Otter Voice Notes VS Deepgram

Otter Voice Notes Reviews

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

Otter Voice Notes mentions (232)

• How to build a Google Meet AI assistant app in 10 minutes without coding

  Of course, there are many existing solutions like Otter.ai or Fathom in the market. But in case you want to build a tool yourself and customize the output of it, then you are on the same page as me. To develop this application, we will use Unbody to convert input video transcriptions into intelligence/generative content and Appsmith to make it easy to design and build the UI of our app without extensive front-end... - Source: dev.to / 5 months ago

• I'm looking for a particular type of software and I don't know where else to go.

  This is weird but I wonder if you could use something like https://otter.ai/. Record your notes as you are going. That should give you at least text of all of your welds. You’d still have to punch it later. Seems like there’s got to be a better way to do this. Stopping every time to break your flow sounds like a huge pain in the ass. Curious what you come up with. Source: 5 months ago

• How I tackled more than 2+ conflicting meetings

  Is there any app from otter.ai that you run on personal machine? How does otter.ai process 4 different audio streams? Source: 5 months ago

• How I tackled more than 2+ conflicting meetings

  Job laptop -> 3.5mm aux (this turns into speaker output) -> 3.5mm mic/audio splitter (this turns into microphone input) -> 3.5mm to usb-c adapter (cause my macbook only has 1 3.5mm aux) --> now the personal macbook has a new "mic input" from the job laptop. Which you can use to pipe audio into otter.ai to transcribe audio. You have to manually name them, but they learn in subsequent meetings. Source: 5 months ago

• How I tackled more than 2+ conflicting meetings

  I recently started to use AI transcription services (you can use any.. But I'm currently using otter.ai) , but I don't have the service join the meetings. I use a 3.5mm aux splitter to pipe the audio out of my job laptop (so one pipe goes to the audio mixer), and use the other split to be passed into a microphone adapter to 3.5mm aux and then to my personal laptop. The personal laptop runs otter.ai to transcribe... Source: 5 months 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 / 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