Real World Haskell VS Deepgram

Real World Haskell Reviews

Deepgram Reviews

1. suz11    

   11 months ago
   Fast

   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

   🏁 Competitors: Picovoice.ai, Google Cloud Speech API, AssemblyAI, Speechmatics, Microsoft Azure, Amazon

   👍 Pros:    Fast|Fast sales|A free demo|Supports multiple languages

   👎 Cons:    Slow support for free customers|Limited free version

Real World Haskell mentions (14)

• Revisiting Haskell after 10 years

  The Real World Haskell book is also outdated, but can also be read online for free, and has many examples and exercises on writing practical and usable applications. Although I have not read the book to the fullest, I still recommend its monad transformers chapter, as it was the one that made it click for me. - Source: dev.to / 4 months ago

• Book list opinion for revision/self-study

  Stage 2: Advanced topics - Real World Haskell - Haskell in Depth. Source: 5 months ago

• Haskell book after Get Programming with Haskell?

  I also liked https://book.realworldhaskell.org/ since it layers up to (wait for it) real world problems e.g reading a barcode from an image. I'm old so the O'Reilly format has a warm place in my heart. More textbooky. Source: about 1 year ago

• What is the best resource to learn Haskell in 2023?

  So we have LYAH, also there is O'Reilly book, which is a bit old but still mostly good, many people start with this book. After any of those three you can probably decide for yourself what to use to continue the study. Source: over 1 year ago

• Building my XMonad config and...wow!

  I worked through Real World Haskell. http://book.realworldhaskell.org/. Source: over 1 year ago

Deepgram mentions (27)

• Building a Live Proctoring System to Detect Multiple Speakers

  Lastly, we will be using Deepgram Audio Diarization APIs to get speaker details from a sample audio clip. - Source: dev.to / 4 months ago

• How do I begin building AI tools for myself?

  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

• Use Langchain, Deepgram, and Mistral 7B to Build a Youtube Video Summarization App

  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

• Create a realtime closed captioning solution with Deepgram and Ably

  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 / 6 months ago

• Introducing Daily's AI-powered Clinical Notes API

  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