> ## Documentation Index
> Fetch the complete documentation index at: https://assemblyai.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Translate AssemblyAI Transcripts Into Other Languages Using Commercial Models

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](https://cloud.google.com/translate/docs/languages), [DeepL](https://www.deepl.com/docs-api/translate-text), and [python-translate](https://github.com/terryyin/translate-python) 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](https://www.assemblyai.com/dashboard/signup).

```python theme={null}
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.

```bash theme={null}
pip install "assemblyai"
```

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

```python theme={null}
import assemblyai as aai

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

```python theme={null}
config = aai.TranscriptionConfig(language_detection=True)
transcriber = aai.Transcriber(config=config)

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

Specify the target language for the translation

```python theme={null}
to_lang = 'en'
```

Get detected language code from the AAI JSON response

```python theme={null}
from_lang = transcript.json_response['language_code']
```

# Commercial Models

## Google Translate API

[https://cloud.google.com/translate/docs/reference/libraries/v2/python](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.

```bash theme={null}
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](https://cloud.google.com/docs/authentication/application-default-credentials)

```python theme={null}
import os
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = './translate_creds.json'
```

```python expandable theme={null}
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](https://www.deepl.com/en/docs-api)

```bash theme={null}
pip install deepl
```

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

```python theme={null}
DEEPL_API_TOKEN = ''
```

```python theme={null}
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](https://github.com/terryyin/translate-python)

```bash theme={null}
pip install translate
```

```python theme={null}
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()
```