The intent of this project is to permit humans to understand the grammar and meaning of bird songs. Recent advances in sensor arrays, computation, and computational linguistics finally make this long-sought goal achievable. The approach taken in this proposal is to: (1) collect very large amounts of bird song recordings from acoustic sensor arrays in a variety of natural settings; (2) process the data by software, some of which is recent and some of which will be developed using new advances in localizing source with beamforming, then filtering out noise, identifying events of interest, and then classifying them according to species and individual, and combining that with behavioral observations; (3) this information/knowledge will then be stored in a large database that can be shared among the collaborating research groups; and (4) it will be analyzed by computational-linguistic tools to identify the syntax of the songs, and combined with information about the context in which it occurred, then analyzed by new software methods to identify the meaning of those songs. The project begins testing inferences from those inferences and explore consequences for individual and community ecology.
The research will be transformational in several ways. First, it will contribute to a profound transformation that is already underway: the recognition of very sophisticated signaling strategies and syntactic structures in non-human species. The new tools and methods for collecting and analyzing bird song now allow a level of observation that previously would not have been possible. Scientists are now collecting truly vast amounts of data from previously inaccessible settings and subjecting data to previously undiscovered sophisticated structural analyses. It will be transformational to computational linguistics if the natural world beyond humans were shown to have languages that are radically different from our own (as seems quite likely). In addition, the project will radically expand the range of engineering with voice recognition and classification, which so far has been restricted almost exclusively to humans.
Other contributions will come from the database that will comprise huge amounts of data pertaining to bird songs and the environmental/behavioral context in which it occurs. Offering both thematic and outreach contributions, the project will bring together people from engineering, ecology, linguistics and art -- and from the US, Mexico and Japan. The educational part will bring together underserved K6-12 students with the research community and will involve them with well-established educational programs in engineering, biology and art | science. While the science portion of this project is high-payoff --- high-risk, the outreach portion will certainly be effective at furthering appreciation and learning of science.
