AI Services on Azure Azure AI Speech Service Fast Transcription Azure recently updated its Speech to Text service to bring what is known as Fast Transcription. It aims to improve on Speech to Text transcription turn-around as the name describes. It is currently in preview at the time of this writing through a REST endpoint and still comes with the
Azure Container Apps Featured Azure Container Apps with Ollama for general AI inference An Azure Container Apps instance can run multiple containers under a construct of a main application container that is supported by other 'sidecar' containers. It gives us the perfect environment to create, for example, a web app that has a complimentary Small Language model inference engine in the
AI Services on Azure Featured Azure AI Speech voice control with OpenAI GPT4 and SSML SSML or Speech Synthesis Markup Language allows us to control the spoken behaviour of a synthesised voice in our application. Within Azure AI Speech, we get the ability to use SSML with the available synthetic and neural voices available from Microsoft and also the neural voices from OpenAI too(with
AI Services on Azure Featured Azure AI Speech to Text vs OpenAI Whisper Azure AI Speech and OpenAI's Whisper model are services that are capable of speech to text transcription not only in the cloud but at the edge too. We do not always entirely need to rely on the use of API keys that authenticate into a cloud-supported inference service
Azure Media Services Azure Media Services Clips Following the Azure Video Indexer indexing Insights I was able to produce from a podcast on a weekly schedule previously, I decided to go further into how this Insights JSON data can be utilised in a helpful way following my previous Summary (discussed here), such as using Azure Media Services
Azure Video Analyser for Media Using Azure Video Analyser for Media in Azure Functions First some clarification, 'Azure Video Analyser for Media' should be considered the new name for what used to be called Video Indexer. It is slightly different from 'Azure Video Analyser' which is currently in Preview. With Azure Video Analyser for Media, it's possible to
Docker Azure Project Overhead Part 2 Following what I did in Overhead Part 1, in Part 2 I wanted to add an improvement whereby the Raspberry Pi would be able to assess what it was seeing and simply report what the result was in text within the result SMS. My hope was to try and eliminate
Azure Functions Azure Project Overhead Part 1 The idea behind the Azure Overhead project is to allow me to essentially see a live view (with images) looking out a window of whether there are available car parking spaces in the shared car parking area at home whenever I am away from home. It's beneficial because
