Application of speech recognition to African elephant (Loxodonta Africana) vocalizations

Patrick J. Clemins, Michael T. Johnson

Research output: Contribution to journalConference articlepeer-review

9 Scopus citations


This paper presents a novel application of speech processing research, classification of African elephant vocalizations. Speaker identification and call classification experiments are performed on data collected from captive African elephants in a naturalistic environment. The features used for classification are 12 Mel-Frequency Cepstral Coefficients plus log energy computed using a shifted filter bank to emphasize the infrasound range of the frequency spectrum used by African elephants. Initial classification accuracies of 83.8% for call classification and 88.1% for speaker identification were obtained. The long-term goal of this research is to develop a universal analysis framework and robust feature set for animal vocalizations that can be applied to many species.

Original languageEnglish
Pages (from-to)484-487
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - 2003
Event2003 IEEE International Conference on Accoustics, Speech, and Signal Processing - Hong Kong, Hong Kong
Duration: Apr 6 2003Apr 10 2003

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


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