This Cookbook walks through how to translate AssemblyAI transcripts using a variety of commerical and open-source machine translation models. Choosing a model depends on your use-case and preferences. Here are some considerations you may want to make when choosing a model to use for translation:

Accuracy and Quality of Translation: you should compare the translations from each provider to see which translation you prefer
Language Support: check the supported languages for Google Translate, DeepL, and python-translate respectively
Cost: while commercial models usually have a free-tier or trials, they will incur costs eventually

Setup

To get started, paste your API token into the empty string below. If you don’t already have an API token, you can get one for free here.

AAI_API_TOKEN = ""

Make sure not to share this token with anyone - it is a private key associated uniquely to your account. Next, we’ll install the AssemblyAI Python SDK.

pip install "assemblyai"

Finally, import the assemblyai package and set your API token in the settings:

import assemblyai as aai

# set the API key
aai.settings.api_key = f"{AAI_API_TOKEN}"

config = aai.TranscriptionConfig(language_detection=True, speech_models=["universal-3-pro", "universal-2"])
transcriber = aai.Transcriber(config=config)

transcript = transcriber.transcribe('./my-audio.mp3')

Specify the target language for the translation

to_lang = 'en'

Get detected language code from the AAI JSON response

from_lang = transcript.json_response['language_code']

Commercial Models

Google Translate API

https://cloud.google.com/translate/docs/reference/libraries/v2/python Note: you will need a GCP account as well as app credentials to make this API request.

pip install google-cloud-translate==2.0.1

Follow Google’s docs on how to generate a credentials JSON file: https://cloud.google.com/docs/authentication/application-default-credentials

import os
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = './translate_creds.json'

from google.cloud import translate_v2

def translate(target: str, text: str) -> dict:
    """Translates text into the target language.

    Target must be an ISO 639-1 language code.
    See https://g.co/cloud/translate/v2/translate-reference#supported_languages
    """
    from google.cloud import translate_v2 as translate

    translate_client = translate.Client()

    if isinstance(text, bytes):
        text = text.decode("utf-8")

    # Text can also be a sequence of strings, in which case this method
    # will return a sequence of results for each text.
    result = translate_client.translate(text, target_language=target)

    print("Text: {}".format(result["input"]))
    print("Translation: {}".format(result["translatedText"]))
    print()

    return result

for sent in transcript.get_sentences():
  translate(to_lang, sent.text)

DeepL API

https://www.deepl.com/en/docs-api

pip install deepl

You will need a DeepL account and API token, which can be found here: https://www.deepl.com/pro-api

DEEPL_API_TOKEN = ''

import deepl

def translate(text):
    translator = deepl.Translator(DEEPL_API_TOKEN)
    result = translator.translate_text(text, target_lang="EN-US") # Note: DeepL requires more formal language code
    return result.text

# Example usage
for sent in transcript.get_sentences():
  translated_text = translate(sent.text)
  print("Text: {}".format(sent.text))
  print("Translation: {}".format(translated_text))
  print()

Open-Source Models

`translate-python` Library

https://github.com/terryyin/translate-python

pip install translate

from translate import Translator

def translate(text):
    translator = Translator(to_lang=to_lang, from_lang=from_lang)
    translation = translator.translate(text)
    return translation

for sent in transcript.get_sentences():
  translated_text = translate(sent.text)
  print("Text: {}".format(sent.text))
  print("Translation: {}".format(translated_text))
  print()

​Setup

​Commercial Models

​Google Translate API

​DeepL API

​Open-Source Models