While a baby's cry can worry a parent, at the same time it can be irritating too. A group of researchers in the US has come up with a new artificial intelligence method which is capable of identifying and differentiating normal and abnormal cries.
The method can detect whether the cry is because of hunger, illness or something else. The research was published in the IEEE/CAA Journal of Automatica Sinica (JAS).
While each baby's cry is unique, they share some common features when they result from the same reasons.
The new research uses a specific algorithm based on automatic speech recognition to detect and recognize the features of infant cries.
In order to analyze and classify those signals, the team used compressed sensing as a way to process big data more efficiently. Compressed sensing is a process that reconstructs a signal based on sparse data and is especially useful when sounds are recorded in noisy environments, which is where the baby cries typically take place.
For the study, the researchers designed a new cry language recognition algorithm which can distinguish the meanings of both normal and abnormal cry signals in a noisy environment.
The algorithm is independent of the individual crier, meaning that it can be used in a broader sense in practical scenarios as a way to recognize and classify various cry features and better understand why babies are crying and how urgent the cries are.
"Like a special language, there are lots of health-related information in various cry sounds. The differences between sound signals actually carry the information," said Lichuan Liu, corresponding author.
Liu added, "These differences are represented by different features of the cry signals. To recognize and leverage the information, we have to extract the features and then obtain the information in it."
"The ultimate goals are healthier babies and less pressure on parents and care givers," added Liu.