Emotions play a crucial role in an animal's life because they facilitate responses to external or internal events of significance for the organism. In social species, one of the main functions of emotional expression is to regulate social interactions. There has recently been a surge of interest in animal emotions in several disciplines, ranging from neuroscience to evolutionary zoology. Because measurements of subjective emotional experiences are not possible in animals, researchers use neurophysiological, behavioural and cognitive indicators. However, good indicators, particularly of positive emotions, are still lacking. Vocalizations are linked to the inner state of the caller. The emotional state of the caller causes changes in the muscular tension and action of its vocal apparatus, which in turn, impacts on vocal parameters of vocalizations. By considering the mode of production of vocalizations, we can understand and predict how vocal parameters should change according to the arousal (intensity) or valence (positive/negative) of emotional states. In this paper, I review the existing literature on vocal correlates of emotions in mammals. Non‐human mammals could serve as ideal models to study vocal expression of emotions, because, contrary to human speech, animal vocalizations are assumed to be largely free of control and therefore direct expressions of underlying emotions. Furthermore, a comparative approach between humans and other animals would give us a better understanding of how emotion expression evolved. Additionally, these non‐invasive indicators could serve various disciplines that require animal emotions to be clearly identified, including psychopharmacology and animal welfare science.

Vocal expression of emotions has been observed across species and could provide a non-invasive and reliable means to assess animal emotions. We investigated if pig vocal indicators of emotions revealed in previous studies are valid across call types and contexts, and could potentially be used to develop an automated emotion monitoring tool. We performed an analysis of an extensive and unique dataset of low (LF) and high frequency (HF) calls emitted by pigs across numerous commercial contexts from birth to slaughter (7414 calls from 411 pigs). Our results revealed that the valence attributed to the contexts of production (positive versus negative) affected all investigated parameters in both LF and HF. Similarly, the context category affected all parameters. We then tested two different automated methods for call classification; a neural network revealed much higher classification accuracy compared to a permuted discriminant function analysis (pDFA), both for the valence (neural network: 91.5%; pDFA analysis weighted average across LF and HF (cross-classified): 61.7% with a chance level at 50.5%) and context (neural network: 81.5%; pDFA analysis weighted average across LF and HF (cross-classified): 19.4% with a chance level at 14.3%). These results suggest that an automated recognition system can be developed to monitor pig welfare on-farm.

Studying vocal correlates of emotions is important to provide a better understanding of the evolution of emotion expression through cross-species comparisons. Emotions are composed of two main dimensions: emotional arousal (calm versus excited) and valence (negative versus positive). These two dimensions could be encoded in different vocal parameters (segregation of information) or in the same parameters, inducing a trade-off between cues indicating emotional arousal and valence. We investigated these two hypotheses in horses. We placed horses in five situations eliciting several arousal levels and positive as well as negative valence. Physiological and behavioral measures collected during the tests suggested the presence of different underlying emotions. First, using detailed vocal analyses, we discovered that all whinnies contained two fundamental frequencies (“F0” and “G0”), which were not harmonically related, suggesting biphonation. Second, we found that F0 and the energy spectrum encoded arousal, while G0 and whinny duration encoded valence. Our results show that cues to emotional arousal and valence are segregated in different, relatively independent parameters of horse whinnies. Most of the emotion-related changes to vocalizations that we observed are similar to those observed in humans and other species, suggesting that vocal expression of emotions has been conserved throughout evolution.

Communicating emotions to conspecifics (emotion expression) allows the regulation of social interactions (e.g. approach and avoidance). Moreover, when emotions are transmitted from one individual to the next, leading to state matching (emotional contagion), information transfer and coordination between group members are facilitated. Despite the high potential for vocalizations to influence the affective state of surrounding individuals, vocal contagion of emotions has been largely unexplored in non-human animals. In this paper, I review the evidence for discrimination of vocal expression of emotions, which is a necessary step for emotional contagion to occur. I then describe possible proximate mechanisms underlying vocal contagion of emotions, propose criteria to assess this phenomenon and review the existing evidence. The literature so far shows that non-human animals are able to discriminate and be affected by conspecific and also potentially heterospecific (e.g. human) vocal expression of emotions. Since humans heavily rely on vocalizations to communicate (speech), I suggest that studying vocal contagion of emotions in non-human animals can lead to a better understanding of the evolution of emotional contagion and empathy.