Tuesday, September 5, 2023

The word nerds who lived and died for the Oxford English Dictionary - Sydney Morning Herald - Dictionary

By Ken Haley

HISTORY
The Dictionary People: The Unsung Heroes Who Created the Oxford English Dictionary
Sarah Ogilvie
Chatto & Windus, $35

Autobibliogenesis. There ought to be a word for the process whereby one book appears to spontaneously generate others. If there were a Guinness listing for the most prolific exemplar of the phenomenon, surely The Oxford English Dictionary would be among its leading claimants.

From The Surgeon of Crowthorne (1998) to Australian Pip Williams’ luminous 2020 novel, The Dictionary of Lost Words, and Caught in the Web of Words, a biography of James Murray, its most celebrated editor, the OED has spawned titles across a broad spectrum of genres.

Sir James Murray, first editor of the Oxford English Dictionary, surrounded by files of word definitions.

Sir James Murray, first editor of the Oxford English Dictionary, surrounded by files of word definitions.Credit: Getty Images

The Dictionary People, by Australian-raised lexicographer Sarah Ogilvie, is the latest addition to this august company. She has been an editor on the world’s largest dictionary of English, and before that was Chief Editor of Oxford dictionaries in Australia.

The Oxford English Dictionary was the first lexicon to trace the evolution of words down the centuries; and first to base its citations on a form of crowdsourcing, inviting readers worldwide to locate the earliest written examples for every entry and shade of meaning.

Credit:

Ogilvie’s work stems from a serendipitous find: a discarded volume that turned out to contain Murray’s address books – identifying 3000 contributors who provided the building blocks of the masterwork that took up 40 years of his life and was only completed, with the last word (zyxt: an obsolete Kentish word meaning: “[Thou] seest.“) printed in 1928, 13 years after his death.

Chasing words may be an intellectual pursuit but it is hardly arid, and occasionally lends itself to pathos. In 1906 the widow of William Sykes from South Devon wrote to Murray that he had been working on a dictionary entry the Friday morning prior and died that evening, so “The last words he ever wrote were to you”.

Ogilvie cleverly (and logically) divides her work into 26 letter-headed chapters. H is for “Hopeless Contributors”, thus defined by successive editors. Some refused to send in their citation slips; others produced slipshod work; a few, to whom Murray had sent specially selected volumes, promised much but produced nothing. Picture the steam rising from the “Scriptorium”, where the editors worked, as he wrote against the name T.W. Tonkin of Barnes, “Impostor – Stole the Book”.

A more diligent sleuth was Eleanor Marx, Karl’s daughter, who committed suicide after learning that the love of her life had secretly wed another. One contribution of hers made it into the dictionary only this century: the verb ruffle, from a Madame Bovary citation.

William Chester Minor, prolific contributor to the OED and inmate in the Broadmoor asylum in Crowthorne.

William Chester Minor, prolific contributor to the OED and inmate in the Broadmoor asylum in Crowthorne.Credit:

The “surgeon” of Crowthorne, aka an inmate at that town’s “insane asylum”, American William Chester Minor, was not the only “lunatic” (using the word in its 19th-century acceptation) engaged as a researcher. Three of the four most prolific contributors were asylum inmates, the fourth ran one. As Ogilvie appositely asks: “Was it their madness that drove them to do so much Dictionary work, or was it the Dictionary work that drove them mad?”

This book should be a desideratum for lovers of new words, or even old ones that fell out of, or were never in, fashion: such as superexalt (to overpraise). Some will like it for the words themselves, others for the characters who defined them. Ogilvie puts some remarkable specimens of humanity under her microscope.

Religion and sex nestle under the covers. More than 10 per cent of Dictionary People were clergymen (too much time on their hands?). A vegetarian vicar, John Mayor, oversaw new words for meat abstainers, depositing fruitarian and nutarian in the word salad bowl. And then there was Henry Spencer Ashbee, who boasted of owning the world’s largest collection of pornography and erotica.

By the late Victorian era, when the word hunt was in full use, Australia was no longer a convict destination, but it could still serve as a refuge, as Ogilvie explains: “Miss Edith Lucas of High Wycombe had ‘gone to Melbourne’ and was never heard of again.”

An especially zealous contributor to the OED (now halfway through its third edition), Chris Collier, hailed from Brisbane, the author’s hometown. He produced 100,000 slips from 1975-2010, among them: kit off (naked); sea changer; snaky, petrolhead. The OED accepted them all, but rejected a parochial favourite, Brizvegas.

Whether it’s words or people that float your boat, this stimulating compendium is – whatever other descriptives you might use – hard to superexalt.

The Booklist is a weekly newsletter for book lovers from books editor Jason Steger. Get it delivered every Friday.

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Electronic Dictionary Market to Hit US$ 12,976.66 Million By 2030 | Latest Research By Consegic Business Intelligence - Yahoo Finance - Dictionary

Consegic Business Intelligence is a data measurement and analytics service provider which gives the most exhaustive and reliable analysis available of global consumers and markets. Our research and competitive landscape allow organizations to record competing evolutions and apply strategies accordingly to set up a rewarding benchmark in the market. We are an intellectual team of experts working together with the winning inspirations to create and validate actionable insights that ensure business growth and profitable outcomes.
Consegic Business Intelligence is a data measurement and analytics service provider which gives the most exhaustive and reliable analysis available of global consumers and markets. Our research and competitive landscape allow organizations to record competing evolutions and apply strategies accordingly to set up a rewarding benchmark in the market. We are an intellectual team of experts working together with the winning inspirations to create and validate actionable insights that ensure business growth and profitable outcomes.

Electronic Dictionary Market is projected to register a CAGR of 11.10% during 2023-2030, due to its increasing demand from educational institutions, language learners, and travelers, among others, and major participants includes are ELLTON ENTERPRISE PTE LTD, APKPure, Merriam-Webster Incorporated, Vasco Electronics, SHARP CORPORATION, iFLYTEK Corporation

New York, Sept. 04, 2023 (GLOBE NEWSWIRE) -- As per the research report “Global Electronic Dictionary Market” published by Consegic Business Intelligence, the market was worth USD 5,739.21 Million in 2022 and is anticipated to reach over USD 12,976.66 Million by the year 2030, growing at a CAGR of 11.10%.

Electronic dictionary stores data in digital format that is often stored and accessed through a computer by means of software. The benefits of electronic dictionary including ease of utilization, faster translation, excellent portability, availability of a broad range of information, and others, make it ideal for utilization by educational institutions, business enterprises, language learners, and travelers among others.

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The rising utilization of electronic dictionary in educational institutions to promote bilingual is one of the key factors driving the market growth. Moreover, rising government initiatives for development of educational institutions, increasing adoption of higher education enrolments, and growing international student mobility trends are key factors fostering the adoption of electronic dictionary. For instance, according to the Institute of International Education Inc., the total number of new international students enrolled in U.S. institutions increased by 7% during the academic year 2021/22. Thus, the rising student enrolments in educational institutions is driving the adoption of electronic dictionaries to aid students in language learning, vocabulary expansion, and exam preparations, thereby, driving the growth of the market.

Additionally, the rising application of electronic dictionary by travelers or tourists is expected to promote potential opportunities for the growth of the electronic dictionary market. Electronic dictionary is often utilized by travelers or tourists for effective communication in foreign countries, attributed to its instant translations and language support. Moreover, electronic dictionary helps in overcoming language barriers and enhance the overall travel experience, which are primary determinants for increasing its utilization by travelers or tourists. However, the availability of substitutes for electronic dictionary is hindering the growth of the market.

Report Attributes

Report Details

Market Size By 2030 

USD 12,976.66 Million

Forecast Period

2023-2030

CAGR (2023-2030)

11.10%

Base Year

2022

Study Timeline

2017-2030

Key Players

CASIO COMPUTER CO. LTD., Canon Electronic Business Machines (H.K.) Co. Ltd., ECTACO Inc., ELLTON ENTERPRISE PTE LTD, APKPure, Merriam-Webster Incorporated, Vasco Electronics, SHARP CORPORATION, iFLYTEK Corporation, Hanvon Technology Co. Ltd.

By Sales Channel

Direct Sales and Distributor Sales

By End-User

Educational Institutions, Business Enterprise, Language Learners, and Travelers

Report Coverage

Company Ranking and Market Share, Growth Factors, Total Revenue Forecast, Regional Competitive Landscape, Business Strategies, and more

By Region

North America, Europe, Asia-Pacific, Latin America, Middle East & Africa

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Electronic Dictionary Market Growth Drivers:

  • Rising utilization of electronic dictionary in educational institutions is driving the market growth.

  • Increasing adoption of electronic dictionary by language learners is spurring the market growth.

Restraints

Opportunities

Global Electronic Dictionary Market Segmentation Details:

Based on sales channel, the distributor sales segment contributed the largest shares to the market growth in 2022. Distributor sales channel includes the sales of electronic dictionaries indirectly to customers through several e-commerce websites and offline distributors including specialist stores, retail stores, and others. Additionally, factors including ease of use, high flexibility, higher accessibility to a broad range of products, and others are among the key prospects driving the growth of the distributor sales channel segment.

Based on end-user, the educational institutions segment accounted for the maximum revenue share in the year 2022. Electronic dictionaries are crucial assets for educational institutions and helps students in language learning, vocabulary expansion, and exam preparations, among others. Factors including the expansion of educational institutions, rising adoption of higher education enrolments, and growing international student mobility trends are among the key prospects fostering the growth of the educational institutions segment.

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Based on region, North American region accounted for the largest revenue share in the year 2022. The increasing utilization of electronic dictionary in educational institutions and rising number of international student enrollments in educational institutes in North America are primary factors driving the growth of electronic dictionary market in the region. Moreover, the rising tourism activities and increasing utilization of electronic dictionary by tourists for language support and instant translations are further boosting the growth of the market in the North American region.

Key Market Highlights

  • Globally, electronic dictionary market is divided based on the sales channel into direct sales and distributor sales.

  • In the context of end-user, the market is separated into educational institutions, business enterprise, language learners, and travelers.

  • The market is geographically divided into five regions: North America, Europe, Asia-Pacific, Latin America, Middle East & Africa.

  • North America and Asia-Pacific are estimated to support the market growth during the forecast period in terms of the large presence of market players combined with high expenditures on advancements in electronic dictionary market.

Browse Full Report & TOC https://ift.tt/gctTSf9 

List of Major Global Electronic Dictionary Market Players

The market research report examines various market factors to determine the key drivers, limitations, and opportunities affecting market players. The report includes a SWOT analysis, regional analysis, and segment analysis to give a complete view of the market situation. This evaluation helps to identify possible growth opportunities through the implementation of technology, product utilization, business strategies, and the launch of new products. The following are major market players operating in the market environment —

• CASIO COMPUTER CO. LTD.

• Canon Electronic Business Machines (H.K.) Co. Ltd.

• ECTACO Inc.

• ELLTON ENTERPRISE PTE LTD

• APKPure

• Merriam-Webster Incorporated

• Vasco Electronics

• SHARP CORPORATION

• iFLYTEK Corporation

• Hanvon Technology Co. Ltd.

Global Electronic Dictionary Market Segmentation: 

  • By Sales Channel

  • Direct Sales

  • Distributor Sales

  • By End-User

    • Educational Institutions

    • Business Enterprise

    • Language Learners

    • Travelers

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Key Questions Covered in the Electronic Dictionary Market Report

  • Based on current market trends and future predictions, which geographical region will have the largest impact on the electronic dictionary growth in the coming years?

  • Which region/country is anticipated to witness the highest CAGR during the forecast period, 2023-2030?

    • Asia-Pacific is anticipated to register fastest CAGR growth during the forecast period due to rapid pace of urbanization, expansion of educational institutions, rising adoption of higher education enrolments, and other related factors.

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Topnotch research organizations and institutions to comprehend the regional and global commercial status use the data produced by Consegic Business Intelligence Pvt Ltd. Our reports comprise in-depth analytical and statistical analysis on various industries in foremost countries around the globe.

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‘Lost in Translation’ With Bill Simmons and Amanda Dobbins - The Ringer - Translation

Sofia Coppola directs

Focus Features


The Ringer’s Bill Simmons and Amanda Dobbins head down to the hotel bar at the Park Hyatt in Tokyo to rewatch Sofia Coppola’s Lost In Translation, starring Bill Murray, Scarlett Johannson, and Giovanni Ribisi.

Producer: Craig Horlbeck

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‘Lost in Translation’ With Bill Simmons and Amanda Dobbins - The Ringer - Translation

Sofia Coppola directs

Focus Features


The Ringer’s Bill Simmons and Amanda Dobbins head down to the hotel bar at the Park Hyatt in Tokyo to rewatch Sofia Coppola’s Lost In Translation, starring Bill Murray, Scarlett Johannson, and Giovanni Ribisi.

Producer: Craig Horlbeck

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Monday, September 4, 2023

Best language translation AI DeepL vs ChatGPT vs Bard - Geeky Gadgets - Translation

DeepL vs ChatGPT vs Google Bard

For language translation tasks, traditional machine translation systems like Google Translate and those based on Statistical Machine Translation (SMT) or Neural Machine Translation (NMT) have been specifically optimized for translation and generally outperform GPT models in terms of accuracy and fluency. These systems have been trained on large bilingual or multilingual corpora and are fine-tuned for translation tasks.

GPT models like GPT-4 can perform translation tasks, but they are not specialized for it. Their translation capabilities are a byproduct of their general language understanding. They are trained on a wide variety of text, including multilingual text, but are not fine-tuned for translation specifically.

Therefore, they may be less accurate and less fluent than specialized machine translation systems for complex or nuanced translations such as DeepL. If you would like to learn more about the differences between DeepL vs ChatGPT vs Google Bard check out the video embedded below kindly created by translation specialist Adrian Probst.

DeepL vs ChatGPT vs Google Bard

Other articles you may find of interest on the subject of  ChatGPT :

What is DeepL

DeepL has been a game-changer in the machine translation industry since its inception in 2017. The company employs a unique neural network (NN) architecture that has redefined the way sentences are translated. This technology enables DeepL to capture even the slightest nuances in language and replicate them in the translation.

The quality of DeepL’s machine translation is not just a claim but has been empirically validated through blind tests. In these tests, professional translators unknowingly pick the most accurate translation among different options, and DeepL has been shown to outperform its competitors by a factor of 3:1.

DeepL offers a flexible and versatile translation service that caters to various use-cases. Whether you’re translating entire documents, web pages, images, or emails, DeepL has got you covered. The service is accessible across multiple devices, allowing you to translate content whether you’re at your desk or on the move.

Features:

  1. Document Translation: DeepL provides a web translator and desktop apps that let users translate all sorts of documents while preserving the original fonts, images, and formatting.
  2. Web Page Translation: The DeepL for Chrome extension allows users to translate entire web pages without having to leave their browser, offering a seamless translation experience.
  3. Multi-Device Support: DeepL’s translation technology can be accessed through various platforms, including browsers, browser extensions, desktop and mobile apps, as well as through an API for more customized solutions.

Overall, DeepL sets itself apart with its unparalleled translation quality and wide array of features, offering a robust and highly accurate translation service that is ahead of its competitors.

What are the advantages of using GPT AI systems for translation?

  1. Contextual Understanding: GPT models can better understand context and may therefore provide translations that are more in tune with the surrounding content.
  2. Multi-Tasking: If you’re building a system that requires not just translation but also other natural language processing tasks, using a GPT model could reduce the complexity of having multiple specialized models.

Disadvantages:

  1. Inaccuracy: GPT models might produce translations that are less accurate or idiomatic than those from specialized systems.
  2. Resource-Intensive: GPT models require more computational resources for inference, which might be overkill for a simple translation task.

Best practices:

  1. Supplement, Don’t Replace: Use GPT models to supplement specialized translation systems, rather than replacing them.
  2. Post-Processing: After obtaining a translation from a GPT model, it may be useful to post-process the text to correct any glaring errors.
  3. Contextual Information: If possible, provide as much context as needed when asking the model to translate. The more context the model has, the better it can translate the text.

While GPT systems can perform translation tasks, their output may not be as accurate or fluent as that of specialized translation systems. They can, however, be useful in scenarios where contextual understanding or multi-tasking capabilities are important.

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The Dictionary of the Jamaican Language takes you bak tu skuul - Jamaica Gleaner - Dictionary

The Jamaican language, popularly referred to as (Jamaican) Patwa, is a significant component of brand Jamaica. However, despite its high international visibility and mounting global interest, it is severely under-resourced in its homeland.

The language has benefitted from the work of outstanding linguists such as Beryl Loftman Bailey whose book Jamaican Creole Syntax (1966) was the first technical grammar of the language, and Frederic G. Cassidy and Robert B. Le Page’s Dictionary of Jamaican English (DJE), which was the first scholarly dictionary prepared. While these works have enjoyed much attention in academia, they are not as known as they should be by ordinary Jamaicans, and they are consulted even less.

Admittedly, on the market are numerous phrase books, glossaries, and dictionaries prepared by laypeople, but these tend to suffer from one or more of the following issues: incorrect part of speech identification; mismatch between the part of speech, the definition, and the example sentence; and incomplete information, forcing Jamaican into English structure. One exception is Eric Rosenfeld’s comprehensive Jamaicasaurus, However, like all of the others (including the scholarly works), it only describes those areas in which Jamaican is different from Standard English. Unfortunately, this common approach of only treating the differences ends up making our vibrant language look malnourished.

FILL THE GAP

To fill the gap, work began in earnest this month on the Dictionary of the Jamaican Language (DJL). The DJL will be a bilingual, unidirectional dictionary; bilingual because the headwords are in Jamaican and the definitions in English; unidirectional because there is no reverse section where the headwords are in English and the definitions are given in Jamaican. The latter will be done at a later stage. The main plan is for the dictionary to be web-based but we may contemplate a print version based on demand. The DJL is coming at an opportune time when there is an urgent need for general-purpose dictionaries and learners’ grammars to support the aims of the National Standards Curriculum, as well as the teaching and learning of Jamaican as a second/foreign language.

Scholarly dictionaries such as the DJE and Richard Allsopp’s Dictionary of Caribbean English Usage (DCEU) attempt to treat both Jamaican and Jamaican English between the same two covers. Additionally, they are intended as supplements to dictionaries such as Webster’s Third New International Dictionary and the Oxford English Dictionary, which cover metropolitan varieties of English. In keeping with their supplemental nature, they mostly list ‘Jamaicanisms’, i.e. words and senses that were considered unique to Jamaica. For example, the only sense the DJE lists for Jamaican sik (sick) is “to sicken, to make sick”, reflecting its use as a transitive verb; because, at that time, that was the only meaning different from standard English. However, Jamaicans also use the word sik as an adjective, e.g. di sik man, and as a stative verb, e.g. di biebi did sik. The latter usage is one way in which the Jamaican word is different from its English source; a feature which Jamaican shares with several West African languages where words denoting properties and states tend to be verbs. The DJL will reflect this aspect of the language rather than trying to force Jamaican into the structures of English and Latin.

The DJL will focus on contemporary usage but, since it aims to be a full record of the Jamaican language, it will include words and senses that have been used throughout the history of the language. Because of the contemporary focus, the order of senses will not necessarily reflect their historical development. Current senses will be listed before older, more dated, ones. Since the speakers of the Jamaican language are in full preparation mode for the back-to-school season, we decided to announce the start of our work on the dictionary by presenting to the nation a little over 30 of the entries to be included in the DJL which are related to school life.

STRUCTURE OF DJL ENTRIES

The headword will be followed by the part of speech. Although we have abbreviated the part of speech below because of space constraints, in the actual dictionary, the part of speech will be spelt out. The part of speech is usually followed by the sense or senses associated with that specific part of speech. Where a word has multiple senses, those senses are numbered consecutively. In cases where additional information about the use of the word/sense may be useful, this is written in small capitals and placed before the relevant sense. Some of these usage labels include “dated”, for words that are old-fashioned (mostly used by grandparents), “offensive” (likely to offend, degrade, upset), “dormant” (no longer in use), and “historical” (still used but only when talking about the past). Each sense is followed by a made-up example sentence which helps to illustrate how the word is used. In the web-based dictionary, each headword will be accompanied by at least one audio file which contains the pronunciation of the word.

Since the DJL is meant to contribute to the standardisation of the language, headwords will be written using the Cassidy-JLU Writing System (CJLU), which is an easy-to-learn phonemic system that was developed by Jamaica-born linguist Frederic Cassidy and amended by the Jamaican Language Unit (JLU). The beauty of this system is that, even if you are seeing or hearing a word for the first time, it doesn’t take long to work out its spelling or pronunciation.

The DJL editorial team comprises a chief editor, Joseph Farquharson; assistant editor, Tajay Henry, and three subeditors, Tali Thorney, Carson Thomas and Donikue Campbell. The initial phase of the DJL is planned to last between 2023 and 2025. This phase is made possible by financial support from the CHASE Fund.

DJL ENTRIES

Abbreviations: intr., intransitive; n., noun; phr., phrase; stat., stative; tr., transitive; v. verb

baal-ed-i-tiicha n. OFFENSIVE. a term of address used by children to taunt a boy sporting a bald head. Baal-ed-i-tiicha, wiet til skuul uova.

baks lonch n. cooked food served for lunch in a disposable rectangular or square container. Bai di taim mi riich a kyantiin, baks lonch don.

bak-tu-skuul n. the period just before the beginning of the school year that is used to make preparations. Dongtoun ful op chruu a bak-tu-skuul ya nou.

big skuul n. (for basic and primary-school students) any education level above the one they are at.

Kim api se shi a go big skuul Septemba a kom.

boblz n. a hair accessory for girls comprising an elastic cord with a small ball at each end. Mi lov wen mi mada plat op mi ier an put iin di priti boblz dem.

brait spaaks n. a person who is quick-witted; but, more commonly, someone who is good at book learning. = SPAAKS. Mi no shak se shi paas ar egzam kaa mi nuo se shi a brait spaaks.

brieks n. 1. = BRIEKS TAIM. 2. any snack that is (intended to be) eaten during the short scheduled break during school hours. Mi figat mi brieks pan i dainin tiebl dis maanin.

brieks taim n. a short scheduled break during the schoolday which allows students to refresh themselves. = BRIEKS. Notn no iina yu lonch pan fi brieks taim so yu afi bai sitn a tok shap.

dons bat n. OFFENSIVE. a person who is slow at book learning. Im neva du im uomwork gud. Im a dons bat.

eksasaiz buk n. 1. a ruled book with either a soft or a hard cover (measuring roughly 4.9 x 6.9 in.), primarily used for writing in schools. Dem nowadiez eksasaiz buk no iizi fi mash op. 2. DATED. a ruled book with a soft cover that is primarily used for writing in schools. Mi eksasaiz buk ful op a mats.

fos braitis n. (in schools where students are streamed based on performance) the class at each grade level with the top-performing students. Mi mash op di egzam so mi a-go ina fos braitis neks ier.

freshaz n. a new student at a college or university, especially during the orientation period. Di freshaz dem a kom iin orli fi kalek dem pakij.

grob n. a new student who is bullied by older students to perform menial or degrading tasks.

Luk ou lang wi sen di grob fi go bai pati an im kyaahn kom bak yet. v. tr. to bully a new student by forcing them to perform menial or degrading tasks. Di fos wiik mi de a ai skuul di biga bwai dem grob mi.

guomin taim n. = GUOMIN UOM TAIM.

guomin uom taim n. the scheduled time one departs for home at the end of a day-long activity such as school or work. = GUOMIN TAIM. Di bel jos ring so dat miin se a guomin uom taim nou.

jain op phr. v. tr. 1. to link or connect two or more things. Dem jain op di buod dem an mek wahn siit. 2. to work together; co-operate; collaborate. Di tuu a dem jain op fi pie di bil. phr. v. stat. be linked or connected. Di tuu piis a waya dem jain op. phr. v. intr. to become a member of a group or organisation. Dem a plan paadna agen bot dis taim mi naa jain op. n. a style of handwriting in which the letters of a word are joined to each other: cursive. = JAININ OP. Sins mi staat taip mi kyaahn rait ina jain op agen.

jainin op n. = JAIN OP n.

kalijaz n. a student who attends a teachers’ college or community college. Di kalijaz dem ful op di kuk shap.

kapi skecha n. a student who copies from the work of others. = kapi teka. Mi a chrai tel tiicha se Jan a kapi skecha.

kapi teka n. = KAPI SKECHA.

kraab tuo = KRAB TUO.

krab tuo n. poor handwriting. Da kraab tuo ya aad fi riid.

lainz n. a sentence or passage that is copied multiple times by hand as a form of punishment in school. Mi kech a skuul liet so di klaas priifek gi mi lainz fi du.

push paint n. 1. a type of pencil with an internal chamber that holds the graphite stick. The stick comes out by squeezing or twisting a part of the pencil. Di push paint we mi a yuuz ron outa led. 2. a wood-cased pencil with a loose graphite stick that can be pushed through the wood casing from either end. It aad fi rait wid push paint.

rang bang n. an X mark used by a teacher grading student work to indicate an incorrect answer. Mi a-go stodi aad fi Mats kaa mi no waahn get no rang bang.

red ingk n. 1. ink that is red in colour. Di red ingk kech mi kluoz. 2. a pen that has red ink. Beg yu wahn red ingk mek mi maak dem piepa ya.

skuulaz n. a student who attends school, especially up to the secondary level. Di ruobot taksi dem no waahn kyar no skuulaz.

spaaks n. = BRAIT SPAAKS.

stiki n. a check mark used by a teacher to indicate that a student’s work is correct or has been checked. = uk stik. Luk umoch stiki mi get ina mi buk.

taim tiebl n. = TAIMZ TIEBL.

taimz tiebl n. a list containing multiples of a series of numbers, used by students as a study aid. = TAIM TIEBL. Tiich se wi fi nuo wi taimz tiebl.

tiich n. an affectionate term of address for a teacher. Tiich, mi jos waahn fi tangk yu fi tek kier a Jahnoi.

uk stik n. 1. a check mark used by a teacher to indicate that a student’s work is correct or has been checked. Johnny get nof uk stik ina im buk. 2. a long stick with a crook or a v-shaped hook at one end used for hoisting or lowering things. Di uk stik kudn riich di manggo dem pan di tap lim. 3. a sturdy stick roughly 2 ½ ft in length (cut from a tree in such a way so there is a short hook at one end), used while clearing land or weeding with a machete. Di faama dem yuuz dem uk stik wen dem a bush di plies so di mashiet no chap dem.

wash out phr. v. tr. 1. use water or other types of liquid to remove unwanted material from something. Mi tuu tayad fi wash out di tuu likl piis a kluoz. 2. (of an event) to cancel because of rain. Di fans dem beks kaa rien wash out di mach. 3. to have an abortion. Im gi mi sitn fi jringk fi wash out di biebi. phr. v. intr. (of a place that is normally dry) covered by a lot of water; flooded. Mi faada grong wash out an im luuz evriting. n. the process of using a substance to stimulate the evacuation of the bowels. Wen alidie don wi afi tek wash out.

Email carilingjm@gmail.com for further information and how to support the work of DJL.

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Sunday, September 3, 2023

How AI is gaining ground in simultaneous interpretation - EL PAÍS USA - Translation

Until recently, it would have sounded like science fiction. Imagine making a video call to an individual who lives on the other side of the world. This person speaks Japanese, but through your headphones, you hear their words in English. It’s similar to having a live interpreter, who can translate different languages in person or online. In this case, however, there is no human involved, but rather artificial intelligence (AI) that can provide simultaneous interpretation.

Kudo, a company that has grown in the market by connecting interpreters with corporate clients, has taken a step forward by including a technology that performs simultaneous translations in online conferences. Its job is not to translate written sentences, but rather to carrying out voice translations, allowing participants in a video conference to hear the translation as if they had an interpreter present.

In a demonstration carried out for EL PAÍS, Tzachi Levy, Kudo’s product manager, speaks in English while he is interpreted almost in real time in Spanish. Although the voice sounds robotic and there is a slight delay compared to a human translation, the result is still surprising. While a human interpretation usually has a delay of five to seven seconds, the artificial experience is around 10.

The company has 20 corporate clients that already use this service, which continues to be constantly improved. The tool works on Kudo’s own video conferencing platform, but is also integrated with Microsoft Teams, which is popular in the corporate world.

At Kudo, they explain that in situations where 100% accuracy in translation is required, the human interpreter will always be the best option. Levy gives the example of European Parliament sessions: “Artificial systems will probably not be used, but in smaller meetings, where there are no interpreters available at the time, this solution can be effective.”

Levy argues that the advance of AI is inevitable, and that progress that was originally thought to take five to 10 years has been achieved in a matter of months. The field is evolving so quickly that, he estimates, within the next year AI could accurately achieve simultaneous translations in 90% of common situations.

Artificial and human intelligence

In June of this year, Wired did a comparison of Kudo technology with interpretation performed by experts. Humans obtained significantly superior results compared to the AI tool, mainly in regards to understanding context. Claudio Fantinuoli, head of technology at Kudo and creator of the automatic translation tool, tells EL PAÍS that the model evaluated by Wired three months ago has already been improved by 25%. The next step in development is to integrate generative artificial intelligence to make the user experience more pleasant: for the voice to sound more fluid, human and able to capture intonation.

One of the main challenges, according to Fantinuoli, is getting AI to interpret the context of the narrative, in other words, to read between the lines. This challenge is still great, but progress is being made thanks to “large language models,” such as the one behind ChatGPT.

Fantinuoli, who is also a university professor and teaches young students aspiring to become professional interpreters, says “he sees no conflict” between AI and human training. What’s more, he believes human interpreters will always be of higher quality. “I try to make them [his students] understand that robots are a reality in the market and that they have to be at the top of their game,” he says. “AI is driving them to be very good interpreters.”

One voice, many languages

Another option that is set to appear in the near future is to add the speaker’s own voice to the interpretation. Fantinuoli says that technically this is already feasible, and it will be integrated into the company’s service in a matter of months. Other companies have already tested the possibility of using a single voice to play content in different languages, but not simultaneously. This is the case of the ElevenLabs platform, which can interpret 30 different languages with the same voice.

The process is simple: a user uploads an audio of more than a minute of the voice they want to replicate. From this file, the tool reads aloud the text they want, either in the source language or other available ones. The platform allows the user to make custom adjustments, fine-tuning the clarity of the reading or even exaggerating the style of the voice, according to their preferences. The program not only imitates the voice, but also captures and reflects distinctive nuances, such as tone, rhythm, accent and intonation.

Recently, Meta launched a multimodal translation model, which can perform speech-to-text, speech-to-speech, text-to-speech and text-to-text translations for up to 100 languages, depending on the task. This could be of use to polyglot speakers, those who mix two or three languages in a single sentence. Meta claims that this model is capable of discerning the different languages at play and carrying out the corresponding translations. While it still shows some small errors, it works quite well when the sentence is expressed in a single language. The tool is available for free in the Beta version.

Claudio Fantinuoli says the Meta’s new tool is surprising, comparing it to “the ChatGPT of spoken discourse.” “What they do is put together all the models, which can do many tasks at the same time. This is the future,” he says.

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