Constructing a phonetic-rich speech corpus while controlling time-dependent voice quality variability for English speech synthesis

This paper presents a practical approach to constructing a large-scale speech corpus for corpus-based speech synthesis. This consists of (1) selecting a source text corpus that fits limited target domains; (2) analyzing the source text corpus to obtain the unit statistics; (3) automatically extracting prompt subjects (sentences) from the source text corpus to maximize the intended unit coverage with the given amount of text; and (4) recording prompt subjects while controlling such critical factors that cause undesirable voice variability. This paper describes related computational methods, such as a greedy algorithm for prompt selection, the proximity effects found in a real recording system, and a technique for detecting the time-dependent voice variations. While the approach is demonstrated in English, it is also promising for other languages.