A Study of Machine Translation Approaches for Gujarati to English Translation

Gandhi, Vedant; Gandhi, Vaibhav Bharat; Gala, Dhrumil Vinil; Tawde, Prachi

doi:10.1109/stcr51658.2021.9588859

Cited by 13 publications

(3 citation statements)

References 11 publications

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“…Using this approach we identified 103,599 clicks on SERPs and a per-SERP CTR of 38.2% (similar to an estimate of 35% from a recent industry report (Gandhi 2021)). Our approach only detects the first click that participants made on SERPs-a limitation that we discuss in § 6.3.…”

Section: Participant Datasupporting

confidence: 53%

Market or Markets? Investigating Google Search’s Market Shares under Vertical Segmentation

Hu,

Gleason,

Aziz

et al. 2024

ICWSM

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Is Google Search a monopoly with gatekeeping power? Regulators from the US, UK, and Europe have argued that it is based on the assumption that Google Search dominates the market for horizontal (a.k.a. “general”) web search. Google disputes this, claiming that competition extends to all vertical (a.k.a. “specialized”) search engines, and that under this market definition it does not have monopoly power. In this study we present the first analysis of Google Search’s market share under vertical segmentation of online search. We leverage observational trace data collected from a panel of US residents that includes their web browsing history and copies of the Google Search Engine Result Pages they were shown.We observe that participants’ search sessions begin at Google greater than 50% of the time in 24 out of 30 vertical market segments (which comprise almost all of our participants’ searches). Our results inform the consequential and ongoing debates about the market power of Google Search and the conceptualization of online markets in general.

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Section: Participant Datasupporting

confidence: 53%

Market or Markets? Investigating Google Search’s Market Shares under Vertical Segmentation

Hu,

Gleason,

Aziz

et al. 2024

ICWSM

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“…Furthermore, a comprehensive dataset of English handwritten digits from USPS was collected [22]. Datasets containing Gurmukhi and Gujarati images were collected from GitHub repositories as well [30,31]. Furthermore, English (USPS [20]) and Arabic datasets (MADBase [32]) considered to assess the proposed method.…”

Section: A Preprocessingmentioning

confidence: 99%

Unveiling Cross-Linguistic Mastery: Advancing Multilingual Handwritten Numeral Recognition with Attention-driven Transfer Learning

Fateh,

Birgani,

Fateh

2023

Preprint

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In the realm of data analysis and document processing, the recognition of handwritten numerals stands as a pivotal advancement. This contribution has steered transformative shifts in optical character recognition, historical handwritten document analysis, and postal automation. A persistent challenge in this arena is the recognition of handwritten digits across a spectrum of languages, each with its idiosyncrasies. We present an innovative paradigm to surmount this hurdle, transcending the confines of monolingual recognition. Unlike the status quo, which gravitates toward a narrow subset of languages, our method orchestrates a comprehensive solution spanning 12 distinct languages, deftly navigating linguistic intricacies. The catalyst for this efficacy is transfer learning, amplifying image quality and recognition acumen. Emboldening this framework is an ingenuity-charged attention-based module that refines precision. Our rigorous experimentations substantiate quantum leaps in image quality and the prowess of linguistic and numeral recognition. Notably, we unearth significant accuracy strides, eclipsing 2% enhancements in specific languages vis-à-vis antecedent methodologies. This endeavor epitomizes a sturdy, economically sound avenue, unshackling multilingual handwritten numeral recognition to an expansive spectrum of languages.

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“…The publication of Warren Weaver's Memorandum of Translation in 1949 marked the beginning of modern machine translation. Rule-based, statistical machine translation (SMT), corpus-based, and neural machine translation (NMT) are some of the machine translation methodologies employed [27]. In the 1970s, the rule-based method to machine translation was introduced.…”

Section: Machine Translationmentioning

confidence: 99%

Jahai language repository: a mobile application

Rahman

Mohamad

Mohtar

et al. 2023

IJEECS

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The Jahai language is facing extinction primarily because it is among the least spoken language among minority groups in Malaysia. This is due to lesser speakers and the shift to using a more dominant language. The Jahai tribe is one of the community groups living in the Royal Belum Perak State Park. People who need assistance from Jahai people often face difficulties in communicating with them due to the language barrier. Therefore, a mobile translation system was developed to preserve the language. The system translates the Jahai terms into Malay language. This way, by using the system, other ethnics in Malaysia can understand the language especially when communicating with Jahai people. Three main steps are required in the translation process; first, key in the text input via special character keypad. Then, the system will search the matching word in the database. Finally, the meaning of the word will be displayed. The testing results have indicated this system is functional and accepted with the SUS score of 94/100. Several future recommendations could be made such as including voice search function and adding more Jahai terms in other categories so as to improve the functionality and usability of this proposed system.

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A Study of Machine Translation Approaches for Gujarati to English Translation

Cited by 13 publications

References 11 publications

Market or Markets? Investigating Google Search’s Market Shares under Vertical Segmentation

Market or Markets? Investigating Google Search’s Market Shares under Vertical Segmentation

Unveiling Cross-Linguistic Mastery: Advancing Multilingual Handwritten Numeral Recognition with Attention-driven Transfer Learning

Jahai language repository: a mobile application

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