Deepgram VS AssemblyAI

Deepgram Reviews

1. suz11    

   10 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

AssemblyAI Reviews

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 / 5 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 / 7 months ago

AssemblyAI mentions (8)

• We Created Something Cool to Help Streamers Grow, What Do You Think? DailyClips.io

  The auto caption is from assemblyai.com, they do a pretty good job. As for manual, you can do `Add Layer` > `Text` from the short-form editor then trim each text layer. Its slow going though. Ideally we will figure out a better interface and build it. For now I recommend using the auto caption, then modifying it to your liking, if there is more than a few words it will probably be faster. Thanks for the kind words! Source: 11 months ago

• How I applied nlp to various youtube videos

  Assemblyai is a great tool for extracting transcripts from videos, I have used it for investor presentations from other sources. - Source: dev.to / over 1 year ago

• Top AI Startups to Watch in 2022

  AssemblyAI is pioneering accurate and accessible speech recognition powered by cutting edge Deep Learning, Machine Learning, and AI research. Its Speech-to-Text API transcribes audio and video files and live audio streams with industry-best accuracy. In addition, the company offers Audio Intelligence APIs that secure higher ROI for users, including Sentiment Analysis, Topic Detection, Content Moderation, Auto... - Source: dev.to / over 2 years ago

• Speaker diarization

  Check out http://assemblyai.com/ - the API has pretty good Diarization results and is free for small volumes of data. Source: over 2 years ago

• I analyzed the last year of popular news podcasts to see if the frequency of negative news could be used to predict the stock market.

  Hello r/python community. I spent a couple weeks analyzing some podcast data from Up First and The Daily over the last year, 8/21/2020 to 8/21/2021 and compared spikes in the frequency of negative news in the podcast to how the stock market performed over the last year. Specifically against the DJIA, the NASDAQ, and the price of Gold. I used Python Selenium to crawl ListenNotes to get links to the mp3 files,... Source: over 2 years ago