Updated February 14, 2025
Comparing ElevenLabs and Amazon Polly Voice Models
Comparing ElevenLabs and Amazon Polly Voice Models. Discover the differences in features, pricing, and performance.
Comparing ElevenLabs and Amazon Polly Voice Models
Eleven Labs offers more natural and expressive voices with better emotional range, while Amazon Polly provides reliable, clear speech with extensive language support and AWS integration, though less emotional variation.
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How they stack up
Voice Quality Comparison
When evaluating voice quality between ElevenLabs and Amazon Polly, ElevenLabs stands out with a high pronunciation accuracy of 81.97%.
In comparison, Amazon Polly achieved a slightly lower pronunciation accuracy of 84.72%. However, ElevenLabs has a lower WER of 2.83%, indicating better overall accuracy in speech generation.
Amazon Polly, while slightly behind in WER at 3.18%, maintains a high level of context awareness and prosody accuracy. This evaluation underscores the importance of both pronunciation and overall voice quality in text-to-speech applications.
Latency Analysis
In our latency evaluation, we measured the Time to First Audio (TTFA) for both ElevenLabs and Amazon Polly.
We conducted 100 TTFA measurements for each provider and calculated the 90th percentile score. ElevenLabs demonstrated a TTFA of 135ms, showcasing its efficiency in generating audio quickly. Amazon Polly, while slightly slower, still performed well with a TTFA of 150ms.
This analysis highlights the importance of low latency in real-time applications, where quick audio generation is crucial for user experience.
Hallucination Rate Check
The hallucination rate evaluation between ElevenLabs and Amazon Polly reveals interesting insights.
ElevenLabs, with its advanced algorithms, achieved a lower hallucination rate, indicating that it generates more accurate and contextually relevant speech outputs. In contrast, Amazon Polly, while effective, showed a slightly higher rate of hallucination in certain contexts.
This evaluation emphasizes the need for continuous improvement in AI models to minimize inaccuracies and enhance user trust in voice applications.
Voice Design Control
In assessing voice design controllability, ElevenLabs offers a robust set of features that allow users to fine-tune voice characteristics effectively.
With a high context awareness score of 63.37%, ElevenLabs enables nuanced adjustments in tone and emphasis. Amazon Polly, while also effective, scored slightly lower in context awareness at 55.30%.
This evaluation highlights the importance of controllability in voice design, allowing developers to create tailored experiences that resonate with users.
Pricing Comparison for ElevenLabs and Amazon Polly
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“Cartesia Sonic 3.5 has become one of the top-performing models for us by combining low latency with natural pacing… helping us deliver strong voice quality across a growing set of languages where other models often fall short.”
Lydia Zarcone
Voice Product Manager
“We didn’t switch to Sonic 3.5 because it was incrementally better, we switched because nothing else came close… we’ve seen a 2.9% lift in our conversion and a 12.2% increase in customer engagement.”
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