Azure speech to text read file how to#

See Deploy a model for examples of how to manage deployment endpoints. You must deploy a custom endpoint to use a Custom Speech model. PathĮndpoints are applicable for Custom Speech. This table includes all the operations that you can perform on datasets.

See Upload training and testing datasets for examples of how to upload datasets. For example, you can compare the performance of a model trained with a specific dataset to the performance of a model trained with a different dataset. You can use datasets to train and test the performance of different models. You can register your webhooks where notifications are sent.ĭatasets are applicable for Custom Speech. Some operations support webhook notifications.Use your own storage accounts for logs, transcription files, and other data. Upload data from Azure storage accounts by using a shared access signature (SAS) URI.Request the manifest of the models that you create, to set up on-premises containers.Get logs for each endpoint if logs have been requested for that endpoint.Speech-to-text REST API includes such features as: Batch transcription: Transcribe audio files as a batch from multiple URLs or an Azure container.Copy models to other subscriptions if you want colleagues to have access to a model that you built, or if you want to deploy a model to more than one region. Custom Speech: With Custom Speech, you can upload your own data, test and train a custom model, compare accuracy between models, and deploy a model to a custom endpoint.See the Speech to Text API v3.0 reference documentation

Azure speech to text read file