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    Vulavula Transcribe

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    Sold by: Lelapa AI 
    Deployed on AWS
    Transcribe and interpret spoken language across African languages with Lelapa AI's Vulavula Multilingual ASR Model.

    Overview

    At Lelapa AI, we're dedicated to advancing language technology and expanding its accessibility through our specialized Automatic Speech Recognition (ASR) Model for Zulu and Sesotho languages. This innovative model is tailored to effectively transcribe and interpret spoken language, supporting a wide range of applications. By converting spoken words into text, it facilitates seamless communication and interaction, particularly in speech-to-text applications. Currently operational for Zulu and Sesotho, our ongoing efforts aim to extend support to additional South African and Sub-Saharan languages. This powerful tool enhances accessibility and usability, enabling more efficient communication and interaction in multilingual environments.

    Highlights

    • **Expansive Language Support:** Lelapa AI introduces the Vulavula ASR Model, engineered to transcribe and interpret spoken language across a wide array of African languages, significantly expanding access to advanced speech recognition tools beyond dominant global languages.
    • **Precision and Speed:** With its cutting-edge technology, the Vulavula ASR Model excels in swiftly transcribing and interpreting spoken language with a higher degree of accuracy than conventional models, enhancing both user experience and data utility.
    • **Adaptable Applications:** Designed to support diverse needs, Lelapa AI's model is perfect for a range of applications including speech-to-text conversion, voice search, and real-time language translation in multilingual African environments, making it a robust tool for developers and businesses targeting African markets.

    Details

    Delivery method

    Latest version

    Deployed on AWS

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    Pricing

    Vulavula Transcribe

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    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.

    Usage costs (2)

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    Dimension
    Description
    Cost/host/hour
    ml.m5.xlarge Inference (Batch)
    Recommended
    Model inference on the ml.m5.xlarge instance type, batch mode
    $30.00
    ml.m5.xlarge Inference (Real-Time)
    Recommended
    Model inference on the ml.m5.xlarge instance type, real-time mode
    $21.00

    Vendor refund policy

    Refunds for services rendered via third party marketplaces are granted solely at our discretion and only in cases of non-delivery or significant non-conformance with the service description as detailed on our website. All refund requests must be made formally in writing within seven days of purchase. For further assistance, please contact our support team.

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    Legal

    Vendor terms and conditions

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    Usage information

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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:
    Deploy the model as an API endpoint for your applications. When you send data to the endpoint, SageMaker processes it and returns results by API response. The endpoint runs continuously until you delete it. You're billed for software and SageMaker infrastructure costs while the endpoint runs. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Deploy models for real-time inference  .
    Deploy the model to process batches of data stored in Amazon Simple Storage Service (Amazon S3). SageMaker runs the job, processes your data, and returns results to Amazon S3. When complete, SageMaker stops the model. You're billed for software and SageMaker infrastructure costs only during the batch job. Duration depends on your model, instance type, and dataset size. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Batch transform for inference with Amazon SageMaker AI  .
    Version release notes

    This is the first version

    Additional details

    Inputs

    Summary

    The input is of content type audio/wav

    file_path = "input_audio.wav" with open(file_path, 'rb') as file: audio_data = file.read()
    Input MIME type
    audio/wav
    https://github.com/Lelapa-AI/lelapa-aws/blob/main/lelapa_aws/input_audio.wav
    https://github.com/Lelapa-AI/lelapa-aws/blob/main/lelapa_aws/input_audio.wav

    Resources

    Support

    Vendor support

    Lelapa AI Automatic Speech Recognition (ASR) Model support please contact us . support@lelapa.ai 

    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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