In the last decade there has been a shift towards development of speech synthesizer using concatenative synthesis technique instead of parametric synthesis. There are a number of different methodologies for concatenative synthesis like TDPSOLA, PSOLA, and MBROLA. This paper, describes a concatenative speech synthesis system based on Epoch Synchronous Non Over Lapp Add (ESNOLA) technique, for st...

This paper describes the development of a speech synthesis voice with a southern Swedish accent. The voice is built for the Festival speech synthesis system using the tools in the festvox suite. The voice type is clustergen, which is a statistical­parametrical synthesis method where parametrical models for phonemes, duration and pitch all are built from a labeled speech d...

HMM-based statistical speech synthesis method is not requiring a very large speech corpus for training the system. In this system, statistical modeling is applied to learn distributions of context-dependent acoustic vectors extracted from speech signals, each vector containing a suitable parametric representation of one speech frame and Vietnamese phonetic rules to synthesize speech. The method...

Concatenation of acoustic units is widely used in most of the currently available text-to-speech systems. While this approach leads to higher intelligibility and naturalness than synthesis-by-rule, it has to cope with the issues of concatenating acoustic units that have been recorded in a di erent order. One important issue in concatenation is that of synchronization of speech frames or, in oth...

Present study in speech synthesis places more and more emphasis on the spectral continuities and diverse prosodic effects. The trainable HMM-based speech synthesis method tends to generate more continuous spectral structures than the traditional unit selection method. However, the F0 trajectory generated by HMM-based speech synthesis is often excessively smoothed and lacks prosodic variance. Th...

In this paper we present a speech synthesis method for diphonebased text-to-speech systems. Its main goal is to achieve prosodic modifications that result in more natural-sounding synthetic speech. This improvement is especially useful for emotional speech synthesis, which requires high-quality prosodic modification. We present a hybrid method based on TD-PSOLA and the harmonic plus noise model...

This paper proposes a method to detect the errors in synthetic speech of a unit selection speech synthesis system automatically using log likelihood ratio and support vector machine (SVM). For SVM training, a set of synthetic speech are firstly generated by a given speech synthesis system and their synthetic errors are labeled by manually annotating the segments that sound unnatural. Then, two ...

This paper presents a novel non-native speech synthesis technique that preserves the individuality of a non-native speaker. Cross-lingual speech synthesis based on voice conversion or HMM-based speech synthesis, which synthesizes foreign language speech of a specific non-native speaker reflecting the speaker-dependent acoustic characteristics extracted from the speaker’s natural speech in his/h...

An image-based approach provides an eficient way for visual speech synthesis. In an image-based visual speech synthesis system, a few lip images, namely visemes, are used for generating an arbitrary new sentence. Many approaches select visemes manually. In this papel; we propose a method for a system to automatically select visemes by minimizing the synthesis error The feasibility of the propos...

This paper describes conversational spontaneous speech synthesis based on hidden Markov model (HMM). To reduce the amount of data required for model training, we utilize an average-voice-based speech synthesis framework, which has been shown to be effective for synthesizing speech with arbitrary speaker’s voice using a small amount of training data. We examine several kinds of average voice mod...