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1. Evolution and plasticity: Divergence of song discrimination is faster in birds with innate song than in song learners in Neotropical passerine birds: EVOLUTION OF SONG DISCRIMINATION IN NEOTROPICAL BIRDS

   https://doi.org/10.1111/evo.13311  

   Freeman, Benjamin G.; Montgomery, Graham A.; Schluter, Dolph (September 2017, Evolution)
2. Cooperative breeding in songbirds promotes female song but slows the evolution of song elaboration

   https://doi.org/10.1101/2024.06.26.600822  

   Snyder, Kate T; Loughran-Pierce, Aleyna; Creanza, Nicole (June 2024, bioRxiv)

   Bird song has historically been characterized as a primarily male behavior that evolves through sexual selection pressures involved in mate attraction. More recently, researchers showed that female song is far more prevalent in songbirds than previously thought, raising new questions about how other social functions of birdsong and sexual selection pressures on females might affect song evolution. Certain breeding systems, particularly cooperative breeding, are hypothesized to change social dynamics and sexual selection pressures on males and females and may thus influence song evolution in both. Here, we construct a large-scale database synthesizing species-level information on the presence of female song, the characteristics of presumably male song, social variables, and breeding systems, and we perform comparative phylogenetic analyses. Our results suggest that cooperative breeding and female song co-occur significantly more than expected and exhibit co-evolutionary dynamics; in particular, cooperative breeding appears to decrease the likelihood that female song is lost. Notably, we find evidence that these trends might be linked to certain social features associated with cooperative breeding, including social bond stability, but not others, such as increased group size. In addition, we observe that song repertoire size appears to evolve more slowly in cooperative breeding lineages. Overall, our findings demonstrate that cooperative breeding may have complex and sex-specific effects on song evolution, maintaining female song while slowing the rate of male song elaboration, suggesting that song in cooperatively breeding species could function in ways that differ from the traditional mate-attraction paradigm and that lesser-studied functions of songs may be evolutionarily consequential. 

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3. Thanks to Song et al.

   https://doi.org/10.1016/j.tree.2021.08.001  

   Lowe, Winsor H.; Martin, Thomas E.; Skelly, David K.; Woods, H. Arthur (November 2021, Trends in Ecology & Evolution)
4. Effects of Inactivation of the Periaqueductal Gray on Song Production in Testosterone-Treated Male Canaries ( Serinus canaria )

   https://doi.org/10.1523/ENEURO.0048-20.2020  

   Haakenson, Chelsea M.; Balthazart, Jacques; Ball, Gregory F. (July 2020, eneuro)
5. Sequence-Based Explainable Hybrid Song Recommendation

   https://doi.org/10.3389/fdata.2021.693494  

   Damak, Khalil; Nasraoui, Olfa; Sanders, William Scott (July 2021, Frontiers in Big Data)

   Despite advances in deep learning methods for song recommendation, most existing methods do not take advantage of the sequential nature of song content. In addition, there is a lack of methods that can explain their predictions using the content of recommended songs and only a few approaches can handle the item cold start problem. In this work, we propose a hybrid deep learning model that uses collaborative filtering (CF) and deep learning sequence models on the Musical Instrument Digital Interface (MIDI) content of songs to provide accurate recommendations, while also being able to generate a relevant, personalized explanation for each recommended song. Compared to state-of-the-art methods, our validation experiments showed that in addition to generating explainable recommendations, our model stood out among the top performers in terms of recommendation accuracy and the ability to handle the item cold start problem. Moreover, validation shows that our personalized explanations capture properties that are in accordance with the user’s preferences. 

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