Do you really need to pay a fortune for your text-to-speech?

The voice AI market has exploded with all the subtlety of a sonic boom.

In January 2024, ElevenLabs achieved unicorn status with an $80 million Series B. Twelve months later, they closed a $180 million Series C at a $3.3 billion valuation.

SoundHound went public at $2.1 billion. Harvey, a voice AI assistant for lawyers, raised $300 million at a $3 billion valuation. The numbers are dizzying and investor enthusiasm palpable.

The message is clear: voice is here and having its moment.

And why shouldn't it? Depending on whose crystal ball you trust, the global text-to-speech market, valued at around $4-5 billion in 2024, is projected to hit anywhere between $28 billion and $54.5 billion by the early 2030s.

Voice AI startups also now represent 22% of recent Y Combinator cohorts.

Even the hyperscalers are betting big – Microsoft, NVIDIA and Meta have all got skin in the game with emerging Voice AI players. It's genuinely impressive stuff.

A sector that went from accessibility afterthought to AI darling in the space of a few years has done so for a reason. The technology works.

Speech-to-text has already transformed how we interact with voice interfaces, making accurate transcription table stakes.

Now neural TTS has made voices that actually sound human, not like your GPS having an existential crisis. The use cases are vast, and especially in voice agents, the opportunity to add business value at scale is exciting.

But, with all that investment comes a wide, and wildly variable, price tag.

The price of sounding human

The going rates for TTS vary considerably, from a few dollars per million characters at the lower end to premium tiers of upwards of $10 per hour of generated audio.

ElevenLabs, the market leader, can cost up to 27 times more than emerging players. 

For that price tag, you get an incredible feature set: voice cloning capabilities, fine-grained emotional controls, the ability to add laughter, sighs, or vocal fry, and exceptionally natural prosody. 

The hyperscalers – Google, Microsoft, Amazon, sit somewhere in the middle, offering broad language coverage and a range of voice models at more moderate pricing.

Then there's a growing cohort of newer entrants positioning themselves as disruptors: less fancy, but clear, natural speech without the premium attached.

In summary:

• Ultra-premium providers: advanced emotional control, voice cloning, high per-minute costs

• Hyperscalers: broad language support, moderate pricing, general-purpose voices

• Production-focused providers: fewer theatrics, clear speech, predictable pricing at scale

So you've got options spanning from budget-friendly to eye-wateringly expensive.

The question is whether your use case actually demands the premium end of that spectrum.

The truthful answer

It depends on what you're building.

For broadcast media, dubbing a ten-hour TV series or a major podcast where emotional range genuinely matters to engage the viewer, paying out the premium tier makes sense. The volume is small and the quality needs to be the best. When your synthetic voice needs to convey genuine emotion, you're shopping at the high end for good reason.

But most enterprises aren't making prestige television.

They're building voice agents for customer support, creating educational content, automating outbound sales calls, or adding voice capabilities to their apps. And for these use cases, the requirements are fundamentally different.

Take contact centers: you don't want your support assistant to laugh at customers. You definitely don't want it to sound angry. You need clarity, proper pronunciation and engagement without a huge range of emotion. The voice should be professional, natural enough not to grate, and reliable enough not to mangle technical terms. That's a very different specification from what commands premium pricing.

And then there's the scale problem.

Paying premium rates for thousands of customer interactions daily makes your voice agent economically unviable before it even launches.

For the vast majority of enterprise use cases, you need good quality, not theatrical quality. Voices that work at scale, both technically and financially.

Why we built ours

At Speechmatics, we spend considerable time talking to our customers, many of them scaling globally and dealing with thousands of daily interactions.

A pattern emerged: they were looking for TTS that was fast, reliable, clear, and crucially, cost-effective at volume.

So we built ours.

Speech to Text

Voice AI agents

Text to Speech

Sarah •friendly support

Theo •trusted presenter

Jack •support specialist

Megan •clear companion

Play

Clear

Not because the market lacks options (clearly!) but because there's a gap between ultra-premium emotional AI voices and what most businesses actually require for production environments.

We focused on low latency because real-time conversations can't have awkward pauses while the AI generates speech.

We prioritized pronunciation accuracy because mispronouncing customer names or technical terms in a support call is a good way to lose trust.

We made it accessible because pricing shouldn't be the barrier to deploying voice technology that genuinely improves customer experience.

The broader point

The voice AI boom is real and justified.

The technology has reached a threshold where it's genuinely useful rather than a novelty.

Companies are right to invest heavily in the space, and the growth projections, while potentially optimistic, aren't pure fantasy.

Yet there's a difference between what's technically impressive and what's commercially necessary.

Not every voice application needs to sound like Olivia Coleman winning an Oscar. Sometimes you just need clear, natural speech that doesn't bankrupt you when you scale.

The question isn't whether TTS is worth investing in. It demonstrably is. The question is what level of investment your specific use case actually requires.

If you're building an AI companion that needs genuine emotional resonance or producing premium content, pay for the premium tier.

For voice agents handling customer queries, appointment bookings, or accessible content at scale? You need something that works well at a price point that makes sense for thousands or millions of interactions.

The voice AI market's explosive growth is brilliant for innovation.

It shouldn't, however, create the assumption that more expensive automatically equals better for your needs. Sometimes the best solution is the one that solves your actual problem efficiently, rather than the one with the most eye-watering valuation.

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