PAPER BRIEF · 研究快讀
給嬰兒哭聲分段——226 段哭聲裏的吸氣與呼氣
Construction and validation of an automated time label segmentation method for infant cries. · BMC pediatrics
嬰兒的哭聲是瞭解其生理與心理狀態的重要窗口，在早期發育階段區分正常與異常情況有臨牀價值。但多數哭聲研究在分析時沒有對"吸氣"與"呼氣"兩個階段做分段——這件事本身就很難。
這項研究開發了一個音頻數據分析工具，能夠對嬰兒哭聲中的吸氣與呼氣階段進行自動分割，並逐段提取時長、頻率和強度參數。研究共收集並分析了 226 段嬰兒哭聲：結果顯示，早產兒與足月兒的聲音參數存在顯著差異。整個流程實現了嬰兒哭聲的自動識別與數字化採集，爲理解哭聲背後的意義提供了一個客觀方法。
三點邊界必須寫清楚：其一，226 是哭聲音頻片段數，不是嬰兒人數；其二，這是方法構建與驗證研究，參數差異不等於診斷結論，涉及嬰幼兒的內容不作篩查、診斷類表述；其三，論文致謝中寫明感謝成都醫學院醫學聲音數據庫的支持，以及成都智矩數據科技有限公司的專業討論（professional discussion）——致謝表明公司提供了專業討論，不表明公司研發了該方法或擁有相關數據。CV 原題錄在徐帆姓名後標有 #；本文僅保留 CV 記載，符號含義與通訊作者身份以論文正式版本腳註爲準。
事實覈對邊界
- 226 段、吸/呼分段、三類參數、早產與足月差異均取自論文摘要（本地已核全文 XML）。
- 致謝原句取自論文 Acknowledgements 段，逐字照錄於證據臺賬。
- 公司口徑僅限"獲專業討論致謝"，數據庫歸屬爲成都醫學院。
- 作者姓名後的 # 爲 CV 原題錄標註，不據此獨立認定通訊作者身份。
AcknowledgementsAcknowledgments: We thank the undergraduate candidates SQC, WZH, LYF, who performed clinical examinations in community hospitals and provided valuable suggestions for this study. Dr Huang Kun provided valuable software segmentation experience for this study. The valuable support from the medical sound database from Chengdu Medical College (http://ama.cmc.edu.cn) and professional discussion from Chengdu Zhiju Data Science Technology Co., Ltd. (www.zjdatast.cn).
論文摘要（原文）
Infant cries serve as critical indicators of an infant's physiological and psychological states, holding essential clinical value in distinguishing between normal and pathological conditions during early development. However, most studies on infant cries failed to segment between inhalation and exhalation during the crying analysis because segmentation remains great challenge. Therefore, we developed an audio data analysis tool capable of accurately segmenting inhalation and exhalation phases in infant cries, followed by extraction of the duration, frequency, and intensity parameters of each segment. Here, 226 sound clips of infants' cries were collected and analyzed. The results revealed the significant differences in sound parameters between premature and term infants. The whole process allows automatic identification and digital collection of infant cries, and it provides an objective method to evaluate the significance behind the cries.