Unreal Speech vs IBM Watson

The best way to compare Unreal Speech vs IBM Watson: audio samples, latency, features, plans, pricing, and more.

Unreal Speech

IBM Watson
Voice Quality
Unreal Speech Samples
IBM Watson Samples
Mean Opinion Score (MOS) is a numerical measure that represents the perceived quality of audio samples, commonly used in evaluating text-to-speech systems. The score ranges from 1 to 5, with 1 indicating poor quality and 5 signifying excellent quality. These scores are derivedfrom comprehensive, professionally-conducted evaluations, and are anonymized to ensure unbiased results.
Features
Unreal Speech Features












IBM Watson Features












Features - Conclusion
- Unreal Speech: Delivers a powerhouse of detailed voice customization, featuring tools like per-word timestamps and pitch control. However, it doesn't support voice cloning or offer multilingual capabilities, making it ideal for projects requiring precise audio adjustments but not language variety.
- IBM Watson: Serves a global audience with its robust voice cloning and multilingual capabilities. It's equipped with essential tools such as pitch and speed control, making it a versatile choice for projects that demand a wide range of voices and languages.
- Both platforms offer strong foundational text-to-speech functionalities, each aligning well with different user needs and application scenarios, from detailed sound engineering with Unreal Speech to diverse language offerings with IBM Watson.
Pricing & Plans
Unreal Speech Pricing
Free
$0/mo
- 250,000 characters
Basic
$49/mo
- 3M characters
- Extra: $16 per 1M chars
Plus
$499/mo
- 42M characters
- Extra: $12 per 1M chars
Pro
$1499/mo
- 150M characters
- Extra: $10 per 1M chars
Enterprise
$4999/mo
- 625M characters
- Extra: $8 per 1M chars
IBM Watson Pricing
Free
$0/mo
- 10,000 characters
Standard
$20/mo
- 1M characters
Pricing & Plans - Conclusion
- Unreal Speech Free Tier: Offers 25 times more characters than IBM Watson, providing significant value for users starting or experimenting without a cost barrier.
- Cost-Effectiveness at Various Levels: Across different usage tiers, Unreal Speech generally offers more cost-effective solutions compared to IBM Watson. It becomes particularly economical for higher volumes, including bulk and enterprise scenarios.
- High Volume Pricing Advantage: Unreal Speech's higher tier plans significantly undercut IBM Watson's cost per million characters, making it the preferred choice for heavy users.
Customer Reviews
Unreal Speech Reviews
Customers appreciate Unreal Speech's Text-to-Speech API for its affordability, ease of setup, and generous free tier. They find the API to be a cost-effective solution compared to competitors, with clear documentation and responsive customer support. The API is praised for its natural-sounding voices and seamless integration into various projects. However, customers express a desire for more voice customization options, support for multiple languages and improvements in voice realism.
IBM Watson Reviews
Compare Alternatives
Unreal Speech Alternatives
IBM Watson Alternatives
Summary
- Cost-Effectiveness of Unreal Speech: Offers a generous free tier and a lower cost per million characters for high-volume users, making it more budget-friendly compared to IBM Watson.
- Feature Limitations of Unreal Speech: Lacks advanced features like voice cloning and multilingual support, which are available with IBM Watson, making IBM Watson a preferred choice for global applications and users requiring diverse language options.
- Common Features: Both services provide essential text-to-speech functionalities such as pitch and speed control, addressing a variety of user needs.
- Conclusion: While Unreal Speech excels in affordability for high-volume users, IBM Watson’s capabilities in voice cloning and multilingual support make it ideal for projects demanding a global reach and language versatility.
TTS Property
Our next-gen TTS model surpasses competitors on performance at one-tenth the cost. Enjoy low latency websocket support and mult-speaker voice generation at pricing that helps you scale.
TTS Property
Our next-gen TTS model surpasses competitors on performance at onespeaker voice generation at pricing that helps you scale.Our next-gen TTS model surpasses competitors on performance at one-tenth the cost. Enjoyspeaker voice generation at pricing that helps you scale.Our next-gen TTS model surpasses competitors on performance at one-tenth the cost. Enjoyspeaker voice generation at pricing that helps you scale.Our next-gen TTS model surpasses competitors on performance at one-tenth the cost. Enjoy
Signal Noise Ratio
Signal Noise Ratio
Signal Noise Ratio
Do you offer any free credits for TTS & ASR?
We offer a generous free plan for developers with one month of free:
- 160 hours of text-to-speech generation
- 1.2 million characters of speech-to-text transcription
What is the monthly subscription?
Our monthly plan is $20 per month for
- 160 hours of text-to-speech generation
- 1.2 million characters of Speech-to-Text transcription
Once you exceed those limits, you can add $5 top-ups to your plan for
- additional 30hrs of Text-to-Speech
- additional 300,000 characters of Speech-to-Text
Do you offer voices & transcription other in languages?
We currently only have English voice generation & transcription. But we're working on multilingual voice support, expected to roll out in 2-3 months.
Can I create custom voices (voice cloning)?
Please contact us at founders@snr.audio with your custom voice (voice cloning) usecase. Once approved by our compliance team, you will get access to your custom voice in under 48-72 hours.
Can I use the generated audio & transcription commercially?
Yes, audio & transcription generated with Signal Noise Labs can be used commercially. You own the license to the generated content to perpetuity.
How do I cancel my subscription?
You can cancel your subscription at any time. Go to the Subscription panel in the dashboard and click the "Cancel Subscription" button.
app.snr.audio
SNR.Audio - Text to Speech and Speech to Text
