Supported Languages

The pre-trained and the supported languages for all Document Understanding ML Packages can be found in the table below.

ML Package	Description	Pre-trained Languages	Supported Languages
UiPathDocumentOCR	Reads document text.	English French German Italian Portuguese Romanian Spanish	English French German Italian Portuguese Romanian Spanish
DocumentUnderstanding	Extracts commonly occurring data points from any type of structured or semi-structured documents, building an ML model from scratch.	n/a	Latin-based languages Cyrillic languages Greek left-to-right Japanese (Preview) Chinese (Preview)
DocumentClassifier	Classifies documents using a custom trained ML model.	n/a	Language-agnostic (supports any language as long as the OCR supports it)
Invoices	Extracts commonly occurring data points from invoices.	English French German Portuguese Romanian Spanish	Latin-based languages Cyrillic languages Greek left-to-right
InvoicesAustralia	Extracts commonly occurring data points from Australian invoices.	English	Latin-based languages Cyrillic languages Greek left-to-right
InvoicesIndia	Extracts commonly occurring data points from Indian invoices.	English	Latin-based languages Cyrillic languages Greek left-to-right
InvoicesJapan	Extracts commonly occurring data points from Japanese invoices.	Japanese (Preview)	Japanese (Preview)
InvoicesChina	Extracts commonly occurring data points from Chinese invoices.	Chinese (Preview)	Chinese (Preview)
Receipts	Extracts commonly occurring data points from receipts.	English Finnish French German Norwegian Romanian Spanish	Latin-based languages Cyrillic languages Greek left-to-right
PurchaseOrders	Extracts commonly occurring data points from purchase orders.	English German	Latin-based languages Cyrillic languages Greek left-to-right
UtilityBills	Extracts commonly occurring data points from utility bills.	English	Latin-based languages Cyrillic languages Greek left-to-right
IDCards	Extracts commonly occurring data points from ID cards.	Australia Austria Belgium Canada Croatia Cyprus Finland France Germany Hong Kong Hungary India Italy Netherlands Poland Romania Spain Switzerland United Kingdom USA (all 50 states plus DC)	Latin-based languages Cyrillic languages Greek left-to-right
Passports	Extracts commonly occurring data points from passports.	International	International
RemittanceAdvices	Extracts commonly occurring data points from remittance advices.	English	Latin-based languages Cyrillic languages Greek left-to-right
DeliveryNotes	Extracts commonly occurring data points from delivery notes.	English German	Latin-based languages Cyrillic languages Greek left-to-right
W2	Extracts commonly occurring data points from W-2 forms.	English	Latin-based languages Cyrillic languages Greek left-to-right
W9	Extracts commonly occurring data points from W-9 forms.	English Spanish	Latin-based languages Cyrillic languages Greek left-to-right
FormExtractor	Provides the endpoint required by the Form Extractor activity.	n/a	Latin-based languages Cyrillic languages Greek left-to-right Asian languages
IntelligentFormExtractor	Provides the endpoint required by the Intelligent Form Extractor activity.	n/a	Latin-based languages Cyrillic languages Greek left-to-right Asian languages
IntelligentKeywordClassifier	Provides the endpoint required by the Intelligent Keyword Classifier activity.	n/a	Latin-based languages Cyrillic languages Greek left-to-right Asian languages
HandwritingRecognition	Reads handwritten text.	English	English

Observations

• To train a model on Japanese documents, use either the DocumentUnderstanding package or the InvoicesJapan package.
• To train a model on Chinese documents, use either the DocumentUnderstanding package or the InvoicesChina package.
• To train a model on Latin script documents, use any package except for InvoicesJapan or InvoicesChina.
• For the supported languages, retraining may be required to get the expected accuracy if the documents are considerably different from the original model training dataset.
• For the supported languages which are not pre-trained by the model, you can train a model with your own data in AI Center, assuming the OCR engine supports it as well.
• Automatic reformatting of dates in a standard yyyy-mm-dd format for Asian languages is currently supported only for Japanese. For documents in other Asian languages, you can extract the dates as String content type and format it in the RPA workflow.