deepgram-js-sdk VS deepgram-python-sdk

Deepgram Node SDK - Official JavaScript SDK for Deepgram's automated speech recognition APIs.

RRP uses several packages to handle the functionality of the program. The command line input is acquired through using readline-sync which asks users for a YouTube link and an email address. YouTube mp3 Downloader is used to specify YouTube videos from which the audio data should be extracted, converted to MP3, and temporarily stored on disk. DeepGram SDK then converts the stored MP3 file to a text transcript. And then SendGrid Mail is utilized to send the transcript as an email to a specified address.

The useMicrophone composable will rely on the browser Media Stream API and the getUserMedia method to request permission to use the browser microphone of the user and pull the audio from it. Since there are several other blog posts in Deepgram Docs about this nifty API, I won't go into detail about how it works. Check out Brian's post for a general introduction to it.

You can learn more about the inner workings by consulting the Next and Deepgram documentation.

If you’ve browsed Deepgram’s documentation but need some help understanding or implementing a feature, @bekahhw from the Deepgram team will be here to jump in and assist you. This thread is a great resource for you whether you’re taking part in the “Build” or “Innovative Ideas” challenge.

Check out the other options supported by the Deepgram Node SDK and if you have any questions feel free to reach out to us on Twitter (we are @DeepgramDevs).

ou have the perfect solution for a speech recognition provider, Deepgram. You get to coding, using their Python SDK.

Deepgram has a Python SDK that we can tap into that’s located on Github. We’ll also need to get started with an API key which we can grab in Console, a game-like hub in Deepgram to try the different types of transcriptions in many coding languages, including Python. When you first sign up, you'll get $150 in API credits to try out Deepgram's speech AI capabilities.

You’ll only need two Python libraries, PyAudio and websockets. The PyAudio library allows you to get sound from your computer’s microphone. The WebSockets Python library is used too since we’re working with live streaming. Deepgram also has a Python SDK but in this post, we’ll hit the API endpoint directly.

Python SDK - Official Python SDK for Deepgram's automated speech recognition APIs.

I also needed a speech-to-text API and leveraged Deepgram. We have a Python SDK I tapped into that made it super quick and easy to get up and running with the voice recognition transcription.

I needed to use an AI voice recognition API that would transcribe the podcast audio. That part was easy to figure out. Use the Deepgram Python SDK. I used the prerecorded option in this scenario to transcribe the already recorded audio. I also grabbed a Deepgram API key from our console, which has gamified missions you can try to get up to speed quicker.

The transcribe_with_deepgram() function comes from our Deepgram Python SDK, located here in Github.

Deepgram’s REST API - A speech-to-text API built on a 100% deep learning platform. It offers up to 90% translation accuracy with model training with no human validation necessary. I chose to write about it because the developer experience is excellent; should you want to extend the capabilities of this API further, you’ll find exactly what you need in Deepgram’s docs and tutorials.

Today I used Dolby.io and Deepgram to enhance an audio file and transcribe the speech of the interview into text. These two APIs seem like a great combination for many future projects!

To get started with our Deepgram Python SDK, you can visit our open-sourced Github repository here. The samples in the README.md will help you get up and running with real-time streaming and recorded audio. We also created special Python documentation for developers, which you can access here.