Permissively-Licensed Named Entity Recognition on the JVM

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The ability to correctly identify entities, such as places, people, and organizations, adds a powerful level of natural language understanding to applications. This post introduces a MIT-licensed one-click deployment to Azure for web services that lets developers get started with a wide range of natural language tasks in 5 minutes or less, by consuming simple HTTP services for language identification, tokenization, part-of-speech-tagging and named entity recognition.

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Building a Custom Spark Connector for Near Real-Time Speech-to-Text Transcription

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This post describes in detail the Azure Cognitive Services speech-to-text WebSocket protocol and shows how to implement the protocol in Java. This enables us to transcribe audio to text in near real-time. We then show how to feed the transcribed radio into a pipeline based on Spark Streaming for further analysis, augmentation, and aggregation. The Java client is reusable across a wide range of text-to-speech scenarios that require time-efficient speech-to-text transcription in more than 10 languages including English, French, Spanish, German and Chinese.

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