But transcribing those recordings into written format can be a very laborious process. Transform audio interviews into written contentĪudio-recorded interviews offer you instant access to accurate information. With BigSpeak, your team has access to important meeting information and insights, without the need for time-consuming manual transcription from your team members. With our meeting transcription solution, you can streamline your workflow and save time and effort on transcribing your meetings. This accuracy is achieved through the use of advanced natural language processing and machine learning techniques, which enable our software to understand the nuances of spoken language and produce highly accurate written transcripts. This means that even in a group meeting setting, our software can accurately distinguish between different speakers and attribute the words to the right person. However, with our powerful meeting transcription solution, the process has never been easier.īigSpeak will identify up to 5 different voices from your speech. Transcribing meetings can be a time-consuming task that requires a great deal of attention to detail. Use BigSpeak for your day-to-day activities. Our smart tool works great in any of these 5 languages, recognizing the spoken words and transcribing them into text. Multilingual speech-to-text softwareĪccurate speech-to-text results supported in English, French, German, Italian, and Japanese. We’re using the latest technologies in natural language processing and machine learning to achieve outstanding accuracy in transcribing spoken words. BigSpeak helps you easily convert audio inputs into text files, supporting multiple languages.Īccurately transform spoken words into written text easily, for interviews, meetings, or even live speeches recorded straight into our app. endpoints/base/:test operation (includes ':') in version 3.1.Automatically transform voice to text with our powerful AI tool. This table includes all the operations that you can perform on endpoints. 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 REST API v3.0 reference documentation
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