sentence
stringlengths
1
479
ᎠᏂᏍᎬᏘ 31Ꮑ 1927 ᎯᎸᏍᎩ ᎢᎧᏁᏥ ᏓᎪᏪᎳᏂ ᎪᎯ ᎢᎪᎯ ᎠᏆᏓᏂᎳᏉ ᏱᎦᏗ ᎠᏎᏉᏉ
ᏱᏂᏥᏪᎭ ᎥᏝ ᎩᎶ ᎰᏩ ᏴᎦᏰᎳ ᎾᏆᏛᎿᏕᎦ ᎠᏮᏌᏉ ᎾᏆᏛᎾᏕᎦ ᎥᎦᏕᏨᏉ ᏥᏙᏩᏕᎦ
ᎠᏫᏄᏣ ᎠᏮᏕᏥᎸᏉ ᎾᏆᏛᎾ ᎾᏉ ᏑᏕᏘᏴᏓ ᎴᏓᎵᏃ ᎢᏯᏅᏙ ᎬᏮᏕᏨᎯ ᎠᏉᎯᏳᏗ
ᎤᏁᎳᏅᎯ ᏗᏆᏓᏂᎸᏤᎸᎯ ᎨᏒᎢ ᎠᎵᎮᎵᏍᏗ ᏗᎨᏒ ᏫᏄᏛᏅ ᎠᏉᎯᏳᏗ ᏧᏅᏟ ᏧᏩᏛᏛ
ᎨᏒᎢ ᎠᏉᎯᏳ ᎠᎴ ᎤᎦᏴᎵᎨ ᎤᏩᏛᏛ ᎨᏒᎢ ᎤᏟᏉ ᎤᏲᎢᏳ ᏱᏄᎵᏍᏔᏁ ᏯᏇᎵᎡ
ᏍᏗᎩᏛ ᎤᎦᎵᏍᏗ ᎢᏳᏍᏗ ᎢᎦᏓᏅᏓᏗᏍᎪᎢ
ᎠᎬᏱᏃ ᎠᎬᏱ ᏕᎦᎵᏍᏗᏍᎪ ᎠᏎᎨ ᏅᎩᎭ ᎢᏳᏪᏅᏍᏗ ᏕᎦᎵᏗᏍᎪ ᏘᎵ ᎩᎳᏃ ᏳᏅᏂᏍ
ᏱᎨᎵ Ꮓ ᎩᎳ ᎠᎹ ᏥᏙᏗᏍᎪ ᏗᎩᏚᏗᏱ ᏃᏭᏃ ᏣᎵᏟᎭᏭᏴ ᎠᎹ Ꮓ ᏕᎦᏑᏴᏍᎪ ᏗᎵ ᎦᏚ Ꮎ
ᏯᎦᏖᎫᏍᏔᎾ ᎢᏣ ᏃᏭ ᎩᎳ ᏘᎸ ᏐᏓ ᏥᎸᏍᎪ ᏃᏭᎴ ᎧᎵᏎᏥ ᏍᎩᏅ ᏃᏭ ᎠᏉᏰᏂ ᎧᎵ ᎢᎦ
ᎦᏐᏳᎩᏍᎪ ᏍᎩᎾ ᏐᏊ ᏂᎦᎵᏍᏓ ᎦᏄᎵ ᏌᏊᏃ ᎤᏆᎶ ᏃᏭ ᎦᏄᎶᏙᏗ ᏍᎩ ᎦᏚ ᎦᏄᎵ ᏃᏭ
ᏂᎦᎵᏍᏗ ᏃᏭᏅ Ꮟ ᎯᎸ ᏳᏪᏅᏍᏗ ᏗᎵᏥᏍᏙᏗ ᎩᎳ ᎤᏅᏏᏌᏛ ᏂᎦᎵᏍᏗ
Durbin: ᏝᎮ ᏱᏃᎭᎵᏓ ᎠᏫ ᏧᏂᏲᏍᏗ ᏥᎡᎲ
Cherokee Hunter: ᎨᏍᏗ ᏥᏃᎠᎵᏙᎯ ᏱᎩ ᏌᏊᎡᎦ ᎢᏯᎩᏃᎭᎵᏙᎸ ᏥᎾᏩᏛᎲᏊᏅ
ᎥᏍᏊ ᎠᏫ ᎩᎶ ᎤᏲᏢ ᎨᏍᏗ ᎠᏮᏍ ᏱᏥᎳ ᎩᎶ ᏦᎩᎾᎵᎪᏒ ᏦᎢᏕ ᏃᏥᎥ ᎣᏣᎣᏍ
ᎣᎦᏛᎦᏅ ᎩᎶ ᏚᏍᏓᏲᏢ ᎪᎯ ᎢᏴ ᏃᏊ ᏄᏢᏍᏔᏅ ᎢᎬᏱ ᏝᏍᏊ ᏲᏥᎪᎡ ᏭᎶᏒ
ᎢᏲᎪᏱ ᎣᏣᎢᏒ ᏥᎦᎾᏏᏂᏐ ᎢᏳᏍᏗ ᏂᎦᎵᏍᏗᏍᎬ ᎯᎠ ᎢᏗᏜ ᏭᎿᎷᏒ ᎤᎿᏅ
ᏬᎩᎷᏣ ᏚᎾᏗᏩᏒ ᎩᎦ ᎤᏩᏍᏉᏨᏍᏔᏅ ᎣᏦᎷᏅᏒ ᎦᏚᏏᏱ ᏧᎦᎾᎥ ᎩᎶ
ᎤᏲᏢ
Durbin: ᎡᏥᏁᏎ
Cherokee Hunter: Ꭵ ᎠᏴᏛᏍᏊ ᏌᏊ ᏳᏩᎪᏗ ᏍᏊ ᏍᎩ ᏥᏄᎵᏍᏔᏅ ᎩᎦ ᏍᏊ
ᏚᏩᏍᏬᏨᏍᏔᏅ ᏥᎨᏒ ᎡᎵᎠᏯ ᎢᏅᏯ ᎣᏍᏙᎷᏅᎡᏒ Ꭸ ᏥᎦᏅ ᏦᏍᏗᏁᏒ
ᎤᎿᏅ ᎣᏍᏕᏙᎲ ᎾᎥ ᎯᏗᏜ ᎨᏓᎵ ᎤᎿ ᏓᏥᏍᏓᏲᏢ ᎠᏴ Ꮭ ᏱᏗᏥᏍᏓᏲᏞ ᎩᎦ
ᎣᏍᏙᎷᏅᎡᏒ ᎨᏴ ᏬᏍᏗᎾᏩᏛᎲ ᎯᎠᏅᏍᏊ Ꮠ ᏥᏛᏟᎢᎵᏒ Ꮎ ᎡᏥ ᏦᎢᏁ
ᏗᎾᏓᎸ ᎤᏪᏥ ᎠᏧᏣ ᎯᎠᏴ Ꮲ ᏂᎠᏔ ᎣᎢᏂᏃᎭᎸᏒ ᏙᏓᏫᏕᎾ ᏥᎡᎲ ᎾᏅ ᏓᏁᎸ
ᏂᏓᎵ ᏅᏲ ᎧᏃᎾ ᏗᎠᎧᎲ ᎣᏣᏗᏍᎪ ᎤᎿᎾ ᎤᎿ ᎣᎢᏂᎦᏐᏏᏗᎲ ᏚᎴᏅ ᎠᏫ
ᏥᏲᎮᎸ ᏙᏍᏗᏍᏓᏲᏏᎶᎥ ᏫᏙᎢᏂᎩᏴ ᎣᎢᎾᏂᎢᏒ ᏁᎳᎩᏅ Ꮠ ᏂᎠᏅᎿ ᎤᎿ ᎦᏚᏍ
ᏗᏜ ᎤᎿ ᏬᎢᎾᏂᎢᏒ ᏅᏃ ᎠᏗᏢ ᏙᎢᏂᎾᏗᏫᏒ ᎠᏫ ᏙᏍᏙᎷᏂᏒ ᏥᏈᏍᏙᎲ ᏃᏭᎴ
ᏥᏙᏍᏖᏍᏔᏅ ᎤᎿ ᏃᏭ ᎬᏩᎦᏘ ᏕᎣᎢᏂᎩᏴ ᏧᎨᏓᎵᏴ ᏗᏜ ᏛᎣᎢᏂᎶᎲ Ꮲ ᏌᎶᎵ
ᏲᏍᏗᎪᎡ
Ꭰurbin: ᎯᎳᎲ Ᏼ ᏍᏗᎷᏤ ᎣᎦᎳᎰᎹ
Wilbur: ᏔᎵᎭ ᏄᏒ ᎢᏳ ᏥᎨᎲ ᎤᎲᏒ ᏐᏁᎳ ᎢᏳ ᎢᏳᏩᏂᎸ
Ꭰurbin: ᎦᎪᎲ ᎡᏍᏗᏩᏛᎯᏙ
Wilbur: ᎠᏴᏃ ᎨᏒ ᎠᏂᏴᏫᏯ ᏂᎦᏙᏉ ᏕᏥᏩᎲᎯᏙ ᏂᏗᎦᎵᏍᏙᏗ Ꭿ ᎠᎬᏱ ᎩᎳ ᎨᏙ ᎠᎭᏂ
ᎣᎦᎳᎰᎹ ᎤᏥᏍᏈᏯ ᎠᏆᏛᎦᏅ Ꭿ ᏍᎩᎾ Ꭽ ᏣᎳᎩ ᎾᎾ ᎭᏂ ᎤᏪᏘ ᏂᏓᏳᏂᎶᏒ
ᎠᏁᎲ ᏍᎩᏉ ᎠᎩᎦᏛᏂᏙᎭ ᏄᎾᏛᎿᏕᎬ ᏃᎴ ᎢᏳᏍᏗ Ꭵ ᎢᏳᏍᏗ ᏄᎾᏛᎿᏕᎬ
ᏍᎩᎾ ᎾᎿ ᎠᏂᏁᎩᎸ ᎠᏂᏁᎸ ᏚᏙᏓᎦᏓ ᎢᏳᏍᏗ ᎾᎾᏛᏁᎵᏙᎲ ᏍᎩᏃ ᏧᏓᎴᏂᏅᏓᏊ
ᏍᎩ ᎢᎬᏩᎵᏍᏔᏅᏓ ᏍᏆᎳ ᏱᏂᎬᏁᎵ Ꭿ ᏱᏂᏥᏫ ᎢᏳᏍᏗ ᏄᎾᏛᎿᏕᎬ Ꭵ ᏧᏙᏓᏚᏓ
Ꭵ ᎠᏂᏁᎸ ᎠᎾᎢᏒ ᎢᎦ ᏧᏓᎴᏅᏓ ᏃᎴ Ꭵ ᏧᏂᎳᏫᏍᏗ ᎨᎰ ᏍᏊ ᏴᏫ ᎢᏳᏍᏗ
ᏂᎨᎦᏛᏁᎲ ᏍᎩ ᏂᎦᏓ ᎢᎬᏩᎵᏍᏔᏅᏓ ᏃᎴ Ꭵ ᎧᏃᎮᏓ ᎨᏐ ᏯᎾᏛᎩ ᎣᏍᏓ ᎧᏃᎮᏓ
ᏱᎩ ᏍᎩᎾ Ꭽ ᏍᎩᎾ Ꭽ ᏱᎬᏩᎵᏍᏔᏅᏓ ᏍᎩᏭ ᏳᏍᏗ ᎭᎩᎧᏛᏂᏙ ᎠᏴ
Ꭰurbin: ᏚᏓᎴᎿᎠᎨ Ꭵ ᎠᎭᏂ ᏃᎴ ᏗᏤᏅᏒ
Wilbur: ᎥᎭᏃ Ꮵ ᎢᎦ ᏍᎩᎾ ᏴᏫ ᏄᏍᏗ ᎤᎾᏂᎩᏍᏗ ᎨᏒ Ꮳ ᏓᎴ ᎾᏍᎩᏂ Ꭵ ᎢᏳᏍᏗ Ꭵ ᏙᏗ
ᏳᏍᏗᏃ ᏴᏓ ᏍᎩᎾ ᏗᎨ ᎡᎵᏍᏗ Ꭵ ᏂᎦᏓ ᎨᎲ Ꮎ ᎤᏍᏗ ᎥᏣ Ꭿ ᏱᏚᏓᎴᎭ ᏍᎩᏯ
ᎢᎦ ᏂᎨᎦᏛᏁᎲ ᏥᏕᎦᎵᏃᎮᎵᏙᎲ ᎤᏒ ᎢᎦ ᎬᏆᎴᏅᏓ Ꭵ ᏍᏗᎩᏓᏃ ᎢᎦᏓ ᎨᏍᏗ Ꭵ
ᎢᏳᏍᏗ ᎢᎨᎦᏛᏁᏗ ᏂᎨᎦᏛᏁ ᎢᏳᏍᏗ ᏯᏂᎩᎠ ᎢᎦᏓ ᎣᏏ ᏄᎾᏛᏅᎯ ᏃᎴ
ᎢᎦᏓ ᎤᏲᎢ ᏄᎾᏛᏅ ᎦᏛᎩᎠ ᏍᎩᏃ ᏥᎦᏗ ᎨᏍᏗ ᎠᏴ ᏱᎪᎵᎦ Ꮟ ᎠᏋᏌᏃ
ᏗᏥᎦᏙᎵ ᏯᏮᏔᏁ ᏱᏥᎦᏔᎮ ᎢᎤᏍᏗ Ꭵ ᏗᏓᎴᏂᏍᎬ ᎨᎵ Ꮟ ᎢᎦᏓ ᎨᏍᏗ ᏰᎵ Ꭵ
ᎠᏂᏐ ᏄᎾᏍᏛ ᎢᎦ ᏯᏂᎩ ᎢᏳᏍᏗ ᎤᏂᎩᏍᏗ ᎨᏒ ᎤᎾᎵᏍᏕᎸᏙᏗ ᎨᏒᎢ
ᏓᏂᏁᎩᎸ ᎤᏲ ᏄᎾᏛᏅ ᎠᎾᏗᏍᎪ Ꭿ Ꮲ ᎢᏅᎯ ᎨᏒ ᎠᏙ ᏗᎨᏒ ᎢᏴ ᏗᏂᏁᎵ ᎨᏒ
ᎡᏍᎦᏊ Ꭿ ᎡᏍᎦᏂ ᏗᏂᏁᎵ ᎦᏚᎲ ᎾᎥᏂᎨ .ᏱᎩ ᎢᏳᏍᏗ ᎦᏛᎩ ᎥᏣᏃ ᏱᏣᎦᏔ
ᏍᎩᎾ Ꭽ ᎤᏥᏈᏯ ᎠᏆᏓᎴᏤᎭ Ꭵ ᏙᏂᏳᏍᏗ ᎠᏓᎴᏂᎭ ᏍᎩᎾ ᎤᏲ ᎢᏂᏗᎬᏩ
ᎾᏛᎿᏕᎩ ᎢᏴ ᏃᎴ ᎮᏍᎦᏂᎨᎲ ᏕᏥᎪᏩᏘᏍᎬ ᎣᏏᏊ ᎢᏳᏍᏗ ᏄᎾᏛᎾᏕᎬ ᎢᎨᎵ
ᎤᏥᏈᏯᏃ ᏔᎵᎭ ᏄᎾᏓᎴ ᏄᏂᏍ ᏄᏂᏍᏗ ᎾᏆᎵᏍᏓᏁ
Ꭰurbin: ᎳᏍᎪ ᏍᎩ ᏱᏄᏍᏗ Ꭵ ᏗᏤᏅᏒ
Wilbur: Ꭵ ᎥᏣᏃ ᏍᎩᎦ ᎠᏩᏓᎴᏤᎮᏃ Ꭵ ᎠᏴ ᏍᎩᎾ ᏗᎦᎳᏫᏍᏗ ᏗᏥᎳᏫᎩ ᎯᎩ Ꭵ
ᎣᏣᏁᎳᏗᏍᎪ ᏂᎦᏓ ᏂᎬ ᏍᎩᎾ ᏙᏣᎦᏎᏍᏙᏔᏂᏓᏍᏗ ᎤᏲᎢ ᏱᏄᏛᎾ ᏍᎩᎾ
ᏬᏥᏃᎮᏍᎪ Ꭵ ᎠᏂᏩᏥᎾ ᏚᎾᏓᏁᎸ ᏚᎾᏙᏢᏒᎢ ᎦᎵᏐᏕ ᏗᎾᏁᏍᎨᏍᎩ ᎪᏍᏞ
social service ᏱᎩ ᎠᏘᏗ ᏥᎩ ᏍᎩᎾ ᎭᏂ ᎬᏂᎨᏒ ᏂᏙᏨᏁᎰ ᎣᏣᏁᎸᏗᏍᎪ
ᏍᎩᏃ Ꭿ ᏮᏓᎴᎩ ᏥᎦᏗ ᎠᏴ ᏄᎾᏛᏅ ᎨᏍᏗ Ꭺ ᏯᏂᎩ Ꭽ ᎭᎾᏗᎠ ᎬᏉᏎ ᎢᎦᏓ
ᎭᏂᏃᎮᏍᎬ ᎨᏍᏗ ᏱᎨᎦᎧᏎᏍᏓᏁᏍᎪ ᏙᏳ ᎤᏲᎢ ᏄᎾᏛᎿ ᎭᎾᏗ ᎨᏍᏗᏃ
ᏱᏥᎪᏩᏓ Ꭵ ᏱᎪᎵᎦ ᏍᎩᎾ ᎭᏂ Ꭿ Ꭵ ᏗᏂᎳᏫᎩ ᎤᎾᏚᏓᎵ ᏧᎾᏤᎵ ᎬᏩᏑᏯᎩᏗ ᎨᎲ
ᏓᏁᎲ ᏍᎦᏚᎩ ᏕᎪᏒᏩᏗᏒᎢ ᏧᎾᎦᏎᏍᏙᏗ
Ꭰurbin: ᏍᎩᏗᏙ ᏄᏍᏧᎥ Ꭵ ᏂᏗᎦᎵᏍᏙᏗᏍᎬᏃ ᏍᏊ Ꭵ ᎦᏲᎵ ᎨᏒ ᏱᎧᏃᎮᎵ ᎥᏍᎩ ᏣᎳᎩ
ᎠᏂᏬᏂᏍᎩ ᎨᏒ Ꮎ ᏣᎳᎩ ᎤᏂᏬᏂᎯᏍᏗ ᎤᏂᎭ ᏍᎩᏳᏍᏗ ᎠᏂᏬᏂᏍᎩ ᎤᎿᏴ
ᏂᏧᎾᏛᎿ Ꮎ ᏌᎷᏱᏴ ᎠᏙᎯᏴ Ꭵ ᏝᏃ ᏳᎾᏚᎵᏍᎪ ᏕᎦᏚᎲ ᏂᏙᏓᏳᎾᏛᏁᏙᏗ Ꭵ
ᏍᎩᏃ ᏣᎳᎩ ᎠᏂᏬᏂᏍᎩ Ꮩ ᎠᏂᏣᎳᎩ ᎨᏒ ᎠᎭᏂᏃ ᏚᏂᎸᏫᏍᏓᏁ ᎤᏟ ᎢᎦ
ᎠᏂᏲᏁᎦ Ꭵ ᏍᎩᏃ ᏍᏗᎩᏓ ᏓᎾᏓᎴᎪ ᏳᏍᏗ
Wilbur: ᏙᎾᎯᏳᏍᏗ ᏗᏓᎴᏂᎭ ᏍᎩᏅ ᎣᏍᏓ ᎭᏂ ᎡᏍᎦᏃ ᎾᎥᏂᎨ ᎠᏂᏁᎩᎵ ᎣᏏ ᏳᏍᏗ
ᏄᎾᏛᏅ ᎤᏙᏳ ᏗᎾᏁᏎᏍᎩ ᏕᎪᏍᎲ ᎢᎦᏓ ᏦᏍᏓ ᏓᏂᏁᎩᎵ Ꭴ ᏍᎩᎾ Ꭲ ᎯᏳ
ᏫᏂᎦᎷᎬᎾ ᏥᎩ ᏍᎩᎾ ᏫᏗᏂᎦᏁᏍᎨᏗ ᎤᎾ ᎢᏴᎢ
Ꭰurbin: Ꭵ ᎢᎦᏓᏛ ᏍᏊ ᎠᏂᏣᎳᎩ ᏥᎩ ᏍᏊ Ꮭ ᏳᎾᏚᎵᏍᎪ Ꮭ Ꭵ Ꮭ ᏳᎾᏚᎵ
Wilbur: ᎠᏂᎾᏰᏍᎬ
Ꭰurbin: ᎥᎲ ᏍᎩ
Wilbur: ᏣᏍᎪᏃ ᏯᏁᎭ ᎩᎶ ᏗᏂᎳᏫᎩ ᎣᏍᏓ ᏫᏗᎬᏩᏃᏏᏐᏗ
Ꭰurbin: ᎩᎳᏃ ᏍᎩᏴ ᎣᏣᎯᎵᏙ ᏓᏲᏣᎴᏅ ᏍᎩ ᏃᏣᏛᏁᎲ ᎣᏥᏃᎮᎵᏙᎲ Ꮎ Ꭵ ᎥᏍᎩ
ᎢᎬᏩᎵᏍᏙᏗ ᎨᏒ ᏍᏗᎯᏓᏃ ᎣᎩᏍᎦᏃᎵ
Wilbur: Ꭵ what means speech not I do not know how to say it ᏳᏁᎦ ᎤᏤᎵ ᏓᎦᏙᎵᏏ
i breakdown communication ᎢᏳᏍᏗ ᎾᏆᎵᏍᏓᏁ ᏍᎩ Ꭿ
Ꭰurbin: ᏍᎩᏃ Ꭵ ᏗᏓᎴᏅᎢᏍᏗ ᎨᏒ Ꮎ Ꭵ ᏛᏟᏃᎮᏟᏙᎲ ᏍᎩᎾ ᎤᏟ ᎢᎦ
Wilbur: ᎠᏎᏃᎨ ᎢᏥᎯᎵ ᏍᎩᎾ ᎣᏍᏓ ᎢᏨᏁᏗ
Ꭰurbin: Ꭵ ᎣᏥᎯᎵᏛ
Wilbur: ᏔᎵᎭ ᎾᏕᏘᏴ ᏃᎴ ᎡᎵᏍᏗ ᏰᎵᏭ ᏍᏗᎩᏓ ᎣᏍᏛ ᎢᏳᎵᏍᏔᏂᏓ ᎨᎮᏍᏗ
Ꭰurbin: Ꭵ about five maybe
Wilbur: maybe never ᏂᏗᎦᎵᏍᏙᏗᎲ ᎠᏕᎳ ᎧᏂᎦᏗ ᏍᏊᏅ ᎠᏎ ᎡᎳᏗ ᏁᏨᏁ ᎠᏕᎳ
Ꭰurbin: ᎢᎸᏍᎩᏛ ᎢᏯᏂ ᏕᎨᏥᏲᏌ ᏚᏂᎸᏫᏍᏓᏁᎲ ᎠᎭᏂ ᎯᎠᏊ ᏏᏅᏓ ᏔᎵ ᎢᏅᏓ ᏥᎨᏒ
Wilbur: ᎡᎵᏍᏗ ᏃᏭ ᎦᏲᎳ ᎢᏳᏍᏗ ᏂᏗᎦᎵᏍᏙᏗᏍᎬ ᏍᎩᎾ ᏍᎩᏳ ᏫᏂᎦᎷᎬᎾ ᎨᎲ
ᏍᎩᎾ ᎣᏍᏓ ᎢᏳᎾᎵᏍᏓᏁᏗ ᏕᏥᎸᏫᏍᏓᏁᎲ ᏃᎴ ᏂᏗᎦᎵᏍᏙᏗᎭ ᎨᏍᏗ ᏳᎾᏚᎵ
ᎤᏅᏌ ᎭᏂᎾᏰᏍᎦ ᏧᎾᏓᏂᎸᎢᏍᏗ ᏍᎩᏍ
Ꭰurbin: ᎥᎲ
Wilbur: ᏍᎨᎠ ᏄᏍᏗ ᏴᏫᏯ ᎠᏎ that is the India way ᎠᏛᏗ ᎢᎦᏓ
Ꭰurbin: ᎠᏎᏍᎩᏂ ᎠᏊ ᎨᎵᏍᎪ ᏴᏫ Ꭵ ᎣᏍᏓ ᏱᏗᎧᏃᎯᏎᎳ Ꭵ ᎢᎬᏩᎵᏍᏔᏂᏓᏍᏗ ᎨᏒ
ᏯᏃᎵᎩ ᎨᎵ ᏳᎾᏚᎳ ᎤᎾᏖᎳᏗᏍᏗ
Wilbur: ᏱᏓᏥᎶᏍᏔᏂ ᎠᏴ ᎤᏐᏱ ᎠᏴ ᏐᏱᏣᎨᎲ ᎠᎬᏱ Ꮎ ᏣᏅᏔ mutual help
program ᏃᏊ ᎠᏴ ᏬᎩᎷᏤᎳ ᏍᎩ ᏳᏍᏗ Ꭵ ᎠᎬᏱ ᏍᏊ ᎠᎩᏍᏚᎢᏒᎢ ᏥᎣᎵ
ᎠᏴ ᏍᎩ ᏱᎬᏆᏚᎳ ᏩᏥᎾ ᏍᎩᎾ ᏄᏍᏛ ᏧᏛᏅᎢᏍᏗ ᎠᏎᏃ ᎠᏂᏃᎮᏍᎬ ᏂᎦᏓ
ᎤᏬᏚᎯ ᏄᏅᏁᎴᎸ ᏍᎩᎾᎢ ᎤᏲᎢ ᏂᏣᏛᏅ ᏕᏥᏁᎩᎸ ᎤᏍᏓ ᏂᏓᏨᏴᏁᎵ ᏃᎴ
ᎠᏈᏱᏗ ᎨᏒ ᏍᏗ ᏓᏣᏈᏴᎮᏏ ᏃᏊᏃ Ꮩ ᏱᎦᎵᏍᏓ ᎬᏈᏱᏗ ᏂᎨᏒᎾ ᏱᎩ ᎦᏙᎯ
ᎠᏓᏁᎵ ᏱᎩ ᎦᏲᏟ ᏩᏥᎾ ᎤᏓᏁᏖᏗ ᏱᎩ ᏍᎩᎾ ᎦᎵᏐᏕ ᏗᎾᏁᏍᎨᏍᎩ ᎨᎲ
Qualla houses ᎠᎾᏗᏍᎪ ᏍᎩᎿ ᎠᏂ ᎤᎾᏤᎵ ᏂᎦᎵᏍᏗ ᏍᎩ ᎢᎦ ᏓᏲᏒ
ᎦᎵᏐᏕ ᎠᏌᎲ ᎠᏳᏁᏍᎨᎲᎴ ᏱᎩ ᎯᎸᎯᏳ ᏃᏊ ᎠᏴ ᏆᏤᎵ ᎢᎬᏩᎵᏍᏙᏗ

Dataset Card for ChrEn

Dataset Summary

ChrEn is a Cherokee-English parallel dataset to facilitate machine translation research between Cherokee and English. ChrEn is extremely low-resource contains 14k sentence pairs in total, split in ways that facilitate both in-domain and out-of-domain evaluation. ChrEn also contains 5k Cherokee monolingual data to enable semi-supervised learning.

Supported Tasks and Leaderboards

The dataset is intended to use for machine-translation between Enlish (en) and Cherokee (chr).

Languages

The dataset contains Enlish (en) and Cherokee (chr) text. The data encompasses both existing dialects of Cherokee: the Overhill dialect, mostly spoken in Oklahoma (OK), and the Middle dialect, mostly used in North Carolina (NC).

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

[More Information Needed]

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

Many of the source texts were translations of English materials, which means that the Cherokee structures may not be 100% natural in terms of what a speaker might spontaneously produce. Each text was translated by people who speak Cherokee as the first language, which means there is a high probability of grammaticality. These data were originally available in PDF version. We apply the Optical Character Recognition (OCR) via Tesseract OCR engine to extract the Cherokee and English text.

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

The sentences were manually aligned by Dr. Benjamin Frey a proficient second-language speaker of Cherokee, who also fixed the errors introduced by OCR. This process is time-consuming and took several months.

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

The dataset was gathered and annotated by Shiyue Zhang, Benjamin Frey, and Mohit Bansal at UNC Chapel Hill.

Licensing Information

The copyright of the data belongs to original book/article authors or translators (hence, used for research purpose; and please contact Dr. Benjamin Frey for other copyright questions).

Citation Information

@inproceedings{zhang2020chren,
  title={ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization},
  author={Zhang, Shiyue and Frey, Benjamin and Bansal, Mohit},
  booktitle={EMNLP2020},
  year={2020}
}

Contributions

Thanks to @yjernite, @lhoestq for adding this dataset.

Downloads last month
315