Every 15 minutes
Transcribe audio uploaded to S3 into a Google Sheet
Every audio file you upload to your S3 bucket is transcribed, and the file name and transcript are added as a row in your sheet.
- Runs
- Every 15 minutes
- Apps
- AWS, Google Sheets
- AI
- Not needed
- Access
- IAM s3:ListBucket/GetObject, transcribe:*; Sheets write
Send this to your assistant
Create a ClickRuntime automation: every 15 minutes, check my S3 bucket for new audio files, transcribe them with AWS Transcribe, and add the file name and transcript to my Transcripts sheet.
First time? Adding ClickRuntime to your assistant takes about two minutes.
Why use it
Why teams use this automation
A research team records customer interviews and drops the audio in an S3 bucket. Someone is supposed to transcribe them, but it's tedious, so the recordings pile up and the insights stay locked in hours of audio nobody has time to replay.
Transcribing each file as it arrives and putting the text in a sheet makes interviews searchable and quotable the same day, and the team can tag and filter them like any other data.
What you get out of it
Searchable interviews
Text in a sheet can be searched, filtered and quoted, which audio files can't.
No transcription backlog
Each upload is handled within the hour, so recordings never pile up.
Keep your audio in your own account
Files stay in your bucket and are transcribed by your AWS account.
One list of every recording
The sheet doubles as an index of what's been recorded and when.
How it works
What happens, step by step
Every 15 minutes, ClickRuntime looks in your S3 bucket for audio files it hasn't seen.
It asks AWS Transcribe to transcribe each new file.
On later checks, it collects transcripts that have finished.
Each finished transcript is added to your Transcripts sheet with the file name.
It keeps a list of files started and finished, so nothing is transcribed twice.
Before it runs live
- Connect AWS
- Connect your Google Sheets account and pick the spreadsheets it may use
What you get
Build your own
Need it to work differently?
Your own rules
Conditions, thresholds, filters and exceptions, written the way you'd explain them to a colleague.
Any number of apps
One automation can read from one app and update several others. Over 248 apps are ready, and anything with an API works too.
AI where it helps
Summaries, classification, extraction and drafts use ClickRuntime's built-in AI, with no extra key.
On a schedule or on each event
Runs as often as every 5 minutes, or the moment an app sends an event, and keeps track of what it already handled.
Changes you can ask for
- Act only on the items that match your own rules, and skip the rest
- Add an AI step, for example to summarize, sort or draft a reply
- Add another app, for example also send it to Slack
- Combine it with other AWS and Google Sheets steps into one automation
Under the hood
The code that runs this automation
import boto3
from google.oauth2.credentials import Credentials
from googleapiclient.discovery import build
from clickruntime import on_trigger, credentials, http, state, report_fetched
SHEET_ID = "your-spreadsheet-id"
REGION, BUCKET = "us-east-1", "northwind-files"
def aws(service):
return boto3.client(service, region_name=REGION, aws_access_key_id=credentials.secret("AWS_ACCESS_KEY_ID"),
aws_secret_access_key=credentials.secret("AWS_SECRET_ACCESS_KEY"))
@on_trigger
def run(event):
s3, tr = aws("s3"), aws("transcribe")
jobs = state.get("jobs") or {}
keys = [o["Key"] for o in s3.list_objects_v2(Bucket=BUCKET, Prefix="audio/").get("Contents", []) if o["Key"].endswith((".mp3", ".wav", ".m4a"))]
new = [k for k in keys if k not in jobs]
report_fetched(len(new) + sum(1 for v in jobs.values() if v != "done"))
for k in new:
jobs[k] = "cr-" + k.replace("/", "-").rsplit(".", 1)[0][:180]
tr.start_transcription_job(TranscriptionJobName=jobs[k], Media={"MediaFileUri": f"s3://{BUCKET}/{k}"}, IdentifyLanguage=True)
rows = []
for k, name in jobs.items():
if name == "done" or k in new:
continue
job = tr.get_transcription_job(TranscriptionJobName=name)["TranscriptionJob"]
if job["TranscriptionJobStatus"] in ("COMPLETED", "FAILED"):
text = http.get(job["Transcript"]["TranscriptFileUri"]).json()["results"]["transcripts"][0]["transcript"] if job["TranscriptionJobStatus"] == "COMPLETED" else "(failed)"
rows.append([k, job["CompletionTime"].isoformat()[:16], text[:45000]])
jobs[k] = "done"
if rows:
build("sheets", "v4", credentials=Credentials(credentials.connection("google", "work")), cache_discovery=False).spreadsheets().values().append(spreadsheetId=SHEET_ID, range="Transcripts!A:C", valueInputOption="RAW", body={"values": rows}).execute()
state.set("jobs", jobs)
return {"started": len(new), "logged": len(rows)}FAQ
Common questions
Which audio formats work?
How long does a transcript take?
Can it tell speakers apart?
What permissions does it need?
Does it need AI?
How many runs does it use?
Can I change how it works?
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