Pretest of images associated with the expertise dimension

In this paper, we present norms concerning the perceived association that two sets of stimuli (photos of people and photos of objects) establish with the concept of expertise. Participants were presented with a set of words associated with the expertise dimension and subsequently asked to judge each stimulus on how much it related with the learned (expertise) dimension on a 7-point scale (1 – Not at all related; 7 – Very related). The interpretation of means’ confidence intervals allowed us to distinguish between images highly related with the expertise dimension and images highly unrelated with this dimension. Summarized results are presented and photos made available to support future research requiring stimuli associated with the expertise dimension.

Call recognition and individual identification of fish vocalizations based on automatic speech recognition: An example with the Lusitanian toadfish

The study of acoustic communication in animals often requires not only the recognition of species specific acoustic signals but also the identification of individual subjects, all in a complex acoustic background. Moreover, when very long recordings are to be analyzed, automatic recognition and identification processes are invaluable tools to extract the relevant biological information. A pattern recognition methodology based on hidden Markov models is presented inspired by successful results obtained in the most widely known and complex acoustical communication signal: human speech. This methodology was applied here for the first time to the detection and recognition of fish acoustic signals, specifically in a stream of round-the-clock recordings of Lusitanian toadfish (Halobatrachus didactylus) in their natural estuarine habitat. The results show that this methodology is able not only to detect the mating sounds (boatwhistles) but also to identify individual male toadfish, reaching an identification rate of ca. 95%. Moreover this method also proved to be a powerful tool to assess signal durations in large data sets. However, the system failed in recognizing other sound types.