The automatic conversion of English text to synthetic speech is presently being performed, remarkably well, by a number of laboratory systems and commercial devices. Progress in this area has been made possible by advances in linguistic theory, acoustic-phonetic characterization of English sound patterns, perceptual psychology, mathematical modeling of speech production, structured programming, and computer hardware design. This review traces the early work on the development of speech synthesizers, discovery of minimal acoustic cues for phonetic contrasts, evolution of phonemic rule programs, incorporation of prosodic rules, and formulation of techniques for text analysis. Examples of rules are used liberally to illustrate the state of the art. Many of the examples are taken from Klattalk, a text-to-speech system developed by the author. A number of scientific problems are identified that prevent current systems from achieving the goal of completely human-sounding speech. While the emphasis is on rule programs that drive a format synthesizer, alternatives such as articulatory synthesis and waveform concatenation are also reviewed. An extensive bibliography has been assembled to show both the breadth of synthesis activity and the wealth of phenomena covered by rules in the best of these programs. A recording of selected examples of the historical development of synthetic speech, enclosed as a 33 1/3-rpm record, is described in the Appendix.

Review of text‐to‐speech conversion for English

Pitch accent in context: predicting intonational prominence from text

Abstract Explaining speakers' choice of items to emphasize or de-emphasize intonationally has been an important topic in theoretical linguistics, as well as in applications such as speech synthesis, where accent decisions affect naturalness as well as interpretation. Heretofore, most researchers have assumed that detailed syntactic, semantic, and discourse-level information must be available in order for accent assignment to be predicted successfully. However, a series of recent experiments on corpora of recorded (read) speech and spontaneous (elicited) speech suggest that it is indeed possible to model human accent strategies with fair success (80–98% correct) for unrestricted text—with only the tools for automatic text analysis currently available. The algorithm developed from these experiments is currently used to assign pitch accent in the Bell Laboratories Text-to-Speech System.

Pitch accent in context: predicting international prominence from text

Improved automated synthesis of human audible speech from text is disclosed. Performance enhancement of the underlying text comprehensibility is obtained through prosodic treatment of the synthesized material, improved speaking rate treatment, and improved methods of spelling words or terms for the sysstem user. Prosodic shaping of text sequences appropriate for the discourse in large groupings of text segments, with prosodic boundaries developed to indicate conceptual units within the text groupings, is implemented in a preferred embodiment.

Automated voice synthesis employing enhanced prosodic treatment of text, spelling of text and rate of annunciation

Improved automated synthesis of human audible speech from text is disclosed. Performance enhancement of the underlying text comprehensibility is obtained through prosodic treatment of the synthesized material, improved speaking rate treatment, and improved methods of spelling words or terms for the system user. Prosodic shaping of text sequences appropriate for the discourse in large groupings of text segments, with prosodic boundaries developed to indicate conceptual units within the text groupings, is implemented in a preferred embodiment.

Methods for controlling the generation of speech from text representing names and addresses

A synthesis method, called speech synthesis from concept, is described which has been designed specifically for providing speech output from information systems. It differs from conventional techniques in that data is passed from the information system to the speech synthesis system, not in the form of text or phonetic transcription, but in the form of an abstract structure called an input concept. The speech synthesis from concept system converts an input concept into speech by using a transformational grammar to generate a well‐formed English sentence and a word concatenation synthesizer to generate the actual speech output. The ’’top down’’ nature of this process reduces the computation required within the information system and enables high‐quality speech to be produced.

S. J. Young

Papers

Speech synthesis from concept: A method for speech output from information systems