Sold by: Neosapience, Inc.
Deployed on AWS
Typecast uses the advanced Typecast SSFM, our next-gen AI voice model that delivers incredibly natural and expressive TTS technology.
Overview
Introducing SSFM (Speech Synthesis Foundation Model), Typecast's cutting-edge AI voice model that represents the next generation of speech synthesis. Built on an advanced large language model, SSFM is 14 times more powerful than its predecessor in understanding language nuances. Trained on a speech dataset 75 times larger than before, it creates incredibly natural and expressive synthetic voices. One of its most impressive features is Voice Cloning - SSFM can replicate any voice with just a 10-second sample, perfectly capturing the speaker's unique style. The model offers complete control over voiceovers, allowing easy adjustments to emotions and speaking pace. Looking ahead, SSFM will support over 30 languages and enable emotion control through natural language prompts. Experience the future of voice technology at https://typecast.ai/ and discover what SSFM can do for you.
Highlights
- Naturalness
- Expressiveness
- Controllability
Details
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Delivery method
Latest version
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.g5.2xlarge Inference (Batch) Recommended | Model inference on the ml.g5.2xlarge instance type, batch mode | $100.00 |
ml.g5.2xlarge Inference (Real-Time) Recommended | Model inference on the ml.g5.2xlarge instance type, real-time mode | $100.00 |
Dimensions summary
You pay by the hour for model inference on the ml.g5.2xlarge instance type. Billing is usage-based and tied to host hours. Two options let you match pricing to how you run the model. Batch mode processes audio in groups, which suits bulk generation and downloadable files. Real-time mode delivers audio as it is generated, which suits live and conversational services. Both bill per host hour, so your cost scales with how long the instance runs. You choose the mode that fits your workload rather than paying for both.
Top-of-mind questions for buyers
You pay for one running ml.g5.2xlarge instance per host hour. This is a GPU-backed instance type used to run the SSFM 2.0 speech synthesis model. Billing counts the time the instance stays running, not the number of audio files or characters generated.
Software charges apply per host hour while the instance runs. A stopped instance does not accrue software host-hour charges. Underlying AWS infrastructure fees, such as storage, may still apply separately even when the instance is not actively running.
Both modes bill per host hour on the same instance type. Choose batch mode to process audio in groups, which suits bulk generation and downloadable narration files. Choose real-time mode to stream audio as it is produced, which suits live services and conversational agents.
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Vendor refund policy
Refund Policy Summary
AWS Marketplace purchases are eligible for refunds. Software products can be fully refunded within 7 days if not functioning as described. Cancellations must be made 7 days before billing. Products with heavy usage, custom implementations, or terms violations are ineligible. Submit requests via AWS Marketplace or help@typecast.ai . Requests are reviewed within 5 business days and processed within 10 business days. Contact help@typecast.ai with questions. Policy updates appear on our AWS Marketplace listing.
Legal
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Initial version
Additional details
Inputs
- Summary
The model accepts input in JSON format.
https://github.com/neosapience/aws-marketplace-ssfm/blob/main/data/input/real-time/input.json
https://github.com/neosapience/aws-marketplace-ssfm/blob/main/data/input/batch/input.json
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
text | A single string containing the input text to be processed by the model. This text serves as the basis for generating the audio output.
| Type: FreeText | Yes |
Resources
Vendor resources
Support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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