Background

某傳統製造業企業營運超過 30 年，業務流程中仍大量依賴紙本文件處理。從品質檢驗報告、進出貨單據、會議紀錄到客戶合約，各廠區每日都持續產出紙本資料。隨著企業規模擴大，紙本作業的效率瓶頸日益明顯，加上國際客戶對供應鏈數位化程度的要求提高，數位轉型已刻不容緩。

The company had previously attempted basic scan-and-archive solutions, but scanned images remained unsearchable, offering limited practical value. Furthermore, factory floor meetings and production instructions were largely communicated verbally, with no comprehensive written record — resulting in information gaps and difficulty tracking decisions.

Challenges Faced

• 歷年累積的數萬份紙本文件需要數位化處理，包含手寫表格、印刷文件與蓋章單據
• Traditional OCR tools have insufficient recognition accuracy for Chinese handwriting and complex tables
• Factory meetings and production instructions are communicated verbally, lacking a complete written record system
• On-site personnel communicate using a mix of Taiwanese and Mandarin, making speech recognition highly challenging
• Digitized data lacks intelligent management tools, preventing it from delivering its full value
• Varying levels of digital literacy among on-site personnel require an extremely simple and intuitive system interface

Industry Solutions

The company adopted LargitData's comprehensive digital transformation solution, integrating OCR (Optical Character Recognition), ASR (Automatic Speech Recognition), and AI-powered analytics to achieve a complete transition from paper-based operations to intelligent, data-driven workflows.

OCR Document Digitization

• 繁體中文 OCR：支援繁體中文印刷體與手寫體辨識；實際辨識品質會隨掃描解析度、字跡工整度、蓋章與手寫覆蓋、版面複雜度而不同，導入前建議以貴公司的真實文件抽樣試跑
• Complex Table Recognition: Automatically recognizes table structures and converts table content into structured data
• Batch Processing Capability: Supports automated batch scanning and recognition processing for large volumes of documents

OCR Optical Character Recognition →

ASR Speech-to-Text

• Multilingual Speech Recognition: Supports real-time recognition and transcription of mixed Mandarin and Taiwanese speech
• Meeting Records: Automatically converts meeting recordings into verbatim transcripts with summarization and key point extraction
• Production Instruction Records: on-site verbal commands are transcribed in real time into written records, ensuring full traceability

ASR Speech-to-Text →

AI-Powered Analysis and Knowledge Management

• Automated Document Review: AI automatically identifies document types and archives them to the appropriate directories
• Full-Text Search System: all digitized documents are searchable by full-text keyword queries
• Intelligent data analysis: structured data extracted from documents is consolidated into visual management dashboards

Implementation Results

• 本案的中文辨識準確率為 98%，測試範圍涵蓋該公司實際使用的手寫表格與含表格線的單據
• 文件從紙本到數位化的處理效率提升 75%，原本需要專人逐份鍵入的作業，改為批次掃描加人工覆核
• 會議紀錄 100% 數位化，部門會議與生產現場指令均以語音轉文字留存，資訊傳遞的可追溯性明顯提升
• 紙本列印與歸檔需求下降，實體檔案櫃的空間壓力獲得緩解
• 數位化資料搭配全文檢索系統，員工可直接以關鍵字定位文件內容，不必再翻找紙本卷宗
• 供應鏈文件具備可查詢的數位版本，回應客戶查核與追溯要求時的準備時間縮短

數字怎麼看：量測口徑與適用前提

上述 98%、75% 與 100% 是該專案在特定文件類型與特定期間下的量測結果，不宜直接視為所有場景的通用規格。以辨識準確率為例，同一套模型在乾淨的印刷體單據與潦草手寫欄位上的表現可能相差很大，而準確率究竟是以字元、欄位還是整份文件為單位計算，結論也會完全不同。

評估 OCR 與 ASR 方案時，建議向供應商確認四件事：第一，準確率的計算單位與測試集組成，最好要求以貴公司的真實文件重跑；第二，效率提升的分母包含哪些步驟，是否已扣除人工覆核與例外處理的時間；第三，語音辨識在國台語混用、現場噪音與多人同時發言下的表現，以及是否需要建立專有名詞詞庫；第四，辨識錯誤的處理流程，包含信心分數門檻、需人工確認的欄位，以及錯誤發生時的追溯機制。導入初期保留人工覆核比例，再依實測結果逐步調整，通常比一次全面自動化更務實。