Nimdzi Insights的首席執(zhí)行官Josef Kubovsky，就“2024年語言服務(wù)創(chuàng)新發(fā)展國際（廈門）論壇暨中國翻譯協(xié)會翻譯服務(wù)委員會2024年會”相關(guān)內(nèi)容，撰寫了三篇聚焦中國語言服務(wù)行業(yè)的文章?，F(xiàn)雙語首篇已上線，共同延續(xù)并鞏固會議成果。
Focus on China#1 聚焦中國#1
Josef Kubovsky
2024 年 11 月 27 日
Over the past two weeks, I’ve had the privilege of traveling across China, culminating in attending the TAC LSC 2024 in Xiamen. Organized under the leadership of Frank Zhonghe Wei and his dedicated team, the event was a masterclass in bringing together innovation, culture, and collaboration in the language service industry. From owners of some of China’s largest translation companies to specialized boutique firms, the conference drew an impressive array of professionals.
在過去的兩周里，我有幸走訪中國，并參加了在廈門舉辦的“語言服務(wù)創(chuàng)新發(fā)展國際（廈門）論壇暨中國翻譯協(xié)會翻譯服務(wù)委員會2024年會”（TAC LSC 2024）會議。由韋忠和及其團(tuán)隊(duì)承辦的此次會議，堪稱一場在語言服務(wù)行業(yè)中融合創(chuàng)新、文化和協(xié)作的精彩盛會。從中國大型翻譯公司到專注于細(xì)分領(lǐng)域的精品公司，此次會議吸引了眾多專業(yè)人士。
The presentations and panels were nothing short of enlightening. They delves deep into the technologies shaping our industry and the challenges that lie ahead. I was particularly intrigued by discussions surrounding generative AI, a theme that reverberated across the three panels exploring current trends and challenges. These panels tackled topics ranging from technological disruption to the nuanced interplay of culture in machine-generated translations.
會議中的演講和討論讓人深受啟發(fā)，深入探討了塑造我們行業(yè)的技術(shù)以及未來的挑戰(zhàn)。讓我尤為感興趣的是圍繞生成式人工智能的討論，這一主題在探索當(dāng)前趨勢和挑戰(zhàn)的三個專題討論中多次被提及。這些討論涵蓋了從技術(shù)變革到文化與機(jī)器翻譯的微妙平衡等議題。
One of the standout themes at TAC LSC 2024 was the role of generative Al in localization. Companies like iFlytek and Huawei showcased how their?large language models (LLMs)are advancing localization workflows, particularly for Chinese-to-English and English-to-Chinese translations. These tools excel at:
● Speed and Scalability:Processing vast datasets and generating initial drafts faster than ever before.
● Consistency in Terminology: Ensuring that complex technical terms are accurately and consistently translated across projects.
TAC LSC 2024的一大主題是生成式人工智能在本地化中的作用。像科大訊飛和華為這樣的公司展示了他們的大語言模型（LLMs）如何推動中英互譯流程的發(fā)展。這些工具在以下方面表現(xiàn)出色：
● 速度與規(guī)?；?/strong>處理海量數(shù)據(jù)集并生成初稿的速度前所未有地快。
● 術(shù)語一致性：確保復(fù)雜技術(shù)術(shù)語在項(xiàng)目中得到準(zhǔn)確且一致的翻譯。
Yet, the limitations of AI were evident in discussions. As highlighted in the “Harnessing Generative AI for Translation” panel, idiomatic expressions and cultural nuances remain significant challenges. For example, translating “不入虎穴焉得虎子” (“Without entering the tiger’s den, how can one get the tiger’s cub?”) literally into English risks losing its metaphorical richness about bravery and risk-taking.
然而，人工智能的局限性也在討論中顯露無疑。正如“利用生成式人工智能進(jìn)行翻譯”的專題中提到的那樣，成語表達(dá)和文化細(xì)微差異仍然是重大挑戰(zhàn)。例如，將“不到虎穴焉得虎子”字面翻譯成英文會失去其關(guān)于勇氣和冒險的隱喻意義。
Cultural adaptation remains a critical weakness in Al-driven localization. At TAC LSC 2024, a recurring concern was AI’s inability to grasp deeper cultural meanings, leading to mechanical or inappropriate translations for target audiences.
文化適應(yīng)性仍然是人工智能驅(qū)動的本地化的一大短板。在TAC LSC 2024會議中，人工智能無法掌握深層次文化意義的能力限制，導(dǎo)致翻譯內(nèi)容機(jī)械化或不適合目標(biāo)受眾的擔(dān)憂多次被提及。
One session illustrated this vividly with a case study of a Chinese drama localized for Western streaming platforms. While Al efficiently handled the bulk of the translations, scenes depicting traditional Chinese customs were mistranslated or stripped of their emotional depth. The machine’s literal interpretations failed to convey the symbolic resonance of concepts like “家”(home) in the Chinese cultural context, which encompasses familial bonds and heritage.
其中一個案例研究生動地展示了這一問題。一部中國電視劇在為西方流媒體平臺進(jìn)行本地化時，雖然人工智能有效地完成了大部分翻譯工作，但涉及中國傳統(tǒng)習(xí)俗的場景卻被誤譯或失去了情感深度。機(jī)器的字面解釋無法傳達(dá)像“家”這樣的概念在中國文化中所包含的家庭紐帶與傳統(tǒng)內(nèi)涵。
Speakers emphasized the growing need for hybrid workflows – integrating AI efficiency with human expertise – to bridge this gap.
演講者強(qiáng)調(diào)，需要越來越多的混合工作流來彌合這一差距，即整合人工智能的高效性與人類專家的專業(yè)性。
The concept of hybrid workflows was central to discussions, particularly during the “Emerging Workflow Models in Translation” panel. These workflows involve:
混合工作流的概念在討論中占據(jù)了核心地位，尤其是在“翻譯中的新型工作流模型”專題中。這些工作流包括：
1.AI for First Drafts 借助人工智能生成初稿
Leveraging generative AI to produce preliminary translations quickly and at scale.
利用生成式人工智能快速大規(guī)模地產(chǎn)生初稿。
2.Human Post-Editing 人工后期編輯
Involving linguists and cultural consultants to refine outputs, ensuring contextual and cultural fidelity.
讓語言學(xué)家和文化顧問對人工智能的輸出進(jìn)行優(yōu)化，確保語境和文化的準(zhǔn)確性。
3.Collaborative Platforms 協(xié)作平臺
?Using advanced tools to streamline communication and revisions between AI and human teams.
利用先進(jìn)工具優(yōu)化人工智能與人類團(tuán)隊(duì)之間的溝通與修訂。
A multinational gaming company shared how they localized a Chinese role-playing game for European audiences using a hybrid approach. Generative AI completed over 100,000 lines of dialogue in just days. Human editors then tailored cultural elements, replacing references to Chinese mythology with Western equivalents that felt authentic to the new audience. The result was a seamless localization that retained the game’s core essence while resonating with European players.
一家跨國游戲公司分享了如何使用混合方法為歐洲觀眾本地化一款中國角色扮演游戲的案例。生成式人工智能在幾天內(nèi)完成了超過10萬行的對話翻譯。人類編輯隨后對文化元素進(jìn)行了調(diào)整，用西方神話替代了中國神話的引用，使其更貼近目標(biāo)受眾。最終的成果是一個無縫的本地化版本，既保留了游戲的核心精髓，又能引起歐洲玩家的共鳴。
It was inspiring to hear perspectives from industry leaders like Arancha Caballero, President of ANETI, and Hélène Pielmeier, Senior Analyst and Director of LSP Services at CSA, who brought a global lens to the discussions. Arancha’s presentation on the State of the Language Industry in Spain and Europe highlighted parallels between European and Chinese localization challenges, particularly around pricing pressures and adapting to AI technologies.
聆聽來自行業(yè)領(lǐng)袖的觀點(diǎn)令人振奮，例如ANETI主席阿蘭查·卡瓦列羅和CSA ?Research高級分析師兼LSP服務(wù)總監(jiān)海琳·皮爾邁耶。他們?yōu)橛懻搸砹巳蚧囊暯?。阿蘭查的演講探討了西班牙和歐洲語言行業(yè)的現(xiàn)狀，并突出了歐洲與中國在本地化挑戰(zhàn)上的相似之處，特別是在價格壓力和適應(yīng)人工智能技術(shù)方面。
Hélène’s talk on?LSP Transformations in the Post-Localization Era?offered actionable insights into how companies can evolve their business models, emphasizing agility and client-centric innovation. These presentations underscored the interconnected nature of our global industry.
海琳關(guān)于“后本地化時代LSP轉(zhuǎn)型”的演講提供了切實(shí)可行的見解，闡述了公司如何通過靈活性和以客戶為中心的創(chuàng)新調(diào)整其業(yè)務(wù)模式。這些演講強(qiáng)調(diào)了我們?nèi)蚧袠I(yè)的緊密關(guān)聯(lián)。
From the presentations and panels at TAC LSC 2024, several key strategies emerged for tackling the challenges of generative AI in localization:
從TAC LSC 2024的演講與討論中，可以總結(jié)出幾條應(yīng)對生成式人工智能在本地化中挑戰(zhàn)的關(guān)鍵策略：
TAC LSC 2024 was a powerful reminder of the balance we must strike between technological innovation and cultural preservation. Generative AI has undeniably transformed localization workflows, but its limitations in cultural sensitivity highlight the enduring value of human expertise.
TAC LSC 2024提醒我們在技術(shù)創(chuàng)新與文化傳承之間找到平衡的重要性。生成式人工智能無疑已經(jīng)改變了本地化工作流，但其在文化敏感性上的局限性凸顯了人類專業(yè)知識的持久價值。
I left Xiamen inspired by the conversations, case studies, and connections. The language service industry is entering a transformative phase, and events like TAC LSC 2024 show that collaboration, curiosity, and cultural awareness will guide us through this evolution.
離開廈門時，我為這些對話、案例研究和建立的聯(lián)系感到振奮。語言服務(wù)行業(yè)正在進(jìn)入一個變革階段，而TAC LSC 2024表明，協(xié)作、好奇心和文化意識將引領(lǐng)我們邁向這一演變。
翻譯：李匯嫻
校對：黃佳琪
終審：韋忠和
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