新加坡Channel NewsAsia（CNA）正利用AI技術革新新聞編輯室，提升報道效率與質量。作爲覆蓋全球1.5億家庭和設備的媒體，CNA自2019年嘗試AI應用，總編輯Walter Fernandez認爲AI潛力巨大，將重塑新聞業。初期編輯們視AI爲輔助工具，強調其支持作用。
Cnam-LMSSC
基於Wav2Vec2架構的法語音素化模型，專門針對頭戴式麥克風音頻數據訓練，可將法語語音轉換為國際音標(IPA)音素序列。
這是一個針對法語語音轉音素任務微調的模型，基於facebook/wav2vec2-base-fr-voxpopuli-v2模型，使用Common Voice v13數據集進行訓練。
CNAP是一個基於Spring Boot和Vue.js 3的應用程序開發平臺，提供用戶管理、角色權限控制和可定製菜單等核心功能模塊，構建靈活可擴展的系統基礎架構。
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