Developing an Automatic Speech Recognition (ASR) system for the Somali language, though not novel, is not actively explored; hence there has been no success in a model for conversational speech. Neither are related works accessible as open-source. The unavailability of digital data is what labels Somali as a low resource language and poses the greatest impediment to the development of an ASR for Somali. The incentive to develop an ASR system for the Somali language is to contribute to reducing the Maternal Mortality Rate (MMR) in Somalia. Researchers acquire interview audio data regarding maternal health and behaviour in the Somali language; to be able to engage the relevant stakeholders to bring about the needed change, these audios must be transcribed into text, which is an important step towards translation into any language. This work investigates available ASR for Somali and attempts to develop a prototype ASR system to convert Somali audios into Somali text. To achieve this target, we first identified the available open-source systems for speech recognition and selected the DeepSpeech engine for the implementation of the prototype. With three hours of audio data, the accuracy of transcription is not as required and cannot be deployed for use. This we attribute to insufficient training data and estimate that the effort towards an ASR for Somali will be more significant by acquiring about 1200 hours of audio to train the DeepSpeech engine

背景與目的： 每一項疾病都有其潛在的風險，但要有效的降低死亡率及併發症發生率，必須找出關鍵性指標加以改善或預防。我們以心臟冠狀動脈繞道手術之患者為例，希望藉由統計分析的方式，找出造成死亡以及術後併發症最相關的因素，目的不只在預測，而在於防範。 研究對象與方法： 在我們的實驗設計上，風險因子分布在手術前、手術中、以及手術後三個階段，對象是某醫學中心接受心臟冠狀動脈繞道手術的220例患者。分析採用迴歸統計建立模型，其中羅吉斯迴歸中的依變數為死亡率與罹病率，線性迴歸的依變數為加護病房留置天數以及總住院日數。ROC curve亦將被建立，以判斷模型是否能區別病患是否罹病或死亡。所得資料亦計算EuroScore及其ROC曲線面積，並與歷史資料做比較。 結果： 所建立的死亡估計模型的有兩個，預測值都在97%以上，ROC曲線面積亦都超過0.96；併發症估計模型由六個變數所構成，預測率及ROC曲線面積分別為94%和0.984。加護病房留置天數及住院天數估計模型分別由八個及十三個因子來解釋，調整後的R square分別為0.527及0.6。EuroScore對死亡與併發症的預測率，分別為93.7%和82%，ROC曲線面積分別是0.864和0.797，均高於歷史文獻記錄，未來應該廣泛應用。 結論與建議： 經由適當的風險分級和危險因子分析，我們可以找出風險高低的標準和依據，了解影響死亡率與罹病率的關鍵因子是什麼，儘可能的做事前的防範與處置，希望能夠改善結果並提高手術的存活率。 EuroScore是個值得採用的預測工具，可以廣泛應用在死亡率與併發症發生率的估計，但是必須搭配風險因子的改善，才能發揮實際的功效。我們認為，體外循環時間與再次手術是最具有空間來降低死亡率與罹病率的兩個要素，有效率的控制時間、改善造成再手術的前因後果，除了死亡率與併發症發生率的下降外，還可以及早脫離對加護病房照顧的需求並減少留置的天數。