Developing a Text to Speech System for Dzongkha

We describe in detail a Grapheme-to-Phoneme (G2P) converter required for the development of a good quality Marathi Text-to-Speech (TTS) system. The Festival and Festvox framework is chosen for developing the Marathi TTS system. Since Festival does not provide complete language processing support specie to various languages, it needs to be augmented to facilitate the development of TTS systems in certain new languages. Because of this, a generic G2P converter has been developed. In the customized Marathi G2P converter, we have handled schwa deletion and compound word extraction. In the experiments carried out to test the Marathi G2P on a text segment of 2485 words, 91.47% word phonetisation accuracy is obtained. This Marathi G2P has been used for phonetising large text corpora which in turn is used in designing an inventory of phonetically rich sentences. The sentences ensured a good coverage of the phonetically valid di-phones using only 1.3% of the complete text corpora.

Gaining fluency in any language is a cumbersome task. To make it easy so many software's are existing now a days. Our aim is to develop a software that enhances the user's way of speech through correctness of pronunciation following the English phonetics. This software allows one to learn, judge and recognize their potential in English language. It also facilitates an extra add-on feature which nourishes the user's communication skills by an option of text to speech conversion conversion also. Enhancing the existing algorithms of speech to text to improve the quality of the output is under consideration.

6th Workshop on Spoken Language Technologies for Under-Resourced Languages (SLTU 2018), 2018

Text-to-Speech (TTS) synthesis has come far from its primitive synthetic monotone voices to more natural and intelligible sounding voices. One of the direct applications of a natural sounding TTS systems is the screen reader applications for the visually impaired and the blind community. The Festival Speech Synthesis System uses a concatenative speech synthesis method together with the unit selection process to generate a natural sounding voice. This work primarily gives an account of the efforts put towards developing a Natural sounding TTS system for Nepali using the Festival system. We also shed light on the issues faced and the solutions derived which can be quite overlapping across other similar under-resourced languages in the region.

1997

This paper describes the design and development of TTS. This paper describes the overview of different types of synthesis system. One approach to the generation of natural-sounding synthesized speech waveforms is to select and concatenate units from a large speech database. The system used the Syllabication procedure and Phones and Diphones. I. Introduction Speech synthesizer or Text to speech Synthesizer is most widely used system in speech technology. We have various text to speech synthesizer systems available like Festival, Multilingual and Flite etc. A Text-To-Speech (TTS) synthesizer is a computer-based system that should be able to read any text aloud, whether it was directly introduced in the computer by an operator or scanned and submitted to an Optical Character Recognition (OCR) system. As such, the process of TTS conversion allows the transformation of a string of phonetic and prosodic symbols into a synthetic speech signal. The quality of the result produced by a TTS sy...

2000

Thai -text analysis, prosody generation and speech synthesis. In the text analysis, problems in Thai text processing can be decomposed into the models of sentence extraction, phrase boundary determination and grapheme-to-phoneme conversion. The syllable duration and F0 contour generation rules are included in the prosody generation. This is to realize the synthetic speech in the suprasegmental level. In the speech synthesis, the definition and the construction of acoustic inventory structure 'demisyllable' are presented. Furthermore, three signal-processing algorithms, amplitude normalization, the segment boundary smoothing and prosodic modification, are also presented in this topic.

This paper presents a rule-based text-to-speech (TTS) Synthesis System for Standard Malay, namely SMaTTS. The proposed system using sinusoidal method and some pre-recorded wave files in generating speech for the system. The use of phone database significantly decreases the amount of computer memory space used, thus making the system very light and embeddable. The overall system was comprised of two phases the Natural Language Processing (NLP) that consisted of the high-level processing of text analysis, phonetic analysis, text normalization and morphophonemic module. The module was designed specially for SM to overcome few problems in defining the rules for SM orthography system before it can be passed to the DSP module. The second phase is the Digital Signal Processing (DSP) which operated on the low-level process of the speech waveform generation. A developed an intelligible and adequately natural sounding formant-based speech synthesis system with a light and user-friendly Graphical User Interface (GUI) is introduced. A Standard Malay Language (SM) phoneme set and an inclusive set of phone database have been constructed carefully for this phone-based speech synthesizer. By applying the generative phonology, a comprehensive letter-to-sound (LTS) rules and a pronunciation lexicon have been invented for SMaTTS. As for the evaluation tests, a set of Diagnostic Rhyme Test (DRT) word list was compiled and several experiments have been performed to evaluate the quality of the synthesized speech by analyzing the Mean Opinion Score (MOS) obtained. The overall performance of the system as well as the room for improvements was thoroughly discussed.

As we know that the speech is easiest way of communication. We commonly use speech for communication. Speech to text is now most widely used mechanism that is basically designed for disabled persons. Peoples who are suffered by disabilities like disabled by hand can use this for communication. Urdu parsing speech to text basically used voice recognizer that listens human voice and translate the urdu speech into urdu text. Few years ago SST is used for traveling system but that work was not very vast. There are many difficulties in this system.one of the biggest problem is noise problem that affect the quality of voice that is recorded. But the main difficulty is that urdu dictionary is very difficult to concatenate with recognizer. Because already done work is not very vast and accurate. There is also accent problem for different peoples.The model used for recognition is mostly markov hidden model(MMH).And the language used is python and machine learning.. The human computer interface has been developed to communicate or interact conveniently for one who is suffering from some kind of disabilities. Speech-to-Text Conversion (STT) systems have a lot of benefits for the deaf or dumb people and find their applications in our daily lives. In the same way, the aim of the system is to convert the input speech signals into the text output for the deaf or dumb students in the educational fields. This paper presents an approach to extract features by using Mel Frequency Cepstral Coefficients (MFCC) from the speech signals of isolated spoken words. And, Hidden Markov Model (HMM) method is applied to train and test the audio files to get the recognized spoken word.

Proc. Workshop in Image and Signal Processing (WISP-2007)

This paper discusses a Text-To-Speech (TTS) synthesis system embedded in a mobile. The TTS system used is unit selection based concatenative speech synthesizer, where a speech unit is selected from the database based on its phonetic and prosodic context. Speech unit considered in the synthesis is larger than a phone, diphone and syllable. Usually the unit is a word or a phrase. While the quality of the synthesized speech has improved significantly by using corpus-based TTS technology, there is a practical problem regarding the trade-off between database size and quality of synthetic speech, especially in mobile environment. Several speech compression schemes currently used in mobiles today are applied on the database. Speech is synthesized from the input text, using compressed speech in the database, The intelligibility and naturalness of the synthesized speech are studied. Mobiles contain a speech codec, one of the modules in the baseband processing. The idea of this paper is to propose a methodology to use the already available speech codec in the mobile and read a SMS aloud to the listener, when TTS is embedded in a mobile. Experimental results show the clear possibility of our idea.

International Journal of Computer Applications, 2013

This paper presents a novel Pashto text-to-speech (TTS) synthesis system based on data driven techniques such as Classification and Regression Tree (CART), Bigrams, and Non Uniform Units (NUUs). A modular concatenative TTS system has been developed for the Pashto language. Speech synthesis is carried out through a series of steps with the intention to provide a gradually more absolute transcription of the text, from which the final speech signal is then generated. The steps can be divided into two modules; a Natural Language Processing (NLP) module and a Digital Signal Processing (DSP) module. These steps incrementally enhance the information derived from the input and put it on a generally accessible internal data structure. The goal is to obtain enough information on the internal data structure so as to be capable to obtain an intelligible and natural speech.