Description:FIELD OF THE INVENTION
The present invention relates to the field of natural language processing (NLP), and more particularly, to machine translation systems. Specifically, the invention pertains to a transformer-based English-to-Hindi and Hindi-to-English translation method leveraging the Jurassic-1 language model.
BACKGROUND OF THE INVENTION
Neural Machine Translation (NMT) has experienced substantial growth but Hindi and English translation remains difficult because of complicated languages and syntax variations and scarce bilingual datasets of high quality. The traditional translation methods fail to grasp Hindi linguistic features properly which results in incorrect grammar or inappropriate contextualization of sentences.
The new transformer-based language models characterized by Jurassic-1 produce fluent and coherent multilingual text generation. Even though Jurassic-1 exists as a translation tool for English to Hindi it remains underutilized in address the distinctive learning capacities of few-shot and zero-shot learning for this low-resource English-Hindi pair.
This research targets the English to Hindi machine translation issue by using the Jurassic-1 language model. The project aims to determine effective methods for Jurassic-1 optimization while also evaluating its translation performance in comparison to current leading NMT systems.
Current solutions include commercial machine translation systems such as Google Translate, Microsoft Translator, and Amazon Translate, which rely on large-scale neural models trained on parallel corpora. These systems provide general-purpose translations but often struggle with context preservation, domain specificity, and the syntactic and semantic complexity of the Hindi language. Moreover, they offer limited flexibility in incorporating custom instructions or adapting to low-resource domains without extensive retraining.
The shortcomings of existing English-Hindi translation systems include poor contextual understanding, limited ability to handle idiomatic expressions, dependency on large parallel corpora, and lack of adaptability to specific domains or user instructions. These systems often produce translations that are grammatically correct but semantically inaccurate, leading to misinterpretations and loss of meaning in real-world applications.
OBJECTIVES OF THE PRESENT INVENTION:
Main objective of the present invention is to develop an efficient English-Hindi and Hindi-English translation system using the Jurassic-1 language model.
Another objective of the present invention is to enhance contextual accuracy and fluency in bilingual machine translation tasks.
Another objective of the present invention is to preserve semantic meaning and syntactic structure during translation between English and Hindi.
Another objective of the present invention is to reduce translation errors in low-resource language pairs using transformer-based architectures.
Another objective of the present invention is to enable scalable and real-time language translation suitable for diverse applications.
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
The proposed invention introduces a novel approach to English-Hindi machine translation by utilizing the Jurassic-1 large language model, a transformer-based architecture developed for advanced natural language understanding and generation. This invention leverages the model’s powerful few-shot and zero-shot learning capabilities to perform high-quality translations, particularly in low-resource language scenarios like English to Hindi.
Herein enclosed is a machine translation system for English-to-Hindi language conversion using a transformer-based Jurassic-1 model, the system comprising:
a Prompt Optimization Module configured to design and refine input prompts to elicit high-quality translations from Jurassic-1 with minimal training data;
a Language Alignment Layer adapted to maintain syntactic consistency and ensure alignment quality between English input text and the generated Hindi output;
an Evaluation and Feedback Loop operatively connected to the Prompt Optimization Module and Language Alignment Layer, configured to evaluate translation quality and feed performance data for prompt refinement;
wherein the Jurassic-1 model processes English input text based on optimized prompts and generates output text in Hindi;
wherein the system leverages few-shot and zero-shot learning capabilities for translation without reliance on large parallel corpora.
The evaluation and Feedback Loop comprises a set of evaluation metrics including BLEU score, METEOR score, and human judgment score.
The performance data generated by the Evaluation and Feedback Loop is used iteratively to enhance prompt engineering strategies and improve overall translation quality.
The output text is suitable for deployment in one or more of the following applications: real-time translation, educational tools, multilingual chatbots, and government communication systems.
The Prompt Optimization Module includes a dynamic prompting mechanism configured to inject language-specific cues and contextual examples into the Jurassic-1 model input.
The Language Alignment Layer ensures preservation of morphological and semantic nuances of Hindi during translation.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
FIGURE 1: SYSTEM ARCHITECTURE
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a",” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and/or “including,” when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", “third”, and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
In some embodiments of the present invention, discloses a novel machine translation system for English-to-Hindi and Hindi-to-English language pairs, utilizing the Jurassic-1 large language model, a transformer-based architecture.
In some embodiments of the present invention, the system introduces a prompt-driven approach that leverages the few-shot and zero-shot capabilities of Jurassic-1 to generate fluent, contextually accurate, and grammatically correct translations, particularly in low-resource language scenarios.
In some embodiments of the present invention, unlike traditional neural machine translation systems that depend heavily on large parallel corpora, the invention employs prompt optimization, controlled fine-tuning, and dynamic prompting strategies to guide the model.
In some embodiments of the present invention, the core components of the system include a Prompt Optimization Module, a Language Alignment Layer, and an Evaluation & Feedback Loop that utilizes BLEU, METEOR, and human judgment scores for performance assessment and iterative refinement.
In some embodiments of the present invention, the invention significantly reduces computational costs and data requirements, making it a scalable and effective solution for real-time translation, multilingual chatbots, educational tools, and government communication systems.
Herein enclosed is a machine translation system for English-to-Hindi language conversion using a transformer-based Jurassic-1 model, the system comprising:
a Prompt Optimization Module configured to design and refine input prompts to elicit high-quality translations from Jurassic-1 with minimal training data;
a Language Alignment Layer adapted to maintain syntactic consistency and ensure alignment quality between English input text and the generated Hindi output;
an Evaluation and Feedback Loop operatively connected to the Prompt Optimization Module and Language Alignment Layer, configured to evaluate translation quality and feed performance data for prompt refinement;
wherein the Jurassic-1 model processes English input text based on optimized prompts and generates output text in Hindi;
wherein the system leverages few-shot and zero-shot learning capabilities for translation without reliance on large parallel corpora.
The evaluation and Feedback Loop comprises a set of evaluation metrics including BLEU score, METEOR score, and human judgment score.
The performance data generated by the Evaluation and Feedback Loop is used iteratively to enhance prompt engineering strategies and improve overall translation quality.
The output text is suitable for deployment in one or more of the following applications: real-time translation, educational tools, multilingual chatbots, and government communication systems.
The Prompt Optimization Module includes a dynamic prompting mechanism configured to inject language-specific cues and contextual examples into the Jurassic-1 model input.
The Language Alignment Layer ensures preservation of morphological and semantic nuances of Hindi during translation.
EXAMPLE 1
BEST METHOD
The proposed invention introduces a novel approach to English-Hindi machine translation by utilizing the Jurassic-1 large language model, a transformer-based architecture developed for advanced natural language understanding and generation. This invention leverages the model’s powerful few-shot and zero-shot learning capabilities to perform high-quality translations, particularly in low-resource language scenarios like English to Hindi.
Unlike traditional Neural Machine Translation (NMT) systems that rely heavily on extensive parallel corpora, this invention utilizes prompt engineering and controlled fine-tuning strategies to guide Jurassic-1 in producing contextually accurate, fluent, and grammatically correct translations. The system incorporates a dynamic prompting mechanism that feeds the model with language-specific cues and contextual examples, enabling it to better capture the syntactic, morphological, and semantic nuances of Hindi.
The core components of the proposed invention include:
• Prompt Optimization Module: Designs and refines input prompts to elicit high-quality translations from Jurassic-1 with minimal training data.
• Language Alignment Layer: Ensures syntactic consistency between English source sentences and the generated Hindi output.
• Evaluation & Feedback Loop: Continuously evaluates translation quality using BLEU, METEOR, and human judgment scores, feeding performance data back into the prompt refinement process.
This invention significantly reduces the dependency on large bilingual datasets and complex training pipelines, making it a cost-effective and scalable solution for machine translation between English and Hindi. It holds potential for deployment in real-time translation applications, educational tools, multilingual chatbots, and government communication systems where accurate and culturally appropriate translation is crucial.
NOVELTY:
A transformer-based translation system utilizing Jurassic-1’s few-shot learning and prompt engineering capabilities to enable accurate, context-aware English to Hindi translation without the need for large-scale parallel corpora.
, Claims:1. A machine translation system for English-to-Hindi language conversion using a transformer-based Jurassic-1 model, the system comprising:
a Prompt Optimization Module configured to design and refine input prompts to elicit high-quality translations from Jurassic-1 with minimal training data;
a Language Alignment Layer adapted to maintain syntactic consistency and ensure alignment quality between English input text and the generated Hindi output;
an Evaluation and Feedback Loop operatively connected to the Prompt Optimization Module and Language Alignment Layer, configured to evaluate translation quality and feed performance data for prompt refinement;
wherein the Jurassic-1 model processes English input text based on optimized prompts and generates output text in Hindi;
wherein the system leverages few-shot and zero-shot learning capabilities for translation without reliance on large parallel corpora.
2. The system as claimed in claim 1, wherein the Evaluation and Feedback Loop comprises a set of evaluation metrics including BLEU score, METEOR score, and human judgment score.
3. The system as claimed in claim 1, wherein performance data generated by the Evaluation and Feedback Loop is used iteratively to enhance prompt engineering strategies and improve overall translation quality.
4. The system as claimed in claim 1, wherein the output text is suitable for deployment in one or more of the following applications: real-time translation, educational tools, multilingual chatbots, and government communication systems.
5. The system as claimed in claim 1, wherein the Prompt Optimization Module includes a dynamic prompting mechanism configured to inject language-specific cues and contextual examples into the Jurassic-1 model input.
6. The system as claimed in claim 1, wherein the Language Alignment Layer ensures preservation of morphological and semantic nuances of Hindi during translation.