English to Gujarati BFSI Domain Parallel Corpora
The dataset consists of bilingual sentence-aligned corpora for the BFSI domain from English to Gujarati and vice versa.
Category
Parallel Corpora
Volume
50K+ Corpus
Last Updated
June 2022
Number of participants
200+ people
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About This OTS Dataset
Introduction
Welcome to the English-Gujarati Bilingual Parallel Corpora dataset for the Banking, Financial Services, and Insurance (BFSI) domain! This meticulously curated dataset offers a rich collection of bilingual text data, translated between English and Gujarati, providing a valuable resource for developing BFSI domain-specific language models and machine translation engines.
Dataset Content
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Extensive Dataset:
Over 50,000 sentences offering a robust dataset for various applications.
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Translator Diversity:
Contributions from more than 200 native translators ensure a wide range of linguistic styles and interpretations.
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Word Count:
Sentences range from 7 to 25 words, suitable for various computational linguistic applications.
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Syntactic Variety:
The corpus encompasses sentences with varying syntactic structures, including simple, compound, and complex sentences.
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Interrogative and Imperative Forms:
The corpus includes sentences in interrogative (question) and imperative (command) forms, reflecting the conversational nature of the BFSI industry.
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Affirmative and Negative Statements:
Both affirmative and negative statements are represented in the corpus, ensuring different polarities.
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Passive and Active Voice:
The corpus features sentences written in both active and passive voice, ensuring different perspectives and representations of information.
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Idiomatic Expressions and Figurative Language:
The corpus incorporates idiomatic expressions, metaphors, and figurative language commonly used in the BFSI domain.
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Discourse Markers and Connectives:
The corpus includes a wide range of discourse markers and connectives, such as conjunctions, transitional phrases, and logical connectors, which are crucial for capturing the logical flow and coherence of the text.
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Cross Translation:
The dataset includes a cross-translation which means a part of the dataset is translated from English to Gujarati and another portion is translated from Gujarati to English to improve bi-directional translation capabilities.
Domain Specific Content
This Parallel Corpus is meticulously curated to capture the linguistic intricacies and domain-specific nuances inherent to the BFSI industry.
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Industry-Tailored Terminology:
The corpus encompasses a comprehensive lexicon of BFSI-specific terminology, ranging from technical banking and financial terms to insurance-related vocabulary and regulatory jargon.
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Authentic Industry Expressions:
Beyond technical terminology, the corpus captures the authentic expressions, idioms, and colloquialisms used within the BFSI industry.
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Contexts Specific to BFSI:
The corpus encompasses a wide range of contexts specific to the BFSI domain, including financial transactions, regulatory compliance, risk management, customer service interactions, and more.
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Cross-Domain Applicability:
While the primary focus is on the BFSI sector, the corpus also includes relevant cross-domain content, such as general business terminology, legal terms, and language related to technology and digital services.
Format and Structure
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Multiple Formats:
Available in Excel format, with the ability to convert to JSON, TMX, XML, XLIFF, XLS, and other industry-standard formats, facilitating ease of use and integration.
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Structure:
It contains information like Serial Number, Unique ID, Source Sentence, Source Sentence Word Count, Target Sentence, and Target Sentence Word Count.
Usage and Application
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Machine Translation and Language Localization:
It serves as a valuable training resource for developing robust machine translation engines tailored to the BFSI domain.
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NLP Applications:
Enabling the creation and improvement of predictive keyboards, spell checkers, grammar checkers, and text/speech understanding systems.
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LLM Training:
Training, fine-tuning, and enhancing bilingual capabilities of LLMs.
Secure and Ethical Collection
•Our proprietary parallel corpus platform “Yugo” was used throughout the process of this dataset creation.
•Throughout the dataset creation process, the data remained within our secure platform and did not leave our environment, ensuring data security and confidentiality.
•It does not include any personally identifiable information, which makes the dataset safe to use.
•The source or translated content included in the corpus does not infringe upon any copyrights or intellectual property rights. The corpus comprises original content created specifically for this purpose.
Update and Customization
To ensure the continued relevance and effectiveness of this BFSI Domain Parallel Corpora Dataset for robust language models and machine translation engines, we are committed to regular updates.
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Annotation:
Various types of annotations like Part-of-speech tagging, Named Entity Recognition (NER), Sentiment Analysis, Intent Classification, Multiple Translation Ranking, or any other application-specific annotations can be made available upon request.
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Classification:
Classification of corpus based on the type of sentence, and subdomain can be made available.
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Custom Collection:
Custom collection can be done on specific requirements in any language pair and domain.
License
This Gujarati-English Parallel Corpus dataset for BFSI domain is created by FutureBeeAI and is available for commercial use.
Use Cases
MT Engine
Language model
Predictive keyboards
Spell check
Grammar correction
Text/speech systems
Dataset Sample(s)
SAMPLE
| Source Language | Target Language |
|---|---|
| The system of tokenization to prevent bank frauds will come into effect from October 1. | બેન્ક ફ્રોડ રોકવા ટોકનાઈઝેશનની સિસ્ટમ ૧લી ઓક્ટોબરથી અમલમાં. |
| No one will be able to know your debit/credit card number with the new system. | નવી સિસ્ટમથી કોઈ તમારો ડેબિટ/ક્રેડિટ કાર્ડ નંબર જાણી નહિ શકે. |
| There is need to promote digital banking in rural areas. | ગ્રામીણ વિસ્તારોમાં ડિજિટલ બેંકિંગને પ્રોત્સાહન આપવાની જરૂર. |
| RBI introduces internet banking guidelines for rural banks | ગ્રામીણ બેંકો માટે ઈન્ટરનેટ બેંકિંગ માટેની RBIની માર્ગદર્શિકા રજૂ કરી. |
| The scope of services of regional rural banks is limited. | પ્રાદેશિક ગ્રામીણ બેંકોની સેવાઓનો વિસ્તાર મર્યાદિત છે. |
| RBI has recently issued a new guideline. | RBIએ હાલમાં જ એક નવી ગાઈડલાઈન બહાર પાડી છે. |
| Preserve the message received after making UPI payments. | UPI કર્યા બાદ પ્રાપ્ત થયેલા મેસેજને સાચવી રાખો. |
| Airtel Payments Bank has launched micro ATM on Wednesday. | એરટેલ પેમેન્ટ્સ બેંકે બુધવારે માઈક્રો એટીએમ લોન્ચ કર્યુ છે. |
| Customers of all banks will be able to withdraw money through micro ATMs | બધી જ બેંકોના ગ્રાહકો માઈક્રો એટીએમ દ્વારા રૂપિયા ઉપાડી શકશે |
| Where to invest to earn Rs 10 lakh in just three years? | માત્ર ત્રણ જ વર્ષમાં 10 લાખ કમાવવા શેમાં રોકાણ કરવું? |
ATTRIBUTES
| target_language | Gujarati |
| source_language | English |
| domain | BFSI |
Dataset Details
Dataset type
Text Corpus Data
Volume
50K+ Sentences
Media type
Text
Language pair
English-Gujarati
File Details
Type
Bilingual
Word count
7 to 25 words per asset
Format
XLSX, TMX, XML, XLIFF, XLS
Annotation
NA
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