Study on phonetic context of Malay syllables towards the development of Malay speech synthesizer [TK7882.S65 H233 2007 f rb].

Pensintesis sebutan Bahasa Melayu telah berkembang daripada teknik pensintesis berparameter (pemodelan penyebutan manusia dan pensintesis berdasarkan formant) kepada teknik pensintesis tidak berparameter (pensintesis sebutan berdasarkan pencantuman). Speech synthesizer has evolved from parametric speech synthesizer (articulatory and formant synthesizer) to non-parametric synthesizer (concatenative synthesizer). Recently, the concatenative speech synthesizer approach is moving towards corpusbased or unit selection technique

BUCEADOR hybrid TTS for blizzard challenge 2011

This paper describes the Text-to-Speech (TTS) systems presented by the Buceador Consortium in the Blizzard Challenge 2011 evaluation campaign. The main system is a concatenative hybrid one that tries to combine the strong points of both statistical and unit selection synthesis (i.e. robustness and segmental naturalness respectively). The hybrid system has reached results significantly above average as far as similarity and naturalness are concerned, with no significant differences with most of the systems in the intelligibility task. This clearly improves the performance achieved in previous participations, and shows the validity of the hybrid approach proposed. Besides, an HMM-based system was built for the ES1 intelligibility tasks, using an HNM-based vocoder.Peer ReviewedPostprint (published version

A Parametric Approach for Efficient Speech Storage, Flexible Synthesis and Voice Conversion

During the past decades, many areas of speech processing have benefited from the vast increases in the available memory sizes and processing power. For example, speech recognizers can be trained with enormous speech databases and high-quality speech synthesizers can generate new speech sentences by concatenating speech units retrieved from a large inventory of speech data. However, even in today's world of ever-increasing memory sizes and computational resources, there are still lots of embedded application scenarios for speech processing techniques where the memory capacities and the processor speeds are very limited. Thus, there is still a clear demand for solutions that can operate with limited resources, e.g., on low-end mobile devices. This thesis introduces a new segmental parametric speech codec referred to as the VLBR codec. The novel proprietary sinusoidal speech codec designed for efficient speech storage is capable of achieving relatively good speech quality at compression ratios beyond the ones offered by the standardized speech coding solutions, i.e., at bitrates of approximately 1 kbps and below. The efficiency of the proposed coding approach is based on model simplifications, mode-based segmental processing, and the method of adaptive downsampling and quantization. The coding efficiency is also further improved using a novel flexible multi-mode matrix quantizer structure and enhanced dynamic codebook reordering. The compression is also facilitated using a new perceptual irrelevancy removal method. The VLBR codec is also applied to text-to-speech synthesis. In particular, the codec is utilized for the compression of unit selection databases and for the parametric concatenation of speech units. It is also shown that the efficiency of the database compression can be further enhanced using speaker-specific retraining of the codec. Moreover, the computational load is significantly decreased using a new compression-motivated scheme for very fast and memory-efficient calculation of concatenation costs, based on techniques and implementations used in the VLBR codec. Finally, the VLBR codec and the related speech synthesis techniques are complemented with voice conversion methods that allow modifying the perceived speaker identity which in turn enables, e.g., cost-efficient creation of new text-to-speech voices. The VLBR-based voice conversion system combines compression with the popular Gaussian mixture model based conversion approach. Furthermore, a novel method is proposed for converting the prosodic aspects of speech. The performance of the VLBR-based voice conversion system is also enhanced using a new approach for mode selection and through explicit control of the degree of voicing. The solutions proposed in the thesis together form a complete system that can be utilized in different ways and configurations. The VLBR codec itself can be utilized, e.g., for efficient compression of audio books, and the speech synthesis related methods can be used for reducing the footprint and the computational load of concatenative text-to-speech synthesizers to levels required in some embedded applications. The VLBR-based voice conversion techniques can be used to complement the codec both in storage applications and in connection with speech synthesis. It is also possible to only utilize the voice conversion functionality, e.g., in games or other entertainment applications

Prosody in text-to-speech synthesis using fuzzy logic

For over a thousand years, inventors, scientists and researchers have tried to reproduce human speech. Today, the quality of synthesized speech is not equivalent to the quality of real speech. Most research on speech synthesis focuses on improving the quality of the speech produced by Text-to-Speech (TTS) systems. The best TTS systems use unit selection-based concatenation to synthesize speech. However, this method is very timely and the speech database is very large. Diphone concatenated synthesized speech requires less memory, but sounds robotic. This thesis explores the use of fuzzy logic to make diphone concatenated speech sound more natural. A TTS is built using both neural networks and fuzzy logic. Text is converted into phonemes using neural networks. Fuzzy logic is used to control the fundamental frequency for three types of sentences. In conclusion, the fuzzy system produces f0 contours that make the diphone concatenated speech sound more natural

Application of singing synthesis techniquest to bertsolaritza

237 p

Natural-sounding speech synthesis using variable-length units

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (p. 112-115).by Jon Rong-Wei Yi.M.Eng

Application of singing synthesis techniquest to bertsolaritza

237 p

Fast Speech in Unit Selection Speech Synthesis

Moers-Prinz D. Fast Speech in Unit Selection Speech Synthesis. Bielefeld: Universität Bielefeld; 2020.Speech synthesis is part of the everyday life of many people with severe visual disabilities. For those who are reliant on assistive speech technology the possibility to choose a fast speaking rate is reported to be essential. But also expressive speech synthesis and other spoken language interfaces may require an integration of fast speech. Architectures like formant or diphone synthesis are able to produce synthetic speech at fast speech rates, but the generated speech does not sound very natural. Unit selection synthesis systems, however, are capable of delivering more natural output. Nevertheless, fast speech has not been adequately implemented into such systems to date. Thus, the goal of the work presented here was to determine an optimal strategy for modeling fast speech in unit selection speech synthesis to provide potential users with a more natural sounding alternative for fast speech output

Corpus-based unit selection for natural-sounding speech synthesis

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.Includes bibliographical references (p. 179-196).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Speech synthesis is an automatic encoding process carried out by machine through which symbols conveying linguistic information are converted into an acoustic waveform. In the past decade or so, a recent trend toward a non-parametric, corpus-based approach has focused on using real human speech as source material for producing novel natural-sounding speech. This work proposes a communication-theoretic formulation in which unit selection is a noisy channel through which an input sequence of symbols passes and an output sequence, possibly corrupted due to the coverage limits of the corpus, emerges. The penalty of approximation is quantified by substitution and concatenation costs which grade what unit contexts are interchangeable and where concatenations are not perceivable. These costs are semi-automatically derived from data and are found to agree with acoustic-phonetic knowledge. The implementation is based on a finite-state transducer (FST) representation that has been successfully used in speech and language processing applications including speech recognition. A proposed constraint kernel topology connects all units in the corpus with associated substitution and concatenation costs and enables an efficient Viterbi search that operates with low latency and scales to large corpora. An A* search can be applied in a second, rescoring pass to incorporate finer acoustic modelling. Extensions to this FST-based search include hierarchical and paralinguistic modelling. The search can also be used in an iterative feedback loop to record new utterances to enhance corpus coverage. This speech synthesis framework has been deployed across various domains and languages in many voices, a testament to its flexibility and rapid prototyping capability.(cont.) Experimental subjects completing tasks in a given air travel planning scenario by interacting in real time with a spoken dialogue system over the telephone have found the system "easiest to understand" out of eight competing systems. In more detailed listening evaluations, subjective opinions garnered from human participants are found to be correlated with objective measures calculable by machine.by Jon Rong-Wei Yi.Ph.D