Taltan Dictionary Project aims to preserve endangered Indigenous language - CFTKTV - Dictionary

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Taltan Dictionary Project aims to preserve endangered Indigenous language  CFTKTV

Translate scanned PDF documents with Document translation - Microsoft - Translation

Today, the Document translation feature of Translator, a Microsoft Azure Cognitive Service, adds the ability to translate PDF documents containing scanned image content, eliminating the need for customers to preprocess them through an OCR engine before translation.

Document translation was made generally available last year, May 25, 2021, allowing customers to translate entire documents and batches of documents into more than 110 languages and dialects while preserving the layout and formatting of the original file. Document translation supports a variety of file types, including Word, PowerPoint and PDF, and customers can use either pre-built or custom machine translation models. Document translation is enterprise-ready with Azure Active Directory authentication, providing secured access between the service and storage through Managed Identity.

Translating PDFs with scanned image content is a highly requested feature from Document translation customers. Customers find it difficult to segregate PDF documents which have regular text or scanned image content through automation. This creates workflow issues as customers have to route PDF documents with scanned image content first to an OCR engine before sending them to document translation.

Document translation services now have the intelligence

• to identify whether the PDF document contains scanned image content or not,
• to route PDFs containing scanned image content to an OCR engine internally to extract text,
• to reconstruct the translated content as regular text PDF while retaining the original layout and structure.

Font formatting like bold, italics, underline, highlights, etc. are not retained for scanned PDF content as OCR technology does not currently capture them. However, font formatting is preserved while translating regular text PDF documents.

Document translation currently supports PDF documents containing scanned image content from 68 source languages into 87 target languages. Support for additional source and target languages will be added in due course.

Now it’s easier for customers to send all PDF documents to Document translation directly and let it decide when and how to use the OCR engine efficiently.

For customers already using Document translation, no code change is required to be able to use this new feature. PDF documents with scanned content can be submitted for translation like any other supported document formats.

We are also pleased to announce that the Document translation adds support for scanned PDF document content with no additional charges to customers. Two pricing plans are available for Document translation through Azure — the Pay-as-you-go plan and the D3 volume discount plan for higher volumes of document translation. Pricing details can be found at aka.ms/TranslatorPricing.

Learn how to get started with Document translation at aka.ms/DocumentTranslationDocs.
Send your feedback to mtfb@microsoft.com.

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AppTek Achieves Top Ranking at the International Workshop in Spoken Language Translation's (IWSLT) 2022 Evaluation Campaign - PR Newswire - Translation

Company's Spoken Language Translation System Ranks First in Isometric Speech Translation Track Which Is Critical in Improving Automatic Dubbing and Subtitling Workflows

MCLEAN, Va., May 26, 2022 /PRNewswire/ -- AppTek, a leader in Artificial Intelligence (AI), Machine Learning (ML), Automatic Speech Recognition (ASR), Neural Machine Translation (NMT), Text-to-Speech (TTS) and Natural Language Processing / Understanding (NLP/U) technologies, announced that its spoken language translation (SLT) system ranked first in the isometric speech translation track at the 19th annual International Workshop on Spoken Language Translation's (IWSLT 2022) evaluation campaign.

Isometric translation is a new research area in machine translation that concerns the task of generating translations similar in length to the source input and is particularly relevant to downstream applications such as subtitling and automatic dubbing, as well as the translation of some forms of text that require constraints in terms of length such as in software and gaming applications.   

"We are thrilled with the results of the track," said Evgeny Matusov, Lead Science Architect, Machine Translation, at AppTek. "This is a testament to the hard work and skill of our team, who have been focusing on developing customized solutions for the media and entertainment vertical."

AppTek entered the competition to measure the performance of its isometric SLT system against other leading platforms developed by corporate and academic science teams around the world.  Participants were asked to create translations of YouTube video transcriptions such that the length of the translation stays within 10% of the length of the original transcription, measured in terms of characters. AppTek participated in the constrained task for the English-German language pair, which is the one out of the three pairs evaluated at IWSLT with the highest target-to-source length ratio in terms of characters count.

Submissions were evaluated on two dimensions – translation quality and length compliance with respect to source input. Both automatic and human assessment found the AppTek translations to outperform competing submissions in terms of quality and the desired length, with performance matching "unconstrained" systems trained on significantly more data. An additional evaluation performed by the task organizers showed that creating synthetic speech from AppTek's system output leads to automatically dubbed videos with a smooth speaking rate and of higher perceived quality than when using the competing systems.

"The superior performance of AppTek's isometric speech translation system is another step towards delivering the next generation of speech-enabled technologies for the broadcast and media markets", said Kyle Maddock, AppTek's SVP of Marketing. "We are committed to delivering the state-of-the-art for demanding markets such as media and entertainment, and isometric translation is a key component for more accurate automatic subtitling and dubbing workflows."

AppTek scientists Patrick Wilken and Evgeny Matusov will present the details of AppTek's submission at this year's IWSLT conference held in Dublin on May 26-27, 2022.

The full IWSLT 2022 results can be found here.

About AppTek
AppTek is a global leader in artificial intelligence (AI) and machine learning (ML) technologies for automatic speech recognition (ASR), neural machine translation (NMT), natural language processing/understanding (NLP/U) and text-to-speech (TTS) technologies.  The AppTek platform delivers industry-leading, real-time streaming and batch technology solutions in the cloud or on-premises for organizations across a breadth of global markets such as media and entertainment, call centers, government, enterprise business, and more. Built by scientists and research engineers who are recognized among the best in the world, AppTek's multidimensional 4D for HLT (human language technology) solutions with slice and dice methodology covering hundreds of languages/dialects, domains, channels and demographics drive high impact results with speed and precision.  For more information, please visit http://www.apptek.com.

Media Contact:
Kyle Maddock
202-413-8654
[email protected]

SOURCE AppTek

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Lewis County Elks Dictionary Project - Lewis Herald - Dictionary

[unable to retrieve full-text content]

Lewis County Elks Dictionary Project  Lewis Herald

Translate scanned PDF documents with Document translation - Microsoft - Translation

Today, the Document translation feature of Translator, a Microsoft Azure Cognitive Service, adds the ability to translate PDF documents containing scanned image content, eliminating the need for customers to preprocess them through an OCR engine before translation.

Document translation was made generally available last year, May 25, 2021, allowing customers to translate entire documents and batches of documents into more than 110 languages and dialects while preserving the layout and formatting of the original file. Document translation supports a variety of file types, including Word, PowerPoint and PDF, and customers can use either pre-built or custom machine translation models. Document translation is enterprise-ready with Azure Active Directory authentication, providing secured access between the service and storage through Managed Identity.

Translating PDFs with scanned image content is a highly requested feature from Document translation customers. Customers find it difficult to segregate PDF documents which have regular text or scanned image content through automation. This creates workflow issues as customers have to route PDF documents with scanned image content first to an OCR engine before sending them to document translation.

Document translation services now have the intelligence

• to identify whether the PDF document contains scanned image content or not,
• to route PDFs containing scanned image content to an OCR engine internally to extract text,
• to reconstruct the translated content as regular text PDF while retaining the original layout and structure.

Font formatting like bold, italics, underline, highlights, etc. are not retained for scanned PDF content as OCR technology does not currently capture them. However, font formatting is preserved while translating regular text PDF documents.

Document translation currently supports PDF documents containing scanned image content from 68 source languages into 87 target languages. Support for additional source and target languages will be added in due course.

Now it’s easier for customers to send all PDF documents to Document translation directly and let it decide when and how to use the OCR engine efficiently.

For customers already using Document translation, no code change is required to be able to use this new feature. PDF documents with scanned content can be submitted for translation like any other supported document formats.

We are also pleased to announce that the Document translation adds support for scanned PDF document content with no additional charges to customers. Two pricing plans are available for Document translation through Azure — the Pay-as-you-go plan and the D3 volume discount plan for higher volumes of document translation. Pricing details can be found at aka.ms/TranslatorPricing.

Learn how to get started with Document translation at aka.ms/DocumentTranslationDocs.
Send your feedback to mtfb@microsoft.com.

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Research translation, innovation updates top BOT's May meeting - The Well : The Well - The Well - Translation

News about University research — how it’s being done and how it’s applied to solve problems — dominated the Board of Trustees meeting May 18-19.

The Office of Undergraduate Research showed how important undergraduates are in making new discoveries in its May 19 presentation. Gabriella Hesse ’22, now a School of Medicine student, presented her research about sex-related tendencies in the development of certain brain diseases. Lauren McShea, a rising sophomore majoring in environmental health sciences, showed how she helped develop low-cost ways to monitor well water for harmful bacteria.

Because so many Carolina faculty are involved in research, “our undergraduates get to be in proximity to that, to take part in that,” said Troy Blackburn, associate dean for undergraduate research. “It’s learning by doing. It’s taking classroom knowledge and using it to solve problems.”

With the full implementation of the new IDEAs in Action curriculum this fall, about 19,000 undergraduates will be required to engage in original research to meet the new research and discovery requirement, Blackburn said.

Student Gabriella Hesse, left, and teaching associate professor Sabrina Robertson share research done on Parkinson’s disease. (Jon Gardiner/UNC-Chapel Hill)

Next steps in research

Provost and Chief Academic Officer J. Christopher Clemens spoke about helping researchers develop their work when asking that the Institute for Convergent Science, based in the College of Arts & Sciences since 2017, become a pan-University, interdisciplinary center.

“Our faculty are very good at sponsored research,” Clemens, the institute’s founding director, told the University Affairs committee. But basic research skills are very different from those required for building a company. “We see ICS as a bridge that helps faculty navigate the pathways they must go through if they’re going to take research from the lab and out into the world.”

The institute, located in the Genome Sciences Building, operates in a three-lane research-to-market process called “Ready, Set, Go.” The middle lane is the newest to the University. “It’s called pre-commercial development,” Clemens said. “It awards money based on proposals,” allowing researchers to continue to develop their ideas without having to take entrepreneurial risks.

“It needed to be elevated. It will help us recruit faculty who will grow the research infrastructure and support other initiatives,” said Chancellor Kevin M. Guskiewicz.

The board approved the institute, which will be led by Gregory P. Copenhaver, Chancellor’s Eminent Professor of Convergent Science and associate dean of research and innovation in the College of Arts & Sciences.

Trustee Vinay B. Patel called the proposed downtown Innovation District “very exciting news, not just for the University but for the entire region.” (Jon Gardiner/UNC-Chapel Hill)

On to innovation and commercialization

Researchers who are ready to be entrepreneurs can call upon the many resources of Innovate Carolina.

“The gap between research and discovery and impact is wide, long, resource-intensive and risky. And this is the place where Innovate Carolina sits,” Michelle Bolas, the University’s chief innovation officer and executive director of Innovate Carolina, told the Strategic Initiatives committee.

One of the department’s recent successes is approval of the 20,000-square-foot Innovation Hub at 136 E. Rosemary St. The downtown Chapel Hill space is being renovated as a new home for Innovate Carolina and a startup accelerator, with co-working and meeting spaces.

The Innovation Hub, scheduled to open in April 2023, and the redevelopment of Porthole Alley will be key components of a proposed downtown Innovation District. “We will be one of the only leading universities with an Innovation District at the edge of our campus, on our front door,” Bolas said.

Trustee Vinay B. Patel called the development “very exciting news, not just for the University but for the entire region,” when he presented an update to the full board.

Board of Trustees Chair David L. Boliek Jr. responded that the new district shows “this board’s commitment to economic development and the vibrancy of Chapel Hill and the 100 block of Franklin Street.”

Guskiewicz announced another tangible result of innovative research attracting funding in his meeting remarks — a $65 million award from the National Institute of Allergy and Infectious Diseases to the UNC Gillings School of Global Public Health. The grant will establish the Antiviral Drug Discovery Center to develop oral antivirals that can combat pandemic-level viruses like COVID-19. The center builds upon UNC’s Rapidly Emerging Antiviral Drug Development Initiative.

Incoming chief of UNC Police Brian James addresses the board during the UNC Board of Trustees full board meeting May 19. (Jon Gardiner/UNC-Chapel Hill)

A new slate of campus leaders

Guskiewicz introduced trustees to four recently hired members of his leadership team:

• Janet Guthmiller, new dean of Adams School of Dentistry and Claude A. Adams Distinguished Professor, effective Oct. 15.
• James W.C. White, new dean of the College of Arts & Sciences, effective July 1.
• Brian James, new chief of UNC Police, effective July 1.
• Amy McConkey, new director of state affairs.

Not in attendance but also mentioned in the chancellor’s remarks was Valerie Howard, new dean of School of Nursing, effective Aug. 1.

Another new leader at the May meeting was Student Body President Taliajah Vann, who took the oath of office to become an ex officio member of the board for the next year. “I am excited to work within this space,” Vann said.

In addition to the Institute for Convergent Science, the trustees voted to approve:

Trustees also received the following reports:

• A budget update and a plan to implement OneStream software as the new campus-wide budget tool, from Nathan Knuffman, vice chancellor for finance and operations.
• An overview of the Office of Institutional Integrity and Risk Management, from George Battle, vice chancellor for institutional integrity and risk management.
• Remarks from Katie Musgrove, Employee Forum chair, who reminded trustees that staff are struggling because of the Great Resignation and a “plague of lingering vacancies” that have left them “overtasked and burned out.”

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Meta Tries Making Human Evaluation of Machine Translation More Consistent - Slator - Translation

Although automatic evaluation metrics, such as BLEU, have been widely used in industry and academia to evaluate machine translation (MT) systems, human evaluators are still considered the gold standard in quality assessment.

Human evaluators use quite different criteria when evaluating MT output. These are determined by their linguistic skills and translation-quality expectations, exposure to ΜΤ output, presentation of source or reference translation, and unclear descriptions of the evaluation categories, among others. 

“This is especially [problematic] when the goal is to obtain meaningful scores across language pairs,” according to a recent study by a multidisciplinary team from Meta AI that includes Daniel Licht, Cynthia Gao, Janice Lam, Francisco Guzman, Mona Dia, and Philipp Koehn.

To address this challenge, the authors proposed in their May 2022 paper, Consistent Human Evaluation of Machine Translation across Language Pairs, a novel metric. Called XSTS, it is more focused on meaning (semantic) equivalence and cross-lingual calibration, which enables more consistent assessment.

Adequacy Over Fluency

XSTS — a cross-lingual variant of STS (Semantic Textual Similarity) — estimates the degree of similarity in meaning between source sentence and MT output. The researchers used a five-point scale, where 1 represents no semantic equivalence and 5 represents exact semantic equivalence.

The new metric emphasizes adequacy rather than fluency, mainly due to the fact that assessing fluency is much more subjective. The study noted that subjectivity leads to higher variability and the preservation of meaning is a pressing challenge in many low-resource language pairs.

The authors compared XSTS to Direct Assessment (i.e., the expression of a judgment on the quality of MT output using a continuous rating scale) as well as some variants of XSTS, such as Monolingual Semantic Textual Similarity (MSTS), Back-translated Monolingual Semantic Textual Similarity (BT+MSTS), and Post-Editing with critical errors (PE).

They found that “XSTS yields higher inter-annotator agreement compared [to] the more commonly used Direct Assessment.”

Cross-Lingual Consistency

“Even after providing evaluators with instruction and training, they still show a large degree of variance in how they apply scores to actual examples of machine translation output,” wrote the authors. “This is especially the case, when different language pairs are evaluated, which necessarily requires different evaluators assessing different output.”

To address this issue, the authors proposed using a calibration set that is common across all languages and consists of MT output and corresponding reference translation. The sentence pairs of the calibration set should be carefully selected to cover a wide quality range, based on consistent assessments from previous evaluations. These scores can then be used as the “consensus quality score.”

Evaluators should assess this fixed calibration set in addition to the actual evaluation task. Then the average score each evaluator gives to the calibration set should be calculated.

According to the authors, “The goal of calibration is to adjust raw human evaluation scores so that they reflect meaningful assessment of the quality of the machine translation system for a given language pair.”

Given that the calibration set is fixed, quality is fixed, and the average score each evaluator assigns to any sentence pair in the set should be the same. Hence, the score assigned by each evaluator and the official fixed score can be used to make adjustments to each evaluator’s score. 

“If this evaluator-specific calibration score is too high, then we conclude that the evaluator is generally too lenient and their scores for the actual task need to be adjusted downward, and vice versa,” explained the authors.

For example, if the consensus quality score for the calibration set is 3.0 but an evaluator assigned it a score of 3.2, then 0.2 from all their scores for the actual evaluation task should be deducted.

The authors concluded that the calibration leads to improved correlation of system scores to subjective expectations of quality based on linguistic and resource aspects, as well as to improved correlation with automatic scores, such as BLEU.

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