Migration guide: Deepgram to AssemblyAI

This guide walks through the process of migrating from Deepgram to AssemblyAI for transcribing pre-recorded audio.

Get Started

Before we begin, make sure you have an AssemblyAI account and an API key. You can sign up for a free account and get your API key from your dashboard.

Side-By-Side Code Comparison

Below is a side-by-side comparison of a basic snippet to transcribe a local file by Deepgram and AssemblyAI:

Deepgram
AssemblyAI

from deepgram import (
     DeepgramClient,
     PrerecordedOptions,
     FileSource,
)

API_KEY = "YOUR_DG_API_KEY"

AUDIO_FILE = "./example.wav"

def main():
    try:
        deepgram = DeepgramClient(API_KEY)

        with open(AUDIO_FILE, "rb") as file:
            buffer_data = file.read()

            payload: FileSource = {
                "buffer": buffer_data,
            }

            options = PrerecordedOptions(
                model="nova-2",
                smart_format=True,
                diarize=True
            )

            response = deepgram.listen.prerecorded.v("1").transcribe_file(payload, options)

            print(response.to_json(indent=4))

    except Exception as e:
        print(f"Exception: {e}")

if name == "main":
    main()

import assemblyai as aai

aai.settings.api_key = "YOUR-API-KEY"
transcriber = aai.Transcriber()

audio_file = "./example.wav"

config = aai.TranscriptionConfig(
    speech_models=["universal-3-5-pro", "universal-2"],
    language_detection=True,
    speaker_labels=True,
)
transcript = transcriber.transcribe(audio_file, config)

if transcript.status == aai.TranscriptStatus.error:
    print(f"Transcription failed: {transcript.error}")
    exit(1)

print(transcript.text)

for utterance in transcript.utterances:
    print(f"Speaker {utterance.speaker}: {utterance.text}")

Below is a side-by-side comparison of a basic snippet to transcribe a publicly-accessible URL by Deepgram and AssemblyAI:

Deepgram
AssemblyAI

from deepgram import (
    DeepgramClient,
    PrerecordedOptions
)

API_KEY = "YOUR_DG_API_KEY"

AUDIO_URL = {
    "url": "https://dpgr.am/spacewalk.wav"
}

def main():
    try:
        deepgram = DeepgramClient(API_KEY)

        options = PrerecordedOptions(
            model="nova-2",
            smart_format=True,
            diarize=True
        )

        response = deepgram.listen.prerecorded.v("1").transcribe_url(AUDIO_URL, options)

        print(response.to_json(indent=4))

    except Exception as e:
        print(f"Exception: {e}")

if name == "main":
    main()

import assemblyai as aai

aai.settings.api_key = "YOUR-API-KEY"
transcriber = aai.Transcriber()

audio_file = (
    "https://assembly.ai/sports_injuries.mp3"
)

config = aai.TranscriptionConfig(
    speech_models=["universal-3-5-pro", "universal-2"],
    language_detection=True,
    speaker_labels=True,
)
transcript = transcriber.transcribe(audio_file, config)

if transcript.status == aai.TranscriptStatus.error:
    print(f"Transcription failed: {transcript.error}")
    exit(1)

print(transcript.text)

for utterance in transcript.utterances:
    print(f"Speaker {utterance.speaker}: {utterance.text}")

Here are helpful things to know about our transcribe method:

The SDK handles polling under the hood
Transcript is directly accessible via transcript.text
English is the default language. We recommend specifying speech_models=["universal-3-5-pro", "universal-2"] for the highest accuracy
We have a cookbook for error handling common errors when using our API.

Installation

Deepgram
AssemblyAI

from deepgram import (
    DeepgramClient,
    PrerecordedOptions,
    FileSource,
)

API_KEY = "YOUR_DG_API_KEY"
deepgram = DeepgramClient(API_KEY)

import assemblyai as aai

aai.settings.api_key = "YOUR-API-KEY"
transcriber = aai.Transcriber()

When migrating from Deepgram to AssemblyAI, you’ll first need to handle authentication and SDK setup: Get your API key from your AssemblyAI dashboard
To follow this guide, install AssemblyAI’s Python SDK by typing this code into your terminal:
pip install assemblyai Things to know:

Store your API key securely in an environment variable
API key authentication works the same across all AssemblyAI SDKs

Audio File Sources

Deepgram
AssemblyAI

# Local Files
AUDIO_FILE = "example.wav"
with open(AUDIO_FILE, "rb") as file:
    buffer_data = file.read()

payload: FileSource = {
    "buffer": buffer_data,
}

options = PrerecordedOptions(
    smart_format=True,
    summarize="v2",
)

file_response = deepgram.listen.rest.v("1").transcribe_file(payload, options)

json = file_response.to_json()

#Public URLs
AUDIO_URL = {
    "url": "https://static.deepgram.com/examples/Bueller-Life-moves-pretty-fast.wav"
}

options = PrerecordedOptions(
    smart_format=True,
    summarize="v2"
)

url_response = deepgram.listen.rest.v("1").transcribe_url(AUDIO_URL, options)

json = url_response.to_json()

transcriber = aai.Transcriber()

# Local Files
transcript = transcriber.transcribe("./audio.mp3")

# Public URLs
transcript = transcriber.transcribe("https://example.com/audio.mp3")

# S3 files (using pre-signed URLs)
s3_client = boto3.client('s3')
presigned_url = s3_client.generate_presigned_url(
    'get_object',
    Params={'Bucket': 'my-bucket', 'Key': 'audio.mp3'},
    ExpiresIn=3600
)

transcript = transcriber.transcribe(presigned_url)

Here are helpful things to know when migrating your audio input handling:

There’s no need to specify the audio format to AssemblyAI - it’s auto-detected. AssemblyAI accepts almost every audio/video file type: here is a full list of all our supported file types
Our SDK handles file upload and transcription automatically in one step
For S3 files, you’ll need to generate pre-signed URLs (see example in cookbook)

Adding Features

Deepgram
AssemblyAI

options = PrerecordedOptions(
   model="nova-2",
   smart_format=True,
   diarize=True,
   detect_entities=True
)

response = deepgram.listen.prerecorded.v("1").transcribe_url(AUDIO_URL, options)

config = aai.TranscriptionConfig(
    speech_models=["universal-3-5-pro", "universal-2"],
    language_detection=True,
    speaker_labels=True, # Speaker diarization
    auto_chapters=True, # Auto chapter detection
    entity_detection=True, # Named entity detection
)

transcript = transcriber.transcribe(audio_url, config)

# Access speaker labels
for utterance in transcript.utterances:
    print(f"Speaker {utterance.speaker}: {utterance.text}")

Key differences:

Use aai.TranscriptionConfig to specify any extra features that you wish to use
The results for Speaker Diarization are stored in transcript.utterances. To see the full transcript response object, refer to our API Reference.
Check our documentation for our full list of available features and their parameters

​Get Started

​Side-By-Side Code Comparison

​Installation

​Audio File Sources

​Adding Features

Get Started

Side-By-Side Code Comparison

Installation

Audio File Sources

Adding Features