Dear MARMAM Readers,
We are pleased to share the recent publication of the following paper in
Bioacoustics:
Susannah J. Buchan,Rodrigo Mahú,Jorge Wuth,Naysa Balcazar-Cabrera,Laura
Gutierrez,Sergio Neira &Néstor Becerra Yoma. "An unsupervised Hidden
Markov Model-based system for the detection and classification of blue
whale vocalizations off Chile". Bioacoustics, Published on line: January
15th, 2019. https://doi.org/10.1080/09524622.2018.1563758
ABSTRACT
In this paper, we present an automatic method, without human
supervision, for the detection and classification of blue whale
vocalizations from passive acoustic monitoring (PAM) data using Hidden
Markov Model technology implemented with a state-of-the-art machine
learning platform, the Kaldi speech processing toolkit. 157.5 hours of
PAM data were annotated for model training and testing, selected from a
dataset collected from the Corcovado Gulf, Chilean Patagonia in 2016.
The system obtained produced 85.3% accuracy for detection and
classification of a range of different blue whale vocalizations. This
system was then validated by comparing its unsupervised detection and
classification results with the published results of southeast Pacific
blue whale song phrase (“SEP2”) via spectrogram cross-correlation,
involving a dataset collected with a different hydrophone instrument.
The proposed system led to a reduction in the root mean square error
relative to published results as high as 80% when compared with
comparable methods employed elsewhere. This is a significant step in
advancing the monitoring of endangered whale populations in this region,
which remains poorly covered in terms of PAM and general ocean
observation. With further training, testing and validation, this system
can be applied to other target signals and regions of the world ocean.
Keywords: blue whale vocalizations, unsupervised detection and
classification, HMM, machine learning.
For any further information, please contact corresponding author:
Prof. Nestor Necerra Yoma at [email protected] or
[email protected]
Thank you and regards,
Nestor
--
Néstor Becerra Yoma, Ph.D.
Professor
Speech Processing and Transmission Lab
Department of Electrical Engineering
Universidad de Chile
Av. Tupper 2007, POBox 412-3
Santiago, Chile
Tel. +56 2 2 978 4205
E-mail: [email protected]
http://www.linkedin.com/in/nestor-becerra-yoma
http://www.lptv.cl
http://www.cmrsp.cl
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