2020
DOI: 10.1111/2041-210x.13475
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Using intrinsic and contextual information associated with automated signal detections to improve call recognizer performance: A case study using the cryptic and critically endangered Night Parrot Pezoporus occidentalis

Abstract: 1. Rapid expansion in the collection of large acoustic datasets to answer ecological questions has generated a parallel requirement for techniques that streamline analysis of these datasets. In many cases, automated signal recognition algorithms, often termed 'call recognizers', are the only feasible option for doing this. To date, most research has focused on what types of recognizers perform best, and how to train these recognizers to optimize performance. 2. We demonstrate that once recognizer construction … Show more

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Cited by 10 publications
(9 citation statements)
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“…To assess whether the relationships are similar, we grouped the different call types into three broad categories of call type: 'bell-like', 'short whistle' and 'long whistle'. Previous research has demonstrated consistent relationships between score and call type within these groups (Leseberg et al 2020). The call type data set contained 406 bell-like calls, 96 long whistle calls and 483 short whistle calls.…”
Section: Relationship Between Call Typesmentioning
confidence: 83%
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“…To assess whether the relationships are similar, we grouped the different call types into three broad categories of call type: 'bell-like', 'short whistle' and 'long whistle'. Previous research has demonstrated consistent relationships between score and call type within these groups (Leseberg et al 2020). The call type data set contained 406 bell-like calls, 96 long whistle calls and 483 short whistle calls.…”
Section: Relationship Between Call Typesmentioning
confidence: 83%
“…Furthermore, the large data sets collected require a call recogniser to extract potential Night Parrot calls. While statistics around the precision and recall of one Night Parrot call recogniser have been established (Leseberg et al 2020), how these relate to the detection radius of the ARUs has not been investigated.…”
Section: Research Problemmentioning
confidence: 99%
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“…Context is important when evaluating recogniser performance (Knight et al 2017;Leseberg et al 2020). Performance metrics should be considered reliable only under the environmental conditions in which they were F-score is a performance metric for automated signal detection that allows the user to prioritise precision and/or recall.…”
Section: Discussionmentioning
confidence: 99%
“…While this decreases the total work somewhat, there is still a large time burden involved with listening to the audio. Passive acoustic monitoring is increasingly being applied to monitor Australian birds particularly in conservation contexts (e.g., Leseberg et al, 2020;Teixeira et al, 2021).…”
Section: Introductionmentioning
confidence: 99%