Sold by: Appen (fka Figure Eight)Â
Overview
This model detects the gender of a speaker in a clip of audio and can be used to better help service customers and personalize their experiences with your product or service. It was mostly trained on English speakers from North America, though we have tested with both English and multilingual speakers (Arabic, Chinese, Corsican, French, German, Russian) and the model does generalize well to different accents. We have tested .wav audio, with a 44100 sample rate, 16 bits per sample, and 2 channels, with audio length ranging from 10 seconds up to 7 minutes long.
Highlights
- Detect the gender of a speaker in an audio clip to better help service customers and personalize their experiences with your product or service
Details
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Delivery method
Latest version
Deployed on AWS
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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.c5.xlarge Inference (Batch) Recommended | Model inference on the ml.c5.xlarge instance type, batch mode | $0.25 |
ml.c5.xlarge Inference (Real-Time) Recommended | Model inference on the ml.c5.xlarge instance type, real-time mode | $0.25 |
Vendor refund policy
We do not currently support refunds, but you can cancel at any time.
Legal
Vendor terms and conditions
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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
For CPU: We recommend using a ml.c5.xlarge (CPU) instance type. Our tests on these took 4.8 seconds prediction time for average payloads of 2 MB when invoked from a desktop.
Additional details
Inputs
- Summary
Usage Instructions: Example for the /invocations endpoint:
Input (application/json): Audio file of the recording [wav, base64 encoded]. Payload: {"instances": [{"audio": {"b64": "BASE_64_ENCODED_WAV_FILE_CONTENTS"}}]}
Output (application/json): Classification into male or female
Content: {"labels": ["female", ... ], "predictions": [ { "label": "female", "scores": [0.3, ...]}]}
- Input MIME type
- json
See Input Summary
See Input Summary
Resources
Vendor resources
Support
Vendor support
If you need any support, have questions, or suggestions, please email ml-support@figure-eight.comÂ
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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