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Multimodal Machine Translation Over the past two decades, advanced technologies have profoundly transformed cross-cultural communication and translation. While these innovations have brought undeniable benefits, they also present new challenges, particularly in navigating the various ways information can be conveyed. Interlingual translations that rely solely on words cannot adequately meet the needs of diverse, culturally heterogeneous audiences. The phenomenon of multimodal translation • Multimodality refers to “the use of several semiotic methods in the design of a semiotic product or design" (Kress & van Leeuwen, 2001:20). In other words, it signifies the symbiotic coexistence in human communication of more than one modality of expression. Hence, multimodal translation conceptualizes translation not merely as a linguistic exercise, but as an integration of several semiotic resources for meaning making, such as pictures, audio etc. Multimodal text translation is commonly referred to as "constrained translation", whereby each non-linguistic element adds to the general meaning and thus creates "constraints" by imposing conditions on the text. Translation in the Digital Realm: Filling the gap In the Digital world, the complex interplay between the verbal mode of expression and the visual, acoustic or other semiotic modes is essential for conveying the message in its entirety. This synergy - of written language and audiovisual material necessitates a reconceptualisation of the traditional translation approaches. - Some researchers (Kress & van Leeuwen, 2001); (Valdeón, 2024) claim that the multimodal nature of text is frequently neglected by scholars in the field of translation studies; whereby multimodality is an essential element for meaning-making processes across different contexts and mediums, particularly in the realm of the World Wide Web. Multimodal Machine Translation: Major tasks and areas of application Multimodal machine translation implies extracting information from multiple modalities (text, audio, visuals) based on the assumption that the additional modalities provide valuable alternative perspectives on the content. MMT employs different modalities as 'scaffolds' to address the ambiguity problem. Studies (Barrault et al., 2018) suggest that visual features can play a pivotal role in disambiguating words and help translators resolve the issue of polysemy. 22. True/False: The term "constrained translation" refers to translations that are not influenced by non- linguistic elements. 23. True/False: Multimodal machine translation (MMT) utilizes multiple modalities, such as text, audio, and visuals, to enhance translation accuracy. 24. True/False: Visual context can help disambiguate the meaning of polysemic words in translation. 25. True/False: The term "video-guided translation" refers to translating written text without any audiovisual elements. 26. True/False: MMT systems operate without any need for contextual understanding of the source material. 27. True/False: The "communication effect" in multimodal translation refers to how the final product impacts the audience. 28. True/False: Game localization does not require consideration of cultural norms of the target audience. 29. True/False: One challenge of MMT is the ephemeral nature of web content, making translation difficult. 30. True/False: Advanced computational models like neural networks are irrelevant in the context of multimodal machine translation. Compose a brief concluding paragraph (approximately 200 words) that defines "multimodal machine translation" and highlights how it differs from traditional machine translation. Pic. 1; Pic 2 "The glasses are broken." Translation: ✔ "Les verres sont cassés." Translation: X "Les lunettes sont cassées." En: Hockey player in white uniform with stick De: Hockeyspielerin in weißem Trikot mit einem Schläger. × De: Hockeyspieler in weißem Trikot mit einem Schläger. Thus, pictures 1 and 2 illustrate the potential translation challenges a MMT tool might encounter. On the picture 1, visual context resolves the ambiguity of English word 'glasses' for English-to-French translation: the accompanying visual content helps the tool to identify that the word refers to tableware rather than reading glasses (lunettes). Besides, in the absence of accompanying visual clues, some gender-neutral words e.g., hockey player may be misinterpreted (see pic 2). The term "hockey player" suggests a male hockey player, which contrasts with the potentially inaccurate translation "hockeyspielerin," meaning female hockey player. (Xuxin et al., 2023) MMT: tasks Scholars (Sulubacak et al., 2020) outline three prominent tasks in MMT (see below). Spoken language translation (SLT) i.e., translating spoken dialogue in real-time or from recorded audio. Example: At the conference, an SLT system provides real-time translation of the spoken content into various languages through audio headsets. Spoken Language Translation Speech-to-Text Speech-to-Speech •Offline: for later use (audio/video recordings), possibility of editing Real-time: translation is produced live for immediate use Consecutive: sequential translation after a person has spoken Simultaneous: continuous translation while a person is speaking Image-guided translation (IGT) implies utilizing visual clues to provide contextually relevant translation. Example: the caption reads, "A boy dives into a pool near a water slide" An IGT system analyzes the image, to translate the caption into another language while capturing the essence of the En: A boy dives into a pool near a water slide. De: Ein Junge taucht in der Nähe einer Wasserrutsche in ein Schwimmbecken. Fr: Un garçon plonge dans une piscine près d'un toboggan. Cs: Chlapec skáče do bazénu poblíž skluzavky. scene, such as "Ein Junge taucht in der Nähe einer Wasserrutsche in ein Schwimmbecken". Corresponding Video Clips i.e., Translation set Source Target Go Hit it 進め (go) Move Forward FeJ8e] : feJ8e] translation (VGT) Video-guided translating spoken content (e.g. in a video) while synchronizing subtitles. Example: a cooking tutorial video where a chef demonstrates making a dish while speaking in their native language. A VGT system would translate the chef's spoken instructions into subtitles. All the above-mentioned tasks involve more than one modality, either by using one modality to accompany or aid the interpretation of language in another modality (e.g., IGT), or by converting one modality into another. Remarkably, these tasks are distinguished from their monolingual counterparts by the requirement of models to generate outputs in a different language. Machine Translation: 2D/3D Communication Effect - In machine translation, when a translated product involves texts and images - meaning the target audience receives information from two modalities a two-dimensional communication effect occurs. Besides linguistic and visual content, some translated products turn to the auditive channel for delivering messages, and this is how how a three-dimensional communication effect is realized. Multimodal Machine Translation: Major Aspects The characteristics of multimodal translation arise from three key aspects: Text composition – how textual elements are combined with other modalities (audio, visuals etc). In the context of multimodal machine translation, it refers to how algorithms facilitate this integration to ensure effective communication across different semiotic components. • Synthetic technology – the use of innovative ways to convey the message; tools and technologies employed to create two- or three-dimensional translation. This implies adjusting multimodal elements in addition to the traditional i.e., bilingual transformation. Communication effect - the overall impression and impact the translation final product has on the potential audience. Multimodal Translation: Applications in Digital Environments (Examples) 1. Audiovisual translation, which includes but is not limited to: • Automatic Subtitling • Dubbing i.e., replacing the original audio with a translated voice-over. • Audio Description i.e., providing translated spoken descriptions for individuals with visual impairments. In this type of translation 'translated language is meant to act as the mortar that cements the rest of the semiotic blocs together' (Pérez González, 2014:122). In other words, in this type of translation, the translated language functions as the cohesive element that unites different semiotic components to convey a message in its entirety. 2. Game localization, which refers to “the varied processes involved in transforming game software developed in one country into a form suitable for sale in target territories" (O'Hagan, & Mangiron, 2013:19-20) and this type of multimodal translation requires a comprehensive understanding of contextual, linguistic and cultural aspects, incl.: Cultural adaptation and localization of the game content to the cultural norms of the target audience, ensuring sensitivity and relevance. This commonly includes such processes as translating voiceovers, adapting text, symbols, images etc. to bridge the gap between cultures. 3. Web Localization and Translation of Social Media Content • Web localization - • a dynamic intersection of technology, language, and culture - adapts website content to meet the cultural needs of diverse audiences leveraging MMT tools. Multimodal translation of social media encompasses the translation of textual materials, images, and videos on platforms like Twitter, Instagram, and Facebook (e.g., generating and translating captions, texts, subtitles for videos etc.) Multimodal translation: The challenges 1. Ephemeral nature of WWW and Social WEB According to Gossen at al., (2015), the Web and Social Web are ephemeral and under constant evolution, thus, web pages can quickly change or become unreachable which create obstacles during the translation process. 2. Data Fusion Integrating heterogeneous data types such as audio, visuals or video requires advanced algorithms: extracting relevant features from each data type is a resource-intensive process. Besides, combining data from different modalities into a single meaningful representation is possible only under certain computational requirements. 3. Vast Training data To make MMT work, the user should always employ high-quality multimodal datasets, and the creation of such repositories is a time-consuming undertaking. 4. Data alignment, quality and synchronization Synchronization of multimodal data types, coupled with the necessity to ensure contextually precice alig nment, adds complexity to the task. Moreover, the quality of data is of paramount importance as well; thus, recent studies (Long et al., 2020) suggest that the effectiveness of multimodal translation heavily depends on the quality of annotated images accompanying bilingual text. 5. Contextual, Polysemic and Cultural Nuances One of the cornerstones of MMT is navigating the contextual intricacies, resolving word polysemy (lingui stic items with multiple meanings), and handling culturally stipulated differences between the translated content and the target audience. Multimodal Translation: Common Strategies The strategies employed in multimodal machine translation facilitate the integration of different modalities to create a meaningful output. 1) Leveraging visual content to disambiguate and complement linguistic modality. Studies suggest that "strategic implementation of visual grounding tend to increase the robustness of machine translation systems by mitigating input noise such as errors in the source text" (Çağlayan at al., 2019:54) Such 'visual scaffolds' helps MMT tool prevent or eliminate mistakes e.g., stipulated by word polysemy and/or contextual challenges. 2) Leveraging MMT evaluation metrics to monitor and evaluate translation quality. Since human evaluation is associated with considerable monetary costs, in recent years, evaluation efforts have converged to devising automatic metrics, which operate by comparing the output of a MMT tool against the corpus of human translations (Sulubacak, 2020) The application of the automated 'post-editing' technique predictably enhances the overall quality of a translated product. Most common evaluation metrics tool used in MMT is Bilingual Evaluation Understudy or BLEU, specifically its variant BLEU-RAC4 (Battaglino at al., 2015) known for its versatility and keen attention to detail. 3) The application of advanced computational models e.g., neural networks, self-attention mechanisms (i.e., transformers) and deep learning techniques to perform MMT tasks. [...] Task 1: Answer the questions based on the text 1. What does multimodality refer to? A) The use of only textual elements in communication B) The coexistence of multiple modes of expression C) A single method of communication D) The exclusion of visual elements 2. What is an example of image-guided translation (IGT)? A) Real-time translation of spoken language B) Translating a video tutorial with subtitles C) Analyzing an image to translate its caption D) Translating a website without images 3. Which task involves translating spoken dialogue in real-time? A) Image-guided translation B) Video-guided translation C) Spoken language translation D) Multimodal translation 4. What characterizes a three-dimensional communication effect in translation? A) Use of only text B) Incorporating visual and audio elements C) Textual elements only D) Exclusively visual elements 5. In the context of MMT, what is "data fusion"? A) Combining data from different languages B) Integrating different types of data, like audio and visuals C) Separating audio from text D) Merging multiple translations into one 6. What is a key challenge faced in multimodal translation? A) Lack of technological tools B) Excessively clear data C) Polysemic words and cultural nuances D) Limited audience reach 7. Which of the following is an example of a multimodal translation application? A) Translating a printed book B) Automatic subtitling in videos C) Writing a speech D) Interpreting a spoken conversation 8. What role do visual features play in multimodal machine translation? A) They complicate the translation process B) They help disambiguate words C) They are unnecessary D) They replace audio elements 9. What does the term "contextual alignment" refer to in MMT? A) Ensuring all data types are unrelated B) Aligning different modalities to ensure coherence C) Separating text from images D) Ignoring the context of the source material 10. What is the Bilingual Evaluation Understudy (BLEU) used for? A) Measuring the length of translations B) Evaluating translation quality C) Generating new translation models D) Formatting translated text 11. Which of the following tasks does not involve using multiple modalities? A) Spoken language translation B) Image-guided translation C) Traditional text translation D) Video-guided translation 12. What is a significant aspect of web localization? A) It ignores cultural differences. B) It focuses solely on textual content. C) It adapts website content to cultural needs. D) It translates web pages without context. 13. Which of the following challenges relates to the ephemeral nature of the web? A) Data alignment B) Data fusion C) Constantly changing web content D) Lack of audio data 14. What does "leveraging visual content" in MMT help to achieve? A) Decrease translation efficiency B) Enhance robustness by clarifying meaning C) Eliminate the need for audio D) Simplify all translations to text only 15. What is one of the major applications of audiovisual translation? A) Printing books B) Dubbing and audio description C) Handwriting translation D) Translating spoken words only 16. What does the term "cultural adaptation" in game localization imply? A) Ignoring cultural differences B) Adapting game content to fit the target culture C) Making games universally identical D) Removing all cultural references 17. Which modality is typically involved in video-guided translation? A) Only audio B) Only visual C) Both audio and visual D) Only textual 18. What is the significance of having high-quality multimodal datasets in MMT? A) They reduce the cost of translation. B) They are irrelevant to the translation process. C) They enhance the accuracy and effectiveness of translations. D) They limit the scope of translation. 19. Which of the following is NOT a key aspect of multimodal translation? A) Text composition B) Synthetic technology C) Sole reliance on spoken language D) Communication effect 20. In the context of MMT, what does the term "polysemy" refer to? A) Words with multiple meanings B) Words that have a single meaning C) Visual elements in translation D) Non-verbal communication methods True/False questions 21. True/False: Multimodal translation includes the integration of several semiotic resources beyond just text.