CrowdsourcingHallucinationComputeaccessCulturalcontextlossAIstartupMultilingualmodelsDialectvariationProverbtranslationRepresentationmattersDiasporacommunityLinguafrancabiasTonallanguageWhoowns thedata?AcademicpartnershipGPTdoesn'tspeak mylanguageLanguagedocumentationMultilingualspeakerTrainingdataimbalanceDatascarcityOraltraditionAnnotationlaborTransliterationGovernmentpolicyTokenizationbiasLanguagejusticeLanguageendangermentOpensourceColoniallegacyCode-switchingAfricanAIHonorificsMorphologicalcomplexityScriptdiversityDigitalinclusion"Lowresource"VoiceinterfacesIndigenousdatasovereigntyCommunitydatasetsFine-tuningOut-of-vocabularywordsLow-resourcelanguageSpeech-to-textCrowdsourcingHallucinationComputeaccessCulturalcontextlossAIstartupMultilingualmodelsDialectvariationProverbtranslationRepresentationmattersDiasporacommunityLinguafrancabiasTonallanguageWhoowns thedata?AcademicpartnershipGPTdoesn'tspeak mylanguageLanguagedocumentationMultilingualspeakerTrainingdataimbalanceDatascarcityOraltraditionAnnotationlaborTransliterationGovernmentpolicyTokenizationbiasLanguagejusticeLanguageendangermentOpensourceColoniallegacyCode-switchingAfricanAIHonorificsMorphologicalcomplexityScriptdiversityDigitalinclusion"Lowresource"VoiceinterfacesIndigenousdatasovereigntyCommunitydatasetsFine-tuningOut-of-vocabularywordsLow-resourcelanguageSpeech-to-text

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.


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