluation 49, 311–325 (2015). https://doi.org/10.1007/s10579-013-9262-z
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DOI: https://doi.org/10.1007/s10579-013-9262-z