隨著科技日益進步，人工智慧的浪潮逐漸席捲各個產業，如何與其互利共生以追求高效率工作成為當今火紅的話題。在人力資源甄選的範疇中，何以精確地將「對的人」置於「對的位置」備受所有倚重人才的組織重視。考量到「適才適所」方能為組織帶來好的績效，個人能力的評分高低無法反映人才是否「合適」，故本研究以契合度作為評分依據。
本研究以研究所教授與學生之間的師徒關係建立為例執行實驗，結合非同步面試，以語音檔案取代書面履歷作為初步篩選的依據。實驗過程利用語音辨識技術將語音檔案轉換為文本，並使用Python撰寫一支以文字探勘技術為基礎之程式，對所有學生提交之檔案進行與導師的契合度評分，並以此評分結果整理為一推薦名單，實踐人才甄選的自動化。
實驗結果以「系統評」、「人資專員評」及「導師評」三方進行驗證，並採用肯德爾等級相關係數作為指標。結果證實「系統評」與「導師評」排序結果的距離為0.0667，而「人資專員評」與更「導師評」的排序結果落於0到0.2，整體而言，「系統評」較「人資專員評」更接近「導師評」的排序結果。
本研究執行的實驗係為參與此實驗之教授所期許條件量身打造，所構建之系統係遵照此位教授設下的需求條件執行評分，若教授有意增加條件，也僅需更新。不僅限於師徒關係的建立，由於所採納的評分條件為個人化設計，此模式亦可套用於企業徵才的過程。使用自動化契合度評分系統可以有效地避免面試官的主觀想法在甄選過程中造成的誤差，進而提供最客觀、公正之推薦人選。

With the advancement in technology, the application of artificial intelligence (AI) has received much attention. In the scope of Human Resource Management, many people pay attention to whether practitioners will be replaced by AI. However, if human-machine cooperation can be effectively utilized, the above-mentioned incident will not happen. Effectively working with AI can make the work more efficient.
This study conducted an asynchronous interview, and constructed an automated compatibility rating system to score each of the candidate in the experiment. In the process, speech recognition would be used to convert the recording files into texts. The automated compatibility rating system was written in Python base on text mining. The scores were sorted as a recommended list to fulfill the automation applied to human re-source selection.
The result of the experiment was verified by the system, human resource specialists, and the professor. By using the Kendall tau ranking distance as the evaluation, the distance between the system and the professor was 0.0667, while the one between the human resource specialists and the professor fell in 0-0.2. Overall, the rank of the system was closer to the professor’s than the human resource specialists’ rank.
The experiments performed in this study were tailored to the requirements expected by the professors participated in this study. The system is not limited to the mentorship establishment. Since the system was personalized design, it can also be applied to the selection of enterprise. Using the automated scoring system can effectively avoid the bias caused by the interviewer's subjective thoughts, and provide the most objective and fair recommended candidates.

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