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Translating Story Map from one language to another using Deep Learning


A story map is a web map that is created for a given context with supporting information so that it becomes a stand-alone resource. It integrates maps, legends, text, photos, and video. Story maps can be built using Esri's story map templates and are a great way to quickly build useful information products tailored to one's organization needs. Using the templates, one can publish a story map without writing any code. One can simply create a web map, supply the text and images for the story, and configure the template files to create a story map.

Sometimes, there is a need to convert the text of a story map from one language to another so that it can be understood by nonnative language speaker as well. This can be done either by employing a human translator or by using a machine translation system to automatically convert the text from one language to another.

Machine translation is a sub-field of computational linguistics that deals with the problem of translating an input text or speech from one language to another. With the recent advancements in Natural Language Processing (NLP) and Deep Learning, it is now possible for a machine translation system to reach human like performance in translating a text from one language to another.

In this notebook, we will pick a story map written in English language, and create another story map with the text translated to Spanish language using the arcgis.learn.text's TextTranslator class. The TextTranslator class is part of inference-only classes offerered by the arcgis.laern.text submodule. These inference-only classes offer a simple API dedicated to several Natural Language Processing (NLP) tasks including Masked Language Modeling, Text Generation, Sentiment Analysis, Summarization, Machine Translation and Question Answering.


  • Inferencing workflows for Inference-only Text models of arcgis.learn.text submodule is based on Hugging Face Transformers library.
  • Refer to the section Install deep learning dependencies of arcgis.learn module for detailed explanation about deep learning dependencies.
  • Beautiful Soup python library to pull text out from the HTML content of the story map.
  • Choosing a pretrained model: Depending on the task and the language of the input text, user might need to choose an appropriate transformer backbone to generate desired inference. This link lists out all the pretrained models offered by Hugging Face Transformers library that allows translation from a source language to one or more target languages.


In [1]:
from arcgis import GIS
from bs4 import BeautifulSoup
from arcgis.learn.text import TextTranslator

Translate Story Map from English to Spanish

In this notebook we have picked up a story map written in English language, which talks about the near-term interim improvements (for the new bicycle and pedestrian bridge design over Lady Bird Lake) to South Pleasant Valley Road. Our goal will be to create a clone of this story map with the text translated to Spanish language

Connect to GIS and clone Story Map

To achieve our goal, we will first connect to an ArcGIS online account, get the desired content by passing the appropriate item-id and cloning the item into our GIS account. We will then apply the TextTranslator model of arcgis.learn.text submodule to this cloned item to convert the content of the story map to Spanish language.

In [2]:
agol = GIS()

gis = GIS('home')
In [3]:
storymapitem = agol.content.get('c8eef2a96c88489c92010a63d0944881')
South Pleasant Valley Road
(Cesar Chavez Street to Elmont Drive)StoryMap by ATD_Publisher
Last Modified: September 08, 2020
0 comments, 2,332 views
In [4]:
cloned_items = gis.content.clone_items([storymapitem], search_existing_items=False)
[<Item title:"South Pleasant Valley Road" type:StoryMap owner:arcgis_python>]
In [5]:
cloned_item = cloned_items[0]
South Pleasant Valley Road
(Cesar Chavez Street to Elmont Drive)StoryMap by arcgis_python
Last Modified: December 07, 2020
0 comments, 0 views
In [6]:

Instantiate text translator

Next, we will instantiate the class object for the TextTranslator model. We wish to translate text from English language into Spanish language. So will invoke the object by passing the corresponding ISO language codes [1] in the model constructor.

In [7]:
translator = TextTranslator(source_language='en', target_language='es')

We will also write some helper functions to help translate the content of story map into the desired language. The replace function is a recursive [2] function that accepts a json (story map item dictionary) object obj and applies the function func on the values v of the keys list passed in the replace function argument.

In [8]:
def replace(obj, keys, func):
    return {k: replace(func(v) if k in keys else v, keys, func) 
        for k,v in obj.items()} if isinstance(obj, dict) else obj

The translate function will translate the English text (passed in the function argument) into Spanish language. The story map text sometimes contain text wrapped inside HTML [3] tags. We will use BeautifulSoup library to get the non-HTML part of the input text content and use the translator's translate method to translate the non-HTML part of the input text into desired language (Spanish in this case).

In [9]:
def translate(text):
    if text == '': 
        return text
    soup = BeautifulSoup(text, "html.parser") 

    for txt in soup.find_all(text=True):
        translation = translator.translate(txt)[0]['translated_text'] if txt.strip() != '' else txt
        txt.string.replace_with(" " + translation + " ")
    return str(soup)

Translate Story Map content

We will call the story map item's get_data() method to retrieves the data associated with the item.

In [10]:
smdata = storymapitem.get_data()

The call to the above method will return a python dictionary containing the contents of the story map which we wish to translate. We wish to translate not only the text content of the story map but also things like title, summary, captions, etc. To do so we will call the replace function defined above with the desired arguments.

In [11]:
result = replace(smdata, ['text', 'alt', 'title', 'summary', 'byline', 'caption', 'storyLogoAlt'], translate)

Update cloned Story Map item

This cloned story map item doesn't contain the translated version of the story map until this point. But this can be achieved by calling the update() method of the cloned item and passing a dictionary of the item attributes we wish to translate.

In [12]:
cloned_item.update({'url': cloned_item.url.replace(,, 
    'text': result,
    'title': translator.translate(storymapitem['title'])[0]['translated_text'],
    'description': translator.translate(storymapitem['description'])[0]['translated_text'],
    'snippet': translator.translate(storymapitem['snippet'])[0]['translated_text']})
100.00% [1/1 00:00<00:00]
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100.00% [1/1 00:00<00:00]

The cloned story map text is now translated into Spanish language and is ready to be shared.

In [13]:
South Pleasant Valley Road
(Cesar Chavez a Elmont Drive)StoryMap by arcgis_python
Last Modified: December 07, 2020
0 comments, 0 views
In [14]:
{'results': [{'itemId': 'a5af5750f9d143238d72bac224f204fb',
   'success': True,
   'notSharedWith': []}]}


This sample demonstrates how inference only TextTranslator class of arcgis.learn.text submodule can be used to perform machine translation task to translate text from one language to another. We showed, how easy it is to translate a story map which is written in English language into Spanish language. Similar workflow can be followed to automate the task of translating story maps or other ArcGIS items into various languages.


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