> ## 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.
# Migration guide: AWS Transcribe to AssemblyAI
This guide walks through the process of migrating from AWS Transcribe 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](https://assemblyai.com/dashboard/signup) 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 file by AWS Transcribe and AssemblyAI:
```python expandable theme={null}
import time
import boto3
def transcribe_file(job_name, file_uri, transcribe_client):
transcribe_client.start_transcription_job(
TranscriptionJobName=job_name,
Media={"MediaFileUri": file_uri},
MediaFormat="wav",
LanguageCode="en-US",
)
max_tries = 60
while max_tries > 0:
max_tries -= 1
job = transcribe_client.get_transcription_job(
TranscriptionJobName=job_name
)
job_status = job["TranscriptionJob"]["TranscriptionJobStatus"]
if job_status in ["COMPLETED", "FAILED"]:
print(f"Job {job_name} is {job_status}.")
if job_status == "COMPLETED":
print(
f"Download the transcript from\n"
f"\t{job['TranscriptionJob']['Transcript']['TranscriptFileUri']}."
)
break
else:
print(f"Waiting for {job_name}. Current status is {job_status}.")
time.sleep(10)
def main():
transcribe_client = boto3.client("transcribe")
file_uri = "s3://test-transcribe/answer2.wav"
transcribe_file("Example-job", file_uri, transcribe_client)
if name == "main":
main()
```
```python expandable theme={null}
import assemblyai as aai
aai.settings.api_key = "YOUR-API-KEY"
transcriber = aai.Transcriber()
# You can use a local filepath:
# audio_file = "./example.mp3"
# Or use a publicly-accessible URL:
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}")
```
## Installation
```python theme={null}
import boto3
import time
transcribe_client = boto3.client("transcribe")
```
```python theme={null}
import assemblyai as aai
aai.settings.api_key = "YOUR-API-KEY"
transcriber = aai.Transcriber()
```
When migrating from AWS to AssemblyAI, you'll first need to handle authentication and SDK setup:
Get your API key from your [AssemblyAI dashboard](https://www.assemblyai.com/dashboard/home)
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
```python theme={null}
def transcribe_file(job_name, file_uri, transcribe_client):
transcribe_client.start_transcription_job(
TranscriptionJobName=job_name,
Media={"MediaFileUri": file_uri},
MediaFormat="wav",
LanguageCode="en-US",
)
```
```python theme={null}
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](/faq/what-audio-and-video-file-types-are-supported-by-your-api)
* 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](/pre-recorded-audio/guides/transcribe_from_s3))
## Basic Transcription
```python theme={null}
while max_tries > 0:
max_tries -= 1
job = transcribe_client.get_transcription_job(
TranscriptionJobName=job_name
)
job_status = job["TranscriptionJob"]["TranscriptionJobStatus"]
if job_status in ["COMPLETED", "FAILED"]:
break
time.sleep(10)
```
```python theme={null}
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 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](/pre-recorded-audio/guides/common_errors_and_solutions) when using our API.
## Adding Features
```python theme={null}
transcribe_client.start_transcription_job(
TranscriptionJobName=job_name,
Media={"MediaFileUri": file_uri},
Settings={
"ShowSpeakerLabels": True,
"MaxSpeakerLabels": 2
}
)
```
```python theme={null}
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_file, 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](/api-reference).
* Check our [documentation](/speech-understanding/getting-started) for our full list of available features and their parameters