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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:
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-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:
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-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-pro", "universal-2"] for the highest accuracy
We have a cookbook for error handling common errors when using our API.
Installation 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 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 # 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:
Adding Features 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-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
