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Artificial intelligence could translate dog vocalisation
Researchers adapted a tool previously trained for human speech.

Technology can distinguish between playfulness and aggression.

Researchers from the University of Michigan are exploring how artificial intelligence (AI) could be used to decipher dog barks.

The AI model has the potential to discover information from animal vocalisations, including the dog’s age, breed and sex. The researchers also believe it could identify if a bark is playful or aggressive.

The project saw researchers adapt a speech-processing model, which was previously trained to study human speech.

Through a collaboration with the National Institute of Astrophysics, Optics and Electronics (INAOE) Institute in Mexico, the team discovered that this model could act as a starting point for training new systems for animal communication.

The development of an AI model for animal vocalisations was previously hampered by the lack of public data. Although human samples are easy to record, there are more limitations when collecting animal recordings.

Researchers say that animal vocalisations are logistically more difficult to record as they either need to be recorded in the wild or, for domestic pets, with the permission of owners.

It was due to these limitations that researchers opted to instead repurpose an existing, human-oriented model.

Existing voice technologies, such as voice-to-text and language translation, are trained to identify the nuances of human speech. The tools are able to distinguish between tone, pitch and accent to translate speech and identify speakers.

The team adapted this model by using a dataset of dog vocalisations from 74 different dogs – of varying breed, age, sex and context. These recordings were then used to modify the machine-learning model.

Using this tool, researchers were able to generate and interpret acoustic representations from the dogs. The AI model not only passed four different classification tasks, but also outperformed other models specifically trained on dog barks with accuracy figures of up to 70 per cent.

Rada Mihalcea, from the University of Michigan’s AI laboratory, said: "This is the first time that techniques optimised for human speech have been built upon to help with the decoding of animal communication.

"Our results show that the sounds and patterns derived from human speech can serve as a foundation for analysing and understanding the acoustic patterns of other sounds, such as animal vocalisations."

The full study can be found here.

Image © Shutterstock

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Two new roles on BEVA Nurse Committee

News Story 1
 The BEVA has opened two new roles on its Nurse Committee.

There is one role available for a full member (for three years) and one role for a student member (until they qualify).

Members must attend all meetings, occurring four times a year. They will assist the committee in understanding the field, identifying issues and engaging with external parties.

More details can be found here

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BSAVA publishes Guide to Nutrition in Small Animal Practice

The BSAVA has added a small animal nutrition advice booklet to its series of BSAVA guides.

The BSAVA Guide to Nutrition in Small Animal Practice offers a resource for veterinary professionals to provide appropriate nutrition for animals. As well as maintaining the wellbeing of healthy pets, the guide explores how nutritional requirements change in times of illness and disease.

The guide is divided into five sections, which explore the importance of nutritional assessment; diet types; feeding at different life stages; feeding for specific situations; and feeding for specific diseases. Online resources are also in the BSAVA Library including client handouts and videos.

It is designed to be suitable for referencing, in-depth case planning and team training sessions.

The BSAVA Guide to Nutrition in Small Animal Practice can be purchased online from the BSAVA store.