inca Languages

Multilingual Conversations with inca

Nexxt Intelligence is committed to enabling inclusive and global market research, and leverages state-of-the-art conversational AI to support 90+ language variants across all inca services, with an even more diverse 140+ languages available for AI Coding!

Language Support
Afrikaans
af
90%
98%
Albanian
sq
90%
66%
Amharic
am
56%
93%
Arabic (MSA)
ar
90%
97%
Arabic (Egyptian)
ar_EG
83%
100%
Arabic (Levantine)
ar_LB
81%
92% †
Arabic (Gulf)
ar_SA
83%
92% †
Arabic (Maghrebi)
ar_MA
83%
92% †
Armenian
hy
84%
87%
Aymara
ay
Azerbaijani
az
85%
96%
Bambara
bm
Basque
eu
83%
92%
Belarusian
be
Bengali
bn
80%
90%
Bhojpuri
bho
Bosnian
bs
90%
100%
Bulgarian
bg
86%
95%
Burmese (Myanmar)
my
69%
98%
Catalan
ca
86%
94%
Cebuano
ceb
Chinese (Mandarin, Simplified)
zh_CN
81%
86%
Chinese (Mandarin, Traditional)
zh_TW
82%
81% †
Chinese (Cantonese, Traditional)
zh_HK
96%
Corsican
co
Croatian
hr
90%
100%
Czech
cs
88%
98%
Danish
da
90%
98%
Dhivehi
dv
Dogri
doi
Dutch
nl
90%
96%
English
en
100%
98%
English (UK)
en_GB
100%
100%
Esperanto
eo
Estonian
et
86%
94%
Ewe
ee
Tagalog (Filipino)
tl
86%
100%
Finnish
fi
90%
95%
French (France)
fr
90%
98%
French (Canada)
fr_CA
90%
93% †
Frisian
fy
Galician
gl
89%
96%
Georgian
ka
83%
98%
German (Germany)
de
87%
98%
German (Switzerland)
de_CH
88%
93%
German (Austria)
de_AT
89%
96%
Greek
el
86%
94%
Guarani
gn
Gujarati
gu
78%
99%
Haitian Creole
ht
Hausa
ha
Hawaiian
haw
Hebrew
iw
87%
96%
Hindi
hi
87%
96%
Hmong
hmn
Hungarian
hu
87%
97%
Icelandic
is
90%
95%
Igbo
ig
Ilocano
ilo
Indonesian
id
85%
99%
Irish
ga
Italian
it
90%
98%
Japanese
ja
84%
94%
Javanese
jv
83%
100%
Kannada
kn
84%
100%
Kazakh
kk
83%
78%
Khmer
km
74%
100%
Kinyarwanda (Rwanda)
rw
69%
86%
Konkani
gom
Korean
ko
77%
95%
Krio
kri
Kurdish
ku
Kurdish (Sorani)
ckb
Kyrgyz
ky
Lao
lo
69%
97%
Latin
la
Latvian
lv
89%
100%
Lingala
ln
Lithuanian
lt
85%
98%
Luganda
lg
Luxembourgish
lb
Macedonian
mk
90%
99%
Maithili
mai
Malagasy
mg
Malay
ms
80%
100%
Malayalam
ml
78%
92%
Maltese
mt
Maori
mi
Marathi
mr
81%
93%
Meiteilon (Manipuri)
mni-Mtei
Mizo
lus
Mongolian
mn
75%
94%
Nepali
ne
79%
93%
Norwegian
no
92%
69%
Nyanja (Chichewa)
ny
Odia (Oriya)
or
Oromo
om
Pashto
ps
Persian
fa
82%
98%
Polish
pl
85%
96%
Portuguese (Portugal)
pt
90%
98%
Portuguese (Brazilian)
pt_BR
89%
99%
Punjabi
pa
78%
97%
Quechua
qu
Romanian
ro
93%
100%
Russian
ru
85%
100%
Samoan
sm
Sanskrit
sa
Scots Gaelic
gd
Sepedi
nso
Serbian
sr
89%
88%
Shona
sn
Sindhi
sd
Sinhala (Sinhalese)
si
79%
98%
Slovak
sk
88%
94%
Slovenian
sl
92%
92%
Somali
so
Southern Sotho (Sesotho)
st
79%
89%
Spanish (Spain)
es
91%
97%
Spanish (Mexico)
es_MX
90%
94%
Spanish (Argentina)
es_AR
90%
94%
Sundanese
su
78%
98%
Swahili
sw
83%
88%
Swedish
sv
91%
98%
Tajik
tg
Tamil
ta
80%
93%
Tatar
tt
Telugu
te
80%
96%
Thai
th
82%
97%
Tigrinya
ti
Tsonga
ts
61%
96%
Turkish
tr
85%
98%
Turkmen
tk
Twi (Akan)
ak
Ukrainian
uk
88%
94%
Urdu
ur
87%
90%
Uyghur
ug
Uzbek
uz
82%
96%
Venda
ve
57%
92%
Vietnamese
vi
84%
99%
Welsh
cy
Xhosa
xh
82%
98%
Yiddish
yi
Yoruba
yo
Zulu
zu
82%
91%

† indicates that a language variant has not been directly tested, but rather estimated based on performance of a more common language variant.

inca SmartProbe Support Scores

Each inca SmartProbe language is automatically evaluated to determine how well it performs in various circumstances. Based on the scores associated with each language in the table above, we provide the following guidance when using inca SmartProbe. For more details on best practices, please refer to our inca Platform documentation or SmartProbe API documentation , depending on which product you are using.

90 - 100%
Suitable for simple and complex conversations; customization is optional.
80 - 89%
Suitable for simple and complex conversations; best practices recommended for complex conversations.
70 - 79%
Suitable for simple and complex conversations; trained model and other best practices recommended.
60 - 69%
Suitable for simple conversations; trained models and other best practices are required.
50 - 59%
Suitable for very simple conversations; trained models and other best practices are required.

inca Transcription Support Scores

Each inca Platform language is automatically evaluated to determine how well user responses can be transcribed in real-time. The Transcription Support Score in the table above indicates how accurately inca can transcribe reasonably high-quality voice recordings each language.

The score can be interpreted as indicating how accurately speech can be transcribed into text under ideal conditions, based on empirical testing and rounded up. However, transcription mistakes will inevitably happen at some point, and so inca allows users to review and make changes to the transcribed text before submitting.

For all languages, we advise providing the following guidance to respondents:

  • Use a high-quality recording device, if available.
  • Minimize background noise, if possible.
  • Speak clearly and enunciate.
  • Review and correct the transcription before submitting the response.