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

Harmonic Plus Noise Model for Concatenative Speech Synthesis

This project develops the new model Harmonic Plus Noise applied for the concatenative speech synthesis. The software is composed of an analysis part (off-line process) applied on the first initial database and a synthesis part (real time process) applied on the HNM database and the prododic modifications from FESTIVAL. The future work consists of the integretion into the HMM-based speech synthesis

The "Tiepstem" : an experimental Dutch keyboard-to-speech system for the speech impaired

An experimental Dutch keyboard-to-speech system has been developed to explor the possibilities and limitations of Dutch speech synthesis in a communication aid for the speech impaired. The system uses diphones and a formant synthesizer chip for speech synthesis. Input to the system is in pseudo-phonetic notation. Intonation contours using a declination line and various rises and falls are generated starting from an input consisting of punctuation and accent marks. The hardware design has resulted in a small, portable and battery-powered device. A short evaluation with users has been carried out, which has shown possibilities for such a device but has also indicated some problems with the current pseudo-phonetic input

Developing a Child Friendly Text-to-Speech System

This paper discusses the implementation details of a child friendly, good quality, English text-to-speech (TTS) system that is phoneme-based, concatenative, easy to set up and use with little memory. Direct waveform concatenation and linear prediction coding (LPC) are used. Most existing TTS systems are unit-selection based, which use standard speech databases available in neutral adult voices. Here reduced memory is achieved by the concatenation of phonemes and by replacing phonetic wave files with their LPC coefficients. Linguistic analysis was used to reduce the algorithmic complexity instead of signal processing techniques. Sufficient degree of customization and generalization catering to the needs of the child user had been included through the provision for vocabulary and voice selection to suit the requisites of the child. Prosody had also been incorporated. This inexpensive TTS system was implemented in MATLAB, with the synthesis presented by means of a graphical user interface (GUI), thus making it child friendly. This can be used not only as an interesting language learning aid for the normal child but it also serves as a speech aid to the vocally disabled child. The quality of the synthesized speech was evaluated using the mean opinion score (MOS)

The Unsupervised Acquisition of a Lexicon from Continuous Speech

We present an unsupervised learning algorithm that acquires a natural-language lexicon from raw speech. The algorithm is based on the optimal encoding of symbol sequences in an MDL framework, and uses a hierarchical representation of language that overcomes many of the problems that have stymied previous grammar-induction procedures. The forward mapping from symbol sequences to the speech stream is modeled using features based on articulatory gestures. We present results on the acquisition of lexicons and language models from raw speech, text, and phonetic transcripts, and demonstrate that our algorithm compares very favorably to other reported results with respect to segmentation performance and statistical efficiency.Comment: 27 page technical repor

EMG-to-Speech: Direct Generation of Speech from Facial Electromyographic Signals

The general objective of this work is the design, implementation, improvement and evaluation of a system that uses surface electromyographic (EMG) signals and directly synthesizes an audible speech output: EMG-to-speech

Development of a Yoruba Text-to-Speech System Using Festival

This paper presents a Text-to-Speech (TTS) synthesis system for Yorúbà language using the open-source Festival TTS engine. Yorúbà being a resource scarce language like most African languages however presents a major challenge to conventional speech synthesis approaches, which typically require large corpora for the training of such system. Speech data were recorded in a quiet environment with a noise cancelling microphone on a typical multimedia computer system using the Speech Filing System software (SFS), analysed and annotated using PRAAT speech processing software. Evaluation of the system was done using the intelligibility and naturalness metrics through mean opinion score. The result shows that the level of intelligibility and naturalness of the system on word-level is 55.56% and 50% respectively, but the system performs poorly for both intelligibility and naturalness test on sentence level. Hence, there is a need for further research to improve the quality of the synthesized speech. Keywords: Text-to-Speech, Festival, Yorúbà, Syllabl