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It's fast - but for an API, not the fastest speech-to-text. For a long while I hadn't done research and trusted them. Then tried Whisper and Picovoice. On-device latency is nothing comparable with cloud APIs. If latency is important go with Whisper or Picovoice. If customization is also important go with Picovoice.
don't get me wrong it's still faster than amazon, Microsoft or Assemblyai
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There are three routes you can go with this. The simplest would probably be to use Microsoft's Face API, which is part of their Azure Cognitive Services platform. All of the computing is done in the cloud, and at least for your purposes, the modelling necessary to detect faces has already been performed by Microsoft, so it's a single method call to send it a picture and receive back a bounding box. The caveat is... Source: over 1 year ago
Azure Cognitive Services provide a few interesting AI as a service offerings beyond CLU & LUIS that can be helpful for conversational AI:. - Source: dev.to / over 1 year ago
Hello, not sure about the quality of this API as I’ve just heard about it but thought it might help you: Azure Cognitive Services. Source: over 1 year ago
Cognitive Services Https://azure.microsoft.com/en-us/services/cognitive-services/. - Source: dev.to / almost 2 years ago
Microsoft Azure offers an umbrella service known as Cognitive Services. This service provides AI capabilities that you can integrate into your existing applications through a single managed area. - Source: dev.to / about 2 years ago
Lastly, we will be using Deepgram Audio Diarization APIs to get speaker details from a sample audio clip. - Source: dev.to / 5 months ago
There are other AI-powered APIs out there to consider, too. For example, Deepgram can be used to transcribe audio (better than Whisper, offered by OpenAI), ElevenLabs can be used to generate speech from text (including using custom voices, which OpenAI's TTS can't currently do), etc. Depending on what you're trying to make, a combination of these services may be what you need. In any case, Python is going to be... Source: 5 months ago
This guide delves deep into the world of YouTube video summarization, harnessing the power of cutting-edge technologies including Deepgram for superior audio transcription, Langchain for harvesting the power of the LLM, and Mistral 7B, a state-of-the-art and open-source LLM. - Source: dev.to / 6 months ago
Historically it's been challenging to provide closed captioning for live experiences, be it a live interview, a sports game with commentary, or a livestream. But Deepgram's AI tooling has changed this, allowing users to easily convert realtime streams of audio into accurate transcripts. - Source: dev.to / 7 months ago
To deliver the best possible output, we’ve tested a wide range of AI models and supporting tools. Today, we’re producing industry-leading clinical notes text by combining Deepgram’s highly capable transcription models, ScienceIO’s healthcare-specific AI for processing medical data, and the Microsoft Azure OpenAI GPT-4 large language model. We’ve worked closely with all three teams to bring this new capability to... - Source: dev.to / 8 months ago
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