How are the speakers for a speech corpus selected? Again, this strongly depends on the application one has in mind. For the development of a speech synthesis system , experienced speakers, such as news readers or actors, are most appropriate. For the training and testing of recognition systems , on the other hand, the population of interest must be suitably sampled. There is no general agreement on the exact meaning of “suitable” in this context. One definition would amount to random sampling of the population of interest. This operationalisation usually results in different numbers of samples from subpopulations in the population of interest. For example, when the total population of army personnel is sampled, the subpopulation of women is likely to be poorly represented. In the case of the training and testing of a recognition system for the army, this female under-representation might seem to be acceptable, because the recogniser would have to deal mainly with male speakers. However, it may appear that some of the influential heavy duty users are women and then the recogniser should better be designed to handle the few but important women with the same performance as for men. In general, random sampling has the potential drawback that extremely large numbers of samples are needed to ensure that rare, but nevertheless important phenomena are included. When, where, and why rare phenomena may still be important depends on the application for which the corpus is collected. In the case of fundamental research, on the other hand, the aim is often to compare subpopulations in some respect, and then it would be more appropriate to draw an equal number of samples from all subpopulations of interest. Uniform sampling of all subpopulations of interest ensures that all relevant variation is included in the corpus with the smallest possible number of speakers. The application for which the speech corpus is collected not only determines the best sampling strategy, but it also influences the choice of speakers. For example, speech processing often involves spectral analysis of the recorded speech. Several analysis techniques, such as pitch extraction or formant extraction , are less accurate for high-pitched voices (women and children) than for low-pitched voices (men). If such analysis techniques are used and the sex of the speakers is of no concern for the research goal, it would thus be sensible to select only men for the speech corpus. In general, however, it is recommended to include all possible types of speakers in a speech corpus, unless there are imperative arguments to exclude specific speaker groups. Specifically, it is strongly recommended to include equal numbers of females and males in each corpus. Speaker characteristics, which are potentially important and should therefore be considered when selecting the speaker population are described and discussed below.
