A Review of Concatenative text To Speech Synthesis

Speech synthesis is the artificial production of human speech. Attempts to control the quality of voice of synthesized speech have existed for more than a decade now. Several prototypes and fully operating systems also have been built based on different synthesis technique. This article reviews recent advances in research and development of speech synthesis with focus on one of the key approaches i.e. statistical parametric approach to speech synthesis based on HMM, so as to provide a technological perspective. In this approach, spectrum, excitation, and duration of speech are simultaneously modeled by context dependent HMMs, and speech waveforms are generated from the HMMs themselves. This paper aims to give an overview of what has been done in this field, summarize and compare the characteristics of various speech synthesis techniques used.

2010

Abstract—In this paper, the main principles of text-to-speech synthesis system ,are presented. Associated problems ,which ,arise when,developing ,speech ,synthesis system ,are described. Used approaches and their application in the speech synthesis systems for Azerbaijani language are shown. Keywords—synthesis of Azerbaijani language, morphemes, phonemes, sounds, sentence, speech synthesizer, intonation, accent, pronunciation.

IEEE Transactions on Audio, Speech, and Language Processing, 2011

Concatenative synthesis and statistical synthesis are the two main approaches to text-to-speech (TTS) synthesis. Concatenative TTS (CTTS) stores natural speech features segments, selected from a recorded speech database. Consequently, CTTS systems enable speech synthesis with natural quality. However, as the footprint of the stored data is reduced, desired segments are not always available in the stored data, and audible discontinuities may result. On the other hand, statistical TTS (STTS) systems, in spite of having a smaller footprint than CTTS, synthesize speech that is free of such discontinuities. Yet, in general, STTS produces lower quality speech than CTTS, in terms of naturalness, as it is often sounding muffled. The muffling effect is due to over-smoothing of model-generated speech features. In order to gain from the advantages of each of the two approaches, we propose in this work to combine CTTS and STTS into a hybrid TTS (HTTS) system. Each utterance representation in HTTS is constructed from natural segments and model generated segments in an interweaved fashion via a hybrid dynamic path algorithm. Reported listening tests demonstrate the validity of the proposed approach. Index Terms-Concatenative text-to-speech (CTTS), dynamic path, hybrid TTS, statistical TTS, TTS synthesis. T HERE are two main approaches for solving the text-to-speech (TTS) paradigm. The first one uses recorded speech feature segments, which may be words, phonemes, or even sub-phonemes. This speech generation method is called concatenative TTS (CTTS). In this approach, speech is generated by concatenating the best compatible segments according to certain concatenation rules. Speech generated by this approach inherently possesses natural quality. However, its quality depends on the size of the recorded database, as high-quality CTTS needs an extensive database. The main disadvantage of CTTS is the possible appearance of discontinuities at segment boundaries due to imperfect concatenation. The smaller the size of the stored database, the larger is the number of discontinuities that typically appear in the generated speech. Thus, in applications where storage and computational resources are limited, such as in mobile Manuscript

This paper describes an approach to speech synthesis in which waveform fragments dynamically produced with a set of formant-based synthesis rules are concatenated with pre-stored natural speech waveform fragments to produce a synthetic utterance. While this hybrid approach was originally implemented as a tool for research into improved voice quality in formant-based synthesis, it has produced such good results that we now view it as a potentially viable and advantageous approach for a textto-speech product. Possible advantages of the approach include smaller speech databases for waveform concatenation, enhancement of certain speech cues for sub-optimal listening environments, and improved and more efficient unit selection/production. In addition, the approach has already proven its utility as a tool for research and development in both concatenative and formant-based synthesis.

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...

The most common, easy and feasible ways of communication is speech. Due to wide range of applications and physically disabled people requires an application to convert text to speech. Now a days Gujarati language is also widely used as a communication medium. Many systems has been developed so far to convert text to speech with one or more limitations. This review paper includes overview about text to speech systems developed for Gujarati language. The techniques to develop speech synthesizer are included. All individual technique is having limitations. So, to overcome these limitations, methodology is provided to develop a hybrid synthesizer for text to speech conversion for Gujarati Language. As a result, A good speech synthesizer achieves two quality measures of text to speech system: Naturalness and Intelligibility. The produced speech than pass through Super position algorithm developed using Formant Synthesizer and Timedomain Synthesizer to achieve more prosody on output and synthesized speech.

1995

Abstract Computer speech synthesis has reached a high level of performance, with increasingly sophisticated models of linguistic structure, low error rates in text analysis, and high intelligibility in synthesis from phonemic input. Mass market applications are beginning to appear. However, the results are still not good enough for the ubiquitous application that such technology will eventually have. A number of alternative directions of current research aim at the ultimate goal of fully natural synthetic speech.

International journal of engineering research and technology, 2013

Attempts to control the quality of voice of synthesized speech have existed for more than a decade now. Several prototypes and fully operating systems have been built based on different synthesis technique. This article reviews recent research advances in R&D of speech synthesis with focus on one of the key approaches i.e. statistical parametric approach to speech synthesis based on HMM, so as to provide a technological perspective. In this approach, spectrum, excitation, and duration of speech are simultaneously modeled by context –dependent HMMs, and speech waveforms are generated from the HMMs themselves. This paper aims to give an overview of what has been done in this field, summarize and compare the characteristics of various synthesis techniques used. It is expected that this study shall be a contribution in the field of speech synthesis and enable identification of research topic and applications which are at the forefront of this exciting and challenging field.

This research paper addresses the problem of improving the intelligibility of the synthesized speech in Marathi TTS synthesis system. The human speech is artificially generated by Speech synthesis. The normal language text will be automatically converted into speech using Text-to-speech system. This research paper deals with a corpus-driven Marathi TTS system based on the concatenative synthesis approach. Concatenative speech synthesis involves the concatenation of the basic units to synthesize an intelligent, natural sounding speech. In this paper syllables are the basic unit of speech synthesis database and the modification of syllable pitch by time scale modification. The speech units are annotated with associated prosodic information about each unit, manually or automatically, based on an algorithm. An annotated speech corpus utilizes the clustering technique that provides way to select the suitable unit for concatenation, depends on the minimum total join cost of the speech unit. The entered text file is analyzed first, this syllabication is performed based on the linguistics rules and the syllables are stored separately. Then the syllable corresponding speech file is concatenated and the silence present in the concatenated speech is removed. After that discontinuities are minimized at syllable boundaries without degrading the quality. Smoothing at the concatenatedsyllable boundary is performed and changing the syllable pitches by time scale modification.