High quality speech at low bit rates (e.g., 2400 bits/s) is one of the important objectives of current speech research. As part of long range activity on this problem, we have developed an efficient computer program that will serve as a tool for investigating whether articulatory speech synthesis may achieve this low bit rate. At a sampling frequency of 8 kHz, the most comprehensive version of the program, including nasality and frication, runs at about twice real time on a Cray-1 computer.

This paper reviews methods for mapping from the acoustical properties of a speech signal to the geometry of the vocal tract that generated the signal. Such mapping techniques are studied for their potential application in speech synthesis, coding, and recognition. Mathematically, the estimation of the vocal tract shape from its output speech is a so-called inverse problem, where the direct problem is the synthesis of speech from a given time-varying geometry of the vocal tract and glottis. Different mappings are discussed: mapping via articulatory codebooks, mapping by nonlinear regression, mapping by basis functions, and mapping by neural networks. Besides being nonlinear, the acoustic-to-geometry mapping is also nonunique, i.e., more than one tract geometry might produce the same speech spectrum. We will show how this nonuniqueness can be alleviated by imposing continuity constraints.

The new AT&T Text-To-Speech (TTS) system for general U.S. English text is based on best-choice components of the AT&T Flextalk TTS, the Festival System from the University of Edinburgh, and ATR's CHATR system. From Flextalk, it employs text normalization, letter-to-sound, and prosody generation. Festival provides a flexible and modular architecture for easy experimentation and competitive evaluation of different algorithms or modules. In addition, we adopted CHATR's unit selection algorithms and modified them in an attempt to guarantee high intelligibility under all circumstances. Finally, we have added our own Harmonic plus Noise Model (HNM) backend for synthesizing the output speech. Most decisions made during the research and development phase of this system were based on formal subjective evaluations. We feel that the new system goes a long way toward delivering on the long-standing promise of truly natural-sounding, as well as highly intelligible, synthesis.

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