Discerning pig screams in production environments

Pig vocalisations convey information about their current state of health and welfare. Continuously monitoring these vocalisations can provide useful information for the farmer. For instance, pig screams can indicate stressful situations. When monitoring screams, other sounds can interfere with scream detection. Therefore, identifying screams from other sounds is essential. The objective of this study was to understand which sound features define a scream. Therefore, a method to detect screams based on sound features with physical meaning and explicit rules was developed. To achieve this, 7 hours of labelled data from 24 pigs was used. The developed detection method attained 72% sensitivity, 91% specificity and 83% precision. As a result, the detection method showed that screams contain the following features discerning them from other sounds: a formant structure, adequate power, high frequency content, sufficient variability and duration

A cross-species judgement bias task: integrating active trial initiation into a spatial Go/No-go task

Abstract Judgement bias tasks are promising tools to assess emotional valence in animals, however current designs are often time-consuming and lack aspects of validity. This study aimed to establish an improved design that addresses these issues and can be used across species. Horses, rats, and mice were trained on a spatial Go/No-go task where animals could initiate each trial. The location of an open goal-box, at either end of a row of five goal-boxes, signalled either reward (positive trial) or non-reward (negative trial). Animals first learned to approach the goal-box in positive trials (Go) and to re-initiate/not approach in negative trials (No-go). Animals were then tested for responses to ambiguous trials where goal-boxes at intermediate locations were opened. The Go:No-go response ratio was used as a measure of judgement bias. Most animals quickly learned the Go/No-go discrimination and performed trials at a high rate compared to previous studies. Subjects of all species reliably discriminated between reference cues and ambiguous cues, demonstrating a monotonic graded response across the different cue locations, with no evidence of learning about the outcome of ambiguous trials. This novel test protocol is an important step towards a practical task for comparative studies on judgement biases in animals

Canine Sense and Sensibility: Tipping Points and Response Latency Variability as an Optimism Index in a Canine Judgement Bias Assessment

Recent advances in animal welfare science used judgement bias, a type of cognitive bias, as a means to objectively measure an animal's affective state. It is postulated that animals showing heightened expectation of positive outcomes may be categorised optimistic, while those showing heightened expectations of negative outcomes may be considered pessimistic. This study pioneers the use of a portable, automated apparatus to train and test the judgement bias of dogs. Dogs were trained in a discrimination task in which they learned to touch a target after a tone associated with a lactose-free milk reward and abstain from touching the target after a tone associated with water. Their judgement bias was then probed by presenting tones between those learned in the discrimination task and measuring their latency to respond by touching the target. A Cox's Proportional Hazards model was used to analyse censored response latency data. Dog and Cue both had a highly significant effect on latency and risk of touching a target. This indicates that judgement bias both exists in dogs and differs between dogs. Test number also had a significant effect, indicating that dogs were less likely to touch the target over successive tests. Detailed examination of the response latencies revealed tipping points where average latency increased by 100% or more, giving an indication of where dogs began to treat ambiguous cues as predicting more negative outcomes than positive ones. Variability scores were calculated to provide an index of optimism using average latency and standard deviation at cues after the tipping point. The use of a mathematical approach to assessing judgement bias data in animal studies offers a more detailed interpretation than traditional statistical analyses. This study provides proof of concept for the use of an automated apparatus for measuring cognitive bias in dogs