The automatic analysis and detection of audio signals is an important field of research with promising applications in various biomedical engineering problems such as speech, heart murmur, and lung sound analysis and classification. In this regard, automatic classification of infant vocalizations is becoming an appealing research area for medical diagnosis in clinical milieu. Indeed, the analysis and classification of infant cry records is a conventional non-inva-sive technique to distinguish between healthy and unhealthy infants.

中文翻译：

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基于深度前馈人工神经网络倒谱分析的婴儿啼哭信号的生物医学诊断

音频信号的自动分析和检测是一个重要的研究领域，在各种生物医学工程问题（如语音，心脏杂音以及肺音分析和分类）中具有广阔的应用前景。在这方面，婴儿发声的自动分类正成为临床环境中医学诊断的吸引人的研究领域。的确，婴儿哭声记录的分析和分类是区分健康婴儿和不健康婴儿的常规非侵入性技术。