When the Tx request is successfully carried out an event is placed in another queue in the same service bus resource. Azure Functions (time triggered by default) pick up those events and act, namely creating Tx requests using the Azure Speech Services batch pipeline. As soon as files land in a storage container, the Grid Event that indicates the complete upload of a file is filtered and pushed to a Service bus topic. The diagram is simple and hopefully self-explanatory. It utilizes Azure resources such as Service Bus and Azure Functions to orchestrate transcription requests to Azure Speech Services from audio files landing in your dedicated storage containers.īefore we delve deeper into the set-up instructions, let us have a look at the architecture of the solution this ARM template builds. This is a smart client in the sense that it implements best practices and optimized against the capabilities of the Azure Speech infrastructure. In order to speed up your transcription solution, for those of you that do not have the time to invest in getting to know our API or related best practices, we created an ingestion layer (a client for batch transcription) that will help you set-up a full blown, scalable and secure transcription pipeline without writing any code. Getting started with any API requires some amount of time investment in learning the API, understanding its scope, and getting value through trial and error. Through an ARM template deployment, all the resources necessary to seamlessly process your audio files are set-up and set in motion. If you are looking for a quick and effortless way to transcribe your audio files or even explore transcription, without writing any code, then this solution is for you. Getting started with Azure Speech and Batch Ingestion Clientīatch Ingestion Client is as a zero-touch transcription solution for all your audio files in your Azure Storage. Azure AI > Azure Speech and Batch Ingestion
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