Amazon Transcribe charges $0.024 per minute for standard speech-to-text, while Amazon Polly costs $16.00 per million characters for its Neural engine. If you are processing 5,000 hours of audio a month, Transcribe will bill you roughly $7,200. The exact same workload on OpenAI’s Whisper API ($0.006/min) would cost $1,800. That is a 4x premium for staying within the AWS walled garden.
These two services function like a massive industrial utility grid: they are everywhere, they are reliable, and they connect seamlessly to your existing infrastructure, but they lack the nuance and "wow" factor of specialized boutique providers.
For speech-to-text, Transcribe is a workhorse. It shines in compliance-heavy industries. Features like PII redaction (masking social security numbers or names automatically) and custom vocabulary filters are enterprise-ready features that open-source models often lack out of the box. However, its raw accuracy (WER) on accented or noisy audio consistently lags behind OpenAI’s Whisper v3.
On the text-to-speech side, Polly has been the standard for years. The "Neural" voices are clear and legible but lack emotional depth—they sound like very polite robots. AWS recently launched a "Generative" engine ($30 per million characters) to compete with ElevenLabs. It is a significant improvement in natural phrasing, but it still falls short of the hyper-realistic, emotive performance ElevenLabs offers.
The real value here isn't the model performance; it's the plumbing. If you use Transcribe, you can drop an MP3 into an S3 bucket, trigger a Lambda function to transcribe it, and push the text to DynamoDB without writing a single line of API integration code or managing a server. You get unified billing, IAM security roles, and SOC2 compliance for free.
Skip this pair if you are a startup building a B2C app where voice quality is your differentiator—Whisper and ElevenLabs are simply better and, in Whisper's case, much cheaper. Use AWS if you are an enterprise moving terabytes of sensitive data where infrastructure reliability and compliance trumps raw model performance.
Pricing
The Free Tier is a 12-month trial, not a permanent allowance. You get 60 minutes/month of Transcribe and 5M characters/month of Polly (Standard) or 1M (Neural).
The hidden cost is the "Generative" engine in Polly, which jumps to $30/1M characters—nearly double the Neural price.
For Transcribe, the price gap is severe. At $0.024/min, it is 400% more expensive than OpenAI Whisper ($0.006/min) and ~600% more than Deepgram Nova-2. AWS offers volume discounts, but they only kick in at massive scale (250k+ minutes/month). If you don't need the AWS ecosystem integration, you are overpaying significantly for transcription.
Technical Verdict
Integration is handled via boto3, the standard AWS SDK. It is robust but verbose. Documentation is exhaustive but often fragmented across different API versions. Latency for real-time streaming is acceptable (hundreds of ms) but not class-leading. The primary friction isn't code—it's configuration: setting up IAM roles, S3 bucket policies, and region-specific endpoints usually takes longer than writing the actual script.
Quick Start
import boto3
import time
# pip install boto3
polly = boto3.client('polly', region_name='us-east-1')
response = polly.synthesize_speech(
Text='System status normal.',
OutputFormat='mp3',
VoiceId='Joanna'
)
with open('status.mp3', 'wb') as f:
f.write(response['AudioStream'].read())Watch Out
- Transcribe bills a minimum of 15 seconds per request, so processing short command clips can be artificially expensive.
- Polly's new 'Generative' voices are only available in specific regions (e.g., us-east-1, eu-central-1).
- Custom vocabularies in Transcribe take time to propagate and don't guarantee fixes for all homophones.
- Real-time streaming in Transcribe requires HTTP/2, which can be tricky to implement if not using the official SDK.