Deploy high quality voices for your apps, website and other services at scale.
Voice Quality
Google Cloud Text-to-Speech Samples
Mean Opinion Score
Fiction
3.93
Non-Fiction
3.82
Conversation
3.42
Murf API Samples
Mean Opinion Score
Fiction
N/A
Non-Fiction
N/A
Conversation
N/A
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 derived from comprehensive, professionally-conducted evaluations, and are anonymized to ensure unbiased results.
Features
Google Cloud Text-to-Speech Features
Voice Cloning
Multi-lingual
Per-word Timestamps
Pitch Control
Speed Control
Phone Formats (e.g. pcm_mulaw)
Murf API Features
Voice Cloning
Multi-lingual
Per-word Timestamps
Pitch Control
Speed Control
Phone Formats (e.g. pcm_mulaw)
Features - Conclusion
Both Google Cloud Text-to-Speech and Murf API offer a robust set of features for text-to-speech conversion, including voice cloning, multi-lingual support, pitch and speed control, and compatibility with phone formats.
However, Google Cloud Text-to-Speech does not support per-word timestamps, a feature also absent in Murf API, indicating a common limitation in these services.
Overall, the feature sets are quite similar, suggesting that the choice between these two services may come down to other factors such as pricing, voice quality, or specific use case requirements.
Pricing & Plans
Google Cloud Text-to-Speech Pricing
Free
$0/mo
1M characters
Pay As You Go
$16per
1M characters
Murf API Pricing
API Subscription
$3000/year
12M characters (per year)
Pricing & Plans - Conclusion
In a direct comparison of annual costs across various usage scenarios, Google Cloud Text-to-Speech consistently offers a more affordable option than Murf API.
For low, medium, and high usage levels, Google Cloud Text-to-Speech's pricing structure results in significantly lower annual costs compared to Murf API's flat annual rate.
This makes Google Cloud Text-to-Speech a more cost-effective choice for users with varying levels of text-to-speech needs.
Customer Reviews
Google Cloud Text-to-Speech Reviews
4.6 out of 5
Average of 163 ratings from leading review sites.
Customers appreciate Google Cloud Text-to-Speech for its multilingual support, high-quality voices, and ease of integration. It is praised for its ability to handle various languages and accents, making it versatile for different applications. However, users are dissatisfied with its dependency on internet connectivity and find the pricing structure confusing and potentially costly. The lack of offline functionality is a significant drawback for many. Despite these issues, the service is valued for its accessibility features and seamless integration with other Google services.
Multilingual support
Voice quality
Ease of integration
Internet dependency
Pricing transparency
Offline functionality
Murf API Reviews
3.8 out of 5
Average of 819 ratings from leading review sites.
Murf API generally receives praise for its variety of natural-sounding voices, user-friendly interface, and quick setup, making it a popular choice for voiceover projects. Customers appreciate the diverse voice options and the ability to customize speech patterns. However, there are significant concerns about the pricing model, which many find too expensive and restrictive in terms of voice generation limits. Additionally, there are complaints about customer service and misleading information regarding free trials and subscriptions. Issues with billing practices and refund policies are also frequently mentioned, causing distrust among some users.
When comparing Google Cloud Text-to-Speech and Murf API, both services offer a comprehensive set of features including voice cloning, multi-lingual support, and pitch and speed control, with neither supporting per-word timestamps.
Google Cloud Text-to-Speech, however, stands out for its more affordable pricing structure across various usage levels and its slightly higher mean opinion scores in voice quality, making it a more cost-effective and potentially more natural-sounding option for users.
Ultimately, the choice between the two may hinge on specific budget constraints and quality preferences.
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