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Datasets:
mnazari
/
nena_speech_1_0_test

Tasks:
Automatic Speech Recognition
Text-to-Speech
Translation
Languages:
Assyrian Neo-Aramaic
Chaldean Neo-Aramaic
Hulaulá
Size:
10K<n<100K
License:
Dataset card Files Community
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mnazari commited on
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1 Parent(s): e3e2556

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  1. README.md +3 -3
  2. audio/alanish/dev.tar +1 -1
  3. audio/alanish/test.tar +1 -1
  4. audio/alanish/train.tar +1 -1
  5. audio/alqosh/dev.tar +1 -1
  6. audio/alqosh/test.tar +1 -1
  7. audio/alqosh/train.tar +1 -1
  8. audio/amedia (christian)/dev.tar +1 -1
  9. audio/amedia (christian)/test.tar +1 -1
  10. audio/amedia (christian)/train.tar +1 -1
  11. audio/amedia (jewish)/dev.tar +1 -1
  12. audio/amedia (jewish)/test.tar +1 -1
  13. audio/amedia (jewish)/train.tar +1 -1
  14. audio/ankawa/dev.tar +1 -1
  15. audio/ankawa/test.tar +1 -1
  16. audio/ankawa/train.tar +1 -1
  17. audio/aqra (town)/dev.tar +1 -1
  18. audio/aqra (town)/test.tar +1 -1
  19. audio/aqra (town)/train.tar +1 -1
  20. audio/aqra (xərpa)/dev.tar +1 -1
  21. audio/aqra (xərpa)/test.tar +1 -1
  22. audio/aqra (xərpa)/train.tar +1 -1
  23. audio/aradhin (christian)/dev.tar +1 -1
  24. audio/aradhin (christian)/test.tar +1 -1
  25. audio/aradhin (christian)/train.tar +1 -1
  26. audio/aradhin (jewish)/dev.tar +1 -1
  27. audio/aradhin (jewish)/test.tar +1 -1
  28. audio/aradhin (jewish)/train.tar +1 -1
  29. audio/arbel/dev.tar +1 -1
  30. audio/arbel/test.tar +1 -1
  31. audio/arbel/train.tar +1 -1
  32. audio/arbuš/dev.tar +1 -1
  33. audio/arbuš/test.tar +1 -1
  34. audio/arbuš/train.tar +1 -1
  35. audio/ashitha/dev.tar +1 -1
  36. audio/ashitha/test.tar +1 -1
  37. audio/ashitha/train.tar +1 -1
  38. audio/azax/dev.tar +1 -1
  39. audio/azax/test.tar +1 -1
  40. audio/azax/train.tar +1 -1
  41. audio/baqopa/dev.tar +1 -1
  42. audio/baqopa/test.tar +1 -1
  43. audio/baqopa/train.tar +1 -1
  44. audio/bariṭle/dev.tar +1 -1
  45. audio/bariṭle/test.tar +1 -1
  46. audio/bariṭle/train.tar +1 -1
  47. audio/barwar of qočanəṣ/dev.tar +1 -1
  48. audio/barwar of qočanəṣ/test.tar +1 -1
  49. audio/barwar of qočanəṣ/train.tar +1 -1
  50. audio/barwar/dev.tar +1 -1
README.md CHANGED
@@ -88,7 +88,7 @@ To find out more about loading and preparing audio datasets, head over to [hf.co
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  The NENA Speech dataset is a multimodal dataset that consists of three different kinds of examples:
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- 1. **Unlabelled speech examples:** these contain audio of speech (`audio`) but no accompanying transcription (`transcription`) or translation (`translation`). This is useful for representation learning.
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  2. **Transcribed speech examples:** these contain both audio and transcription of speech. These are useful for machine learning tasks like automatic speech recognition and speech synthesis.
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  3. **Transcribed and translated speech examples:** these kinds of examples contain audio, transcription, and translation of speech. These are useful for tasks like multimodal translation.
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@@ -107,7 +107,7 @@ Make sure to filter for the kinds of examples you need for your task before befo
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  "proficiency": "proficient as mom",
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  "age": "70's",
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  "crowdsourced": true,
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- "unlabelled": true,
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  "interrupted": true,
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  "client_id": "gwurt1g1ln" ,
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  "path": "et/train/nena_speech_0uk14ofpom196aj.mp3",
@@ -123,7 +123,7 @@ Make sure to filter for the kinds of examples you need for your task before befo
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  - `proficiency (string)`: The proficiency of the speaker
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  - `age (string)`: The age of the speaker (e.g. `"20's"`, `"50's"`, `"100+"`)
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  - `crowdsourced (bool)`: Indicates whether the example was crowdsourced as opposed to collected from existing language documentation resources
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- - `unlabelled (bool)`: Usually an empty field
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  - `interrupted (bool)`: Indicates whether the example was interrupted with the speaker making sound effects or switching into another language
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  - `client_id (string)`: An id for which client (voice) made the recording
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  - `path (string)`: The path to the audio file
 
88
 
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  The NENA Speech dataset is a multimodal dataset that consists of three different kinds of examples:
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+ 1. **Unlabeled speech examples:** these contain audio of speech (`audio`) but no accompanying transcription (`transcription`) or translation (`translation`). This is useful for representation learning.
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  2. **Transcribed speech examples:** these contain both audio and transcription of speech. These are useful for machine learning tasks like automatic speech recognition and speech synthesis.
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  3. **Transcribed and translated speech examples:** these kinds of examples contain audio, transcription, and translation of speech. These are useful for tasks like multimodal translation.
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  "proficiency": "proficient as mom",
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  "age": "70's",
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  "crowdsourced": true,
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+ "unlabeled": true,
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  "interrupted": true,
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  "client_id": "gwurt1g1ln" ,
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  "path": "et/train/nena_speech_0uk14ofpom196aj.mp3",
 
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  - `proficiency (string)`: The proficiency of the speaker
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  - `age (string)`: The age of the speaker (e.g. `"20's"`, `"50's"`, `"100+"`)
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  - `crowdsourced (bool)`: Indicates whether the example was crowdsourced as opposed to collected from existing language documentation resources
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+ - `unlabeled (bool)`: Usually an empty field
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  - `interrupted (bool)`: Indicates whether the example was interrupted with the speaker making sound effects or switching into another language
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  - `client_id (string)`: An id for which client (voice) made the recording
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  - `path (string)`: The path to the audio file
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