We tested the influence of fundamental oscillation (fo) on human and machine speaker recognition performance in vocalic test utterances. In experiment I, we trained a Gaussian-Mixture model on 15 speakers (80 multi-word utterances each) and tested it with sustained vowel utterances (/a:/, /i:/ and /u:/) under six fo conditions, three changing (fall, rise, fall-rise) and three steady-state (high, mid, low). Results revealed better performance for the steady-state compared to the changing conditions and within the steady-state condition, performance was poorest for high fo. In experiment II, we tested 9 human listeners on a subset of 4 speakers from experiment I. They went through two training tasks (training 1: multi-word utterances; training 2: words). In the test, they recognized speakers based on the same vocalic utterances as in experiment I (for these 4 speakers). Results showed that performance was about equally high for the changing and steady-state vowels, however, in the steady-state condition performance was best for high fo vowels. The experiments suggest that (a) fo has an influence on the strength of speaker specific characteristics in vowels and (b) humans - compared to machines - pay attention to different acoustic information in vocalic utterances for speaker recognition.

Existing databases of isolated vowel sounds or vowel sounds embedded in consonantal context generally document only limited variation of basic production parameters. Thus, concerning the possible variation range of vowel and voice quality-related sound characteristics, there is a lack of broad phenomenological and descriptive references that allow for a comprehensive understanding of vowel acoustics and for an evaluation of the extent to which corresponding existing approaches and models can be generalised. In order to contribute to the building up of such references, a novel database of vowel sounds that exceeds any existing collection by size and diversity of vocalic characteristicsis presented here, comprised of c. 34600 utterances of 70 speakers (46 nonprofessional speakers, children, women and men, and 24 professional actors/actresses and singers of straight theatre, contemporary singing, and European classical singing). The database focuses on sounds of the long Standard German vowels /i–y–e–ø–ɛ–a–o–u/ produced with varying basic production parameters such as phonation type, vocal effort, fundamental frequency, vowel context and speaking or singing style. In addition, a read text and, for professionals, songs are also included. The database is accessible for scientific use, and further extensions are in progress.

Call-by-need is widely regarded as an optimal (to within a constant factor) parameter passing mechanism for functional programming languages. Except for certain special cases involving higher order functions, call-by-need is optimal with respect to time. However, call-by-need is far from optimal with respect to space. We examine some of the space problems which can arise with call-by-need and other parameter passing mechanisms. A simple optimizing technique, based on work by Mycroft [1], is proposed. If it can be determined both that an expression must be evaluated eventually and that the evaluation of the expression is likely to reduce the space required by the program, then the evaluation is performed as soon as possible. This optimization does not result in optimal space performance in all cases. However, in most of the common cases where call-by-need causes a problem the proposed optimization avoids the problem. Since our technique is not always optimal, it is likely to be of greatest advantage in situations where efficiency is important but not critical. For example, functional languages with call-by-name semantics are increasingly being used as specification languages. Since such a specification is runnable, it may be used as a prototype. This makes it possible to experiment with a program and refine the specification before the implementation in the target language is started.