What's the Difference Between Amazon Polly and Amazon Transcribe?

Compare Amazon Polly and Amazon Transcribe side by side — features, pricing, and ideal use cases to help you choose the right product.

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Compare side-by-side

Comparisons	Amazon Polly	Amazon Transcribe
Category	Machine Learning, Speech AI	Machine Learning, Speech AI
Description	Turn text into lifelike speech using deep learning for natural-sounding voices.	Automatic speech recognition service that converts audio to text.
Best for	Text-to-speech Accessibility E-learning Telephony Content creation	Call center analytics Subtitling Meeting transcription Medical transcription Content indexing
Key features	Neural voices SSML support Multiple languages Real-time streaming Speech marks	Real-time transcription Custom vocabulary Speaker identification Channel identification Toxicity detection
Pricing model	Pay per character converted to speech	Pay per second of audio transcribed
Free tier	Yes	Yes
Expert take	“Polly Neural voices are nearly indistinguishable from human speech. Use SSML tags to control pacing, emphasis, and pronunciation. For batch content production, Polly outputs audio files; for real-time use cases like IVR, it streams directly.” — Oleksii Bebych, re:Post Top Contributor [profile]	“Custom vocabulary and custom language models are the two levers for improving accuracy on domain-specific terminology. For real-time use cases like live captioning, streaming transcription delivers partial results with low latency while speaker diarization separates overlapping voices.” — Didier Durand, re:Post Top Contributor [profile]
Product page	Learn more about Amazon Polly »	Learn more about Amazon Transcribe »

When to use Amazon Polly or Amazon Transcribe

Use Amazon Polly when:

Text-to-speech
Accessibility
E-learning
Telephony
Content creation

Learn more about Amazon Polly »

Use Amazon Transcribe when:

Call center analytics
Subtitling
Meeting transcription
Medical transcription
Content indexing

Learn more about Amazon Transcribe »

Next steps with AWS for Machine Learning

Create a free account

Start building with Amazon Polly and Amazon Transcribe on the AWS Free Tier.

Get started with Amazon Polly

Turn text into lifelike speech using deep learning for natural-sounding voices.

Go to Amazon Polly

Get started with Amazon Transcribe

Automatic speech recognition service that converts audio to text.

Go to Amazon Transcribe

AWS product comparisons

What's the difference between Amazon Aurora and Amazon RDS?

Both are fully managed relational database services on AWS, but Aurora is a cloud-native engine built for higher performance and availability, while RDS gives you familiar open-source and commercial engines with less operational overhead than self-managed.

What's the difference between Amazon DynamoDB and Amazon RDS?

DynamoDB is a serverless NoSQL database for applications with well-defined access patterns that need consistent single-digit millisecond performance. RDS is a managed relational database for applications that need SQL, joins, and transactional integrity across multiple engines.

What's the difference between Amazon DynamoDB and Amazon Keyspaces?

Both are fully managed, serverless-capable NoSQL databases on AWS. DynamoDB is AWS-native with its own API and data model; Keyspaces is Apache Cassandra-compatible, letting you use existing Cassandra drivers, tools, and expertise.

What are the differences between Amazon DynamoDB and Amazon DocumentDB?

Both are fully managed NoSQL databases on AWS, but they serve different data models. DynamoDB is a key-value store optimized for known access patterns at massive scale; DocumentDB is a document database for flexible JSON schemas with MongoDB compatibility.

What's the difference between Amazon DocumentDB and Amazon Neptune?

Both handle semi-structured data, but they're optimized for different query patterns. DocumentDB stores and queries JSON documents; Neptune stores and traverses relationships between entities.

What's the difference between Amazon Aurora and Amazon RDS?

Both are fully managed relational database services on AWS, but Aurora is a cloud-native engine built for higher performance and availability, while RDS gives you familiar open-source and commercial engines with less operational overhead than self-managed.

What's the difference between Amazon Aurora and Amazon Neptune?

Both are purpose-built, fully managed AWS databases, but they solve fundamentally different problems. Aurora handles structured relational data with SQL; Neptune handles highly connected data where relationships between entities are the primary query pattern.

What's the difference between Amazon Aurora and Amazon DynamoDB?

Both are fully managed AWS database services, but they serve fundamentally different data models and access patterns. Aurora is a relational database for structured data with relationships; DynamoDB is a NoSQL key-value store built for single-digit millisecond performance at any scale.

What's the difference between Amazon RDS and Amazon Redshift?

Both run SQL queries, but they're optimized for fundamentally different workloads. RDS handles transactional operations (inserts, updates, lookups) for your application. Redshift handles analytical queries (aggregations, scans, joins across billions of rows) for your data team.

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