BiSync: A Bilingual Editor for Synchronized Monolingual Texts

Abstract: In our globalized world, a growing number of situations arise where people are required to communicate in one or several foreign languages. In the case of written communication, users with a good command of a foreign language may find assistance from computer-aided translation (CAT) technologies. These technologies often allow users to access external resources, such as dictionaries, terminologies or bilingual concordancers, thereby interrupting and considerably hindering the writing process. In addition, CAT systems assume that the source sentence is fixed and also restrict the possible changes on the target side. In order to make the writing process smoother, we present BiSync, a bilingual writing assistant that allows users to freely compose text in two languages, while maintaining the two monolingual texts synchronized. We also include additional functionalities, such as the display of alternative prefix translations and paraphrases, which are intended to facilitate the authoring of texts. We detail the model architecture used for synchronization and evaluate the resulting tool, showing that high accuracy can be attained with limited computational resources. The interface and models are publicly available at https://github.com/jmcrego/BiSync and a demonstration video can be watched on YouTube at https://youtu.be/_l-ugDHfNgU .

• The paper introduces BiSync, a bilingual editor that synchronizes text across languages using neural machine translation for real-time editing.
• The system employs control tokens in a transformer architecture, achieving high BLEU scores and low TER to ensure quality synchronization.
• BiSync offers flexible editing workflows by allowing users to alternate between languages and generate alternative translations and paraphrases.

An Overview of BiSync: A Bilingual Editor for Synchronized Monolingual Texts

The paper presented by Josep Crego, Jitao Xu, and François Yvon introduces BiSync, an innovative bilingual writing assistant. BiSync addresses the limitations of conventional computer-aided translation (CAT) systems by allowing users to simultaneously compose and synchronize text in two languages. This system supports free alternation between writing in either language, overcoming the traditional constraints of fixed-source sentence and target-side restrictions that characterize existing CAT tools.

Key Features and Implementation

BiSync integrates several functionalities intended to enhance the editing process for bilingual texts. Its hallmark feature is the bidirectional synchronization of two text boxes, ensuring that modifications in one language automatically produce semantically equivalent adjustments in the other. The system can be adjusted to prevent automatic alterations when users wish to freeze one language.

Another notable function is the generation of alternative translations and paraphrases. These features facilitate user interaction by offering multiple ways to complete sentences or express ideas, thus enhancing overall fluency and accuracy in writing. The automated synchronization waits briefly after text input to ensure a seamless user experience. This aspect mirrors the industry standard in commercial translation interfaces but extends flexibility by enabling edits across both language contexts.

Technological Framework

The underlying architecture of BiSync is based on a refined version of neural machine translation (NMT). Specifically, the system leverages control tokens to manage tasks such as insertion, deletion, substitution, and bilingual text infilling (BTI). This model is trained with synthetic datasets generated from existing parallel corpora to simulate editing tasks that users might perform.

The authors utilize a custom-trained transformer model, drawing on recent advances in language processing to optimize performance. The model's flexibility allows it to generate translations from scratch or update existing translations with minimal disruption. The architecture supports efficient inference through CTranslate2, enabling rapid execution without sacrificing linguistic accuracy.

Performance Evaluation

Experimental results highlight BiSync's superiority over baseline translation models across various tasks. The system's design facilitates high BLEU scores in synchronization tasks, outperforming general translation model configurations. Furthermore, BiSync maintains low Translation Edit Rate (TER) scores, indicating that synchronized translations remain close to the initial drafts, an important factor for maintaining text integrity during iterative editing processes.

Implications and Future Directions

BiSync offers practical applications for bilingual users, significantly impacting fields that require precise multilingual document composition. It addresses a crucial gap between complete automation and nuanced manual adjustments, providing an accessible tool that enhances both productivity and quality in bilingual writing tasks.

From a theoretical perspective, BiSync embodies a step forward in developing more interactive and adaptive machine translation systems. It converges on solutions that balance automated efficiency with user control, potentially setting a precedent for future developments in translational AI.

The authors propose further refinement through the integration of grammatical error prediction and more sophisticated revision management. These improvements aim to reinforce user autonomy without undermining the synchronization's coherence.

In conclusion, BiSync represents a notable advancement in bilingual text composition, merging technical innovation with user-oriented design to facilitate nuanced yet efficient multilingual communication.