Amazon Polly Alternatives (2026): 9 Text-to-Speech APIs

Amazon Polly sits inside AWS, so leaving is as much an architecture decision as a voice decision. You're choosing between speech from the same kind of cloud account that runs the rest of your stack, and speech from a specialist vendor whose whole business is voice.

The nine alternatives below are in no particular order, grouped by approach: speech services from large cloud platforms, developer voice APIs built for apps and agents, and voiceover tools with a studio or script upload.

Same cloud account or a specialist voice vendor?

Staying with a large cloud platform keeps billing, security reviews, access control and logging in one familiar place. A specialist vendor usually moves faster on voice quality and conversation features, but it adds another supplier, another set of keys and another service to monitor.

Neither is wrong. Product teams shipping a voice agent often care most about how quickly the first audio arrives. Teams producing training videos care more about how a voice sounds over ten minutes. Work out which of those you are before you compare voices.

Read the lifecycle notes before you build

Voice products change fast, and two current notices show why it pays to check before you write code. OpenAI's own documentation says its older text-to-speech models are due to shut down in the first week of 2027. LMNT's website now says its speech generation journey has come to an end.

Neither appears in the list below, but the lesson applies to every vendor on it. Before you commit, look for a deprecations page, a model lifecycle policy or a changelog, and ask how much notice you'd get before a voice or model is retired.

Nine speech services side by side

Tool	Kind of service	Good for
Azure Speech	Cloud speech service	Speech in apps and voice agents
Deepgram	Text-to-speech API for voice agents	Streaming audio with flexible deployment
Fish Audio	Text-to-speech and voice cloning	Expressive narration for video and ads
IBM Text to Speech	Cloud speech API	Many languages and voices from one API
Murf AI	Text-to-speech API	Low-latency speech for voice applications
Narakeet	Script-to-voiceover tool	Turning scripts into narrated audio or video
Rime	Conversational voice models	Voices for spoken conversation
Unreal Speech	Text-to-speech API	Word timestamps and long audio
WellSaid	AI voiceover generator	Voices modelled on licensed voice actors

Speech from the big cloud platforms

Azure Speech is Microsoft's speech service for building speech-enabled apps and voice agents, with prebuilt speech models. IBM Text to Speech is an API cloud service that converts written text into natural-sounding audio in a range of languages and voices. Both make most sense if you already run on that provider.

Voice APIs built for developers and agents

Deepgram's text-to-speech API is built for voice agents, with streaming audio, and the vendor says it deploys on cloud, VPC or on-premises, wherever your data lives. Murf AI offers a text-to-speech API for voice applications and claims it's the consistently fastest and most efficient one for voice agents; test that against your own latency target.

Rime builds voice models for conversation, with enterprise deployment options. Unreal Speech offers streaming audio, per-word timestamps and long-audio requests, and the timestamps are handy if you're syncing captions or highlighting words as they're spoken. My guide to text-to-speech APIs covers more developer options.

Voiceover tools with a studio or script upload

If your output is narration rather than live conversation, a voiceover tool may suit you better than a raw API. WellSaid says it's built with real voice actors, with voices modelled on licensed performers. Fish Audio offers text-to-speech and voice cloning for narration in videos and advertising. Narakeet turns typed or uploaded scripts into voiceovers and narrated videos.

Cloning a voice raises consent and rights questions, and the rules vary by country, so check what your regulator and the voice owner allow before you clone anyone. For more studio-style tools, see my roundup of text-to-speech software.

The speech services, A to Z

Azure Speech

Best for: Teams on Microsoft Azure building speech-enabled apps and voice agents from prebuilt speech models in the same cloud as the rest of their stack.

Deepgram

Best for: Developers building voice agents who need streaming audio and the option to deploy on cloud, VPC or on-premises, wherever their data lives.

Fish Audio

Best for: Creators producing narration for videos and advertising who want text-to-speech with voice cloning and, by the vendor's account, emotionally controllable delivery.

IBM Text to Speech

Best for: Builders wanting a cloud API that turns written text into natural-sounding audio across a range of languages and voices.

Murf AI

Best for: Product teams building voice applications and agents, from a vendor that says its API is the consistently fastest and most efficient for voice agents.

Narakeet

Best for: People who want to type or upload a script, pick a voice and get back voiceover audio or a narrated video.

Rime

Best for: Conversational products needing voice models designed for human conversation, with enterprise deployment options.

Unreal Speech

Best for: Apps that need streaming audio, per-word timestamps and support for long-audio requests from a text-to-speech API.

WellSaid

Best for: Voiceover producers who want AI voices modelled on licensed voice actors, which the vendor presents as its defining difference.

My advice for product teams

Decide what failure looks like before you choose. For a voice agent, it's a pause long enough that the caller talks over the reply. For a training course, it's a mispronounced product name in every module. For an app read-aloud feature, it's a voice that sounds fine for a sentence and tiring for a page. Test against the failure that would hurt you, not against a vendor's demo sentence.

Keep your code swappable, too. Put speech behind one small internal interface so that changing vendor later means changing one module, not every screen. Given how quickly models are retired, you'll probably be glad of it.

One script, every shortlisted voice

1. Write a short script that includes your product names, a list of customer or place names, numbers, dates and an abbreviation or two.
2. Run it through each shortlisted service in every language you need to support.
3. For live use, measure how long the first audio takes to arrive on a normal connection.
4. Play the results to people who haven't heard them before and ask which they'd listen to for ten minutes.
5. Check each vendor's lifecycle or deprecation notes for the voices you've picked.

You'll have a shortlist of one or two in an afternoon, and real audio to show whoever signs off.

Do you make text-to-speech or voice software? Tool makers can ask to be considered for a featured place on this list.

Want your tool on this list? Featured spots and reviews here are paid partnerships. Here's how to partner with me.

Frequently asked questions

Should I stay with my cloud provider's speech service?

If the rest of your stack is there and the voices meet your needs, staying keeps billing, security and logging simple. Move to a specialist if you need faster conversation, more expressive voices or features your provider doesn't offer.

What matters most for a voice agent?

How quickly the first audio arrives, how natural the voice sounds mid-conversation and how well it handles names and numbers. Test all three with your own script.

Is voice cloning allowed?

It depends on consent and where you operate. Rules vary by country, so check with your regulator and get the voice owner's written permission before cloning any voice.

How do I protect myself if a voice model is retired?

Read each vendor's lifecycle notes, keep speech behind one internal interface in your code and keep a second vendor tested and ready.

What are per-word timestamps used for?

They tell you when each word is spoken, which helps you sync captions, highlight text as it's read or cut audio cleanly.

Are these speech services ranked?

No. They're in no particular order and grouped by approach: cloud platforms, developer APIs and voiceover tools.