Methodological considerations concerning manual annotation of musical audio in function of algorithm development

In research on musical audio-mining, annotated music databases are needed which allow the development of computational tools that extract from the musical audiostream the kind of high-level content that users can deal with in Music Information Retrieval (MIR) contexts. The notion of musical content, and therefore the notion of annotation, is ill-defined, however, both in the syntactic and semantic sense. As a consequence, annotation has been approached from a variety of perspectives (but mainly linguistic-symbolic oriented), and a general methodology is lacking. This paper is a step towards the definition of a general framework for manual annotation of musical audio in function of a computational approach to musical audio-mining that is based on algorithms that learn from annotated data. 1

Language-trained animals: a window to the "black box"

Animals have to process quantity of information in order to take decisions and adapt their behaviors to their physical and social environment. They have to remember previous events (learning), to cope with their internal (motivational and emotional) states and to display flexible behavioral responses. From a human point of view it is quite impossible to access all those information, not only because of the sensorial channels used that can vary but also because all the processing phase occurs in the “black box” and non-human animals are not able to express verbally what they think, feel or want. Though useful information might lie in the “collected data” (animal mind), extracting them into insightful knowledge with human-accessible form (clear meaning, no interpretation) presents a demanding and sophisticated undertaking. Several scientists decided to trained different individuals from several species (apes, dolphins, grey parrots, dogs) in order to teach them a new communicative system that they could share with us. Here, the different studies (techniques and species used) are presented, their constrains but also the main findings