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@article{172912,
        author = {Athira R Kurup and Dr.B.Ben Sujitha and Deva Mahilan},
        title = {Advancements in Infant Cry Classifications: A Literature Review on Methods and Systems},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {9},
        pages = {1386-1390},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172912},
        abstract = {The use of spoken language, a complex instrument developed over thousands of years, is one of the essential elements of human communication. Unfortunately, throughout the first several years of life, we still lack this ability to communicate; instead, we cry to express pain, hunger, and other emotions. The literature review highlights the importance of pitch, intensity, and length in classification, the impact of medical issues and prematurity on cry features, and foundational work on cry acoustics. There are still problems with noise reduction, dataset standardization, and practical implementation because of individual differences in kid screams and ambient unpredictability. This literature review looks at the current state of research in infant cry classification with a focus on how the technology can be used for the identification of early developmental diseases, emotional state, and medical diagnosis. Advanced machine learning algorithms, deep learning algorithms, and audio analysis methods have been developed in recent years which enable an automated system to distinguish between screams that are made due to pain, discomfort, hunger or any other emotional or physical state.},
        keywords = {Adaptive models, Annotated datasets, Automatic recognition, Cry analysis, Cry classification, Databases, Deep learning, Emotion detection, Ethical considerations, Feature fusion, Infant cry recognition, Lightweight algorithms, Machine learning, Multimodal approaches, Neural networks, Pain detection, Real-world applications, Signal processing, Transfer learning, Wavelet-based methods.},
        month = {February},
        }