Abstract

The text to speech (TTS) is one of the recommended research level topics in the domain of natural language processing and speech processing. In this day and age, the usage of mobile phones is extremely increasing so the researchers focus on speech processing on mobile devices. TTS system for mobile phones is difficult to implement as they have limited storage capacity and computing performance. Therefore, phoneme based Myanmar TTS (MTTS) system is proposed for resource limited devices. In this paper, rule based Myanmar number conversion and new phonological rules are proposed. For speech generation, firstly, phoneme speech database in which there are only 133 phoneme units is created and then the new phoneme concatenation algorithm is applied. Moreover, each module of MTTS system is presented in detail with their respective experimental results and the system achieved the acceptable level of intelligibility although naturalness is still needed to achieve the satisfactory level according to these results.

Keyword

Text to speech, Myanmar language, Phoneme, Concatenative speech synthesis.

Cite this article

Refference

[1][1]Black AW, Campbell N. Optimising selection of units from speech databases for concatenative synthesis.1995.

[2][2]Conkie A. Robust unit selection system for speech synthesis. The Journal of the Acoustical Society of America. 1999 .

[3][3]Hunt AJ, Black AW. Unit selection in a concatenative speech synthesis system using a large speech database. In international conference on acoustics, speech, and signal processing 1996. (pp. 373-76). IEEE.

[4][4]Toda T, Kawai H, Tsuzaki M, Shikano K. Unit selection algorithm for Japanese speech synthesis based on both phoneme unit and diphone unit. In international conference on acoustics, speech, and signal processing 2002 (pp. 465-8). IEEE.

[5][5]Douke M, Hayashi M, Makino E. A study of automatic program production using TVML. Eurographics.1999:42-5.

[6][6]Win KY, Takara T. Myanmar text-to-speech system with rule-based tone synthesis. Acoustical Science and Technology. 2011; 32(5):174-81.

[7][7]Soe EP, Thida A. Text-to-speech synthesis for Myanmar language. International Journal of Scientific & Engineering Research. 2013; 4(6):1509-18.

[8][8]Wongpatikaseree K, Ratikan A, Thangthai A, Chotimongkol A, Nattee C. A real-time Thai speech synthesizer on a mobile device. In international symposium on natural language processing 2009 (pp. 42-7). IEEE.

[9][9]Wongpatikaseree K, Ratikan A, Chotimongkol A, Chootrakool P, Nattee C, Theeramunkong T, et al. A hybrid diphone speech unit and a speech corpus construction technique for a Thai text-to-speech system on mobile devices. In international conference on electrical engineering/electronics computer telecommunications and information technology 2010 (pp. 1089-93). IEEE.

[10][10]Mokgonyane TB, Sefara TJ, Manamela PJ, Manamela MJ, Modipa TI. Development of a speech-enabled basic arithmetic m-learning application for foundation phase learners. In AFRICON 2017 (pp. 794-9). IEEE.

[11][11]Karabetsos S, Tsiakoulis P, Chalamandaris A, Raptis S. Embedded unit selection text-to-speech synthesis for mobile devices. IEEE Transactions on Consumer Electronics. 2009; 55(2):613-21.

[12][12]Gopi A, Shobana PD, Sajini T, Bhadran VK. Implementation of Malayalam text to speech using concatenative based TTS for android platform. In international conference on control communication and computing 2013 (pp. 184-9). IEEE.

[13][13]Myanmar language commission, Myanmar grammar. 30th year special edition. University Press, Yangon, Myanmar; 2005.

[14][14]Tun DT. Acoustic phonetics and the phonology of the myanmar language. School of Human Communication Sciences, La Trobe University, Melbourne, Australia. 2007.

[15][15]Zhao Z, Ma X. Active learning for the prediction of prosodic phrase boundaries in Chinese speech synthesis systems using conditional random fields. In IEEE/ACIS international conference on software engineering, artificial intelligence, networking and parallel/distributed computing 2015 (pp. 1-5). IEEE.

[16][16]Htay HH, Murthy KN. Myanmar word segmentation using syllable level longest matching. In the workshop on Asian language resources, IJCNLP 2008 (pp. 41-8).

[17][17]Jurafsky D, Martin JH. Speech and language processing: an introduction to natural language processing, computational linguistics, and speech recognition. Prentice Hall; 2000.