GPTdoesn'tspeak mylanguageVoiceinterfacesLanguagedocumentationCommunitydatasetsLanguageendangermentLanguagejusticeCulturalcontextlossOraltraditionScriptdiversityDatascarcityMorphologicalcomplexityAfricanAIMultilingualmodelsRepresentationmattersLinguafrancabiasDialectvariationAIstartupLow-resourcelanguageHallucinationHonorificsOpensourceFine-tuningProverbtranslationSpeech-to-textDigitalinclusionDiasporacommunityTonallanguageGovernmentpolicyColoniallegacyCrowdsourcingWhoowns thedata?Multilingualspeaker"Lowresource"IndigenousdatasovereigntyTransliterationTrainingdataimbalanceCode-switchingTokenizationbiasComputeaccessOut-of-vocabularywordsAcademicpartnershipAnnotationlaborGPTdoesn'tspeak mylanguageVoiceinterfacesLanguagedocumentationCommunitydatasetsLanguageendangermentLanguagejusticeCulturalcontextlossOraltraditionScriptdiversityDatascarcityMorphologicalcomplexityAfricanAIMultilingualmodelsRepresentationmattersLinguafrancabiasDialectvariationAIstartupLow-resourcelanguageHallucinationHonorificsOpensourceFine-tuningProverbtranslationSpeech-to-textDigitalinclusionDiasporacommunityTonallanguageGovernmentpolicyColoniallegacyCrowdsourcingWhoowns thedata?Multilingualspeaker"Lowresource"IndigenousdatasovereigntyTransliterationTrainingdataimbalanceCode-switchingTokenizationbiasComputeaccessOut-of-vocabularywordsAcademicpartnershipAnnotationlabor

Local Language NLP Bingo! - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. GPT doesn't speak my language
  2. Voice interfaces
  3. Language documentation
  4. Community datasets
  5. Language endangerment
  6. Language justice
  7. Cultural context loss
  8. Oral tradition
  9. Script diversity
  10. Data scarcity
  11. Morphological complexity
  12. African AI
  13. Multilingual models
  14. Representation matters
  15. Lingua franca bias
  16. Dialect variation
  17. AI startup
  18. Low-resource language
  19. Hallucination
  20. Honorifics
  21. Open source
  22. Fine-tuning
  23. Proverb translation
  24. Speech-to-text
  25. Digital inclusion
  26. Diaspora community
  27. Tonal language
  28. Government policy
  29. Colonial legacy
  30. Crowdsourcing
  31. Who owns the data?
  32. Multilingual speaker
  33. "Low resource"
  34. Indigenous data sovereignty
  35. Transliteration
  36. Training data imbalance
  37. Code-switching
  38. Tokenization bias
  39. Compute access
  40. Out-of-vocabulary words
  41. Academic partnership
  42. Annotation labor