title: Call recognition and individual identification of fish vocalizations based on automatic speech recognition: An example with the Lusitanian toadfish.
abstract: 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.
authors.affiliation: Departamento de Biologia Animal and cE3c - Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa, Bloco C2. Campo Grande, 1749-016 Lisboa, Portugal.
authors.forename: Manuel
authors.initials: M
authors.lastname: Vieira
authors.affiliation: Departamento de Biologia Animal and cE3c - Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa, Bloco C2. Campo Grande, 1749-016 Lisboa, Portugal.
authors.forename: Paulo J
authors.initials: PJ
authors.lastname: Fonseca
authors.affiliation: MARE-Marine and Environmental Sciences Centre, ISPA-Instituto Universitário, Rua Jardim do Tabaco 34, 1149-041 Lisboa, Portugal.
authors.forename: M Clara P
authors.initials: MC
authors.lastname: Amorim
authors.affiliation: Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, Bloco C6. Campo Grande, 1749-016 Lisboa, Portugal.
authors.forename: Carlos J C
authors.initials: CJ
authors.lastname: Teixeira
mesh_terms: D000162:Acoustics; D000818:Animals; D024541:Batrachoidiformes / Q000145:classification / Q000502:physiology*; D017753:Ecosystem; D006801:Humans; D008297:Male; D008390:Markov Chains; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D012726:Sexual Behavior, Animal; D012815:Signal Processing, Computer-Assisted; D013018:Sound Spectrography; D013061:Speech Acoustics; D013068:Speech Production Measurement / Q000379:methods*; D014828:Vocalization, Animal