portaudio VS deepgram-python-sdk

Thank you. I actually already did and no bites. Did in a couple facebook groups and also no bites. Its a rather complex issue as it appears to be something on a code level. https://github.com/PortAudio/portaudio/issues/523

For sound, there's PortAudio for C and C++, and Windows, Mac, and Linux; FMOD comes in C++.

However, PyAudio depends on another library called portaudio, which is not part of the default Linux dependencies. To install it on your machine, you need to issue the following command on your terminal:

I am trying to build a portable sound synthesiser using the cross-platform library portaudio. The library has it's own CMake file to be built with. I think I have managed to build it as part of my project (build finishes with exit code 0) but I can't figure how to actually use it's imports. Any #include I try to use results in cannot open source file.

The bug fix will be included in the imminent PortAudio release: https://github.com/PortAudio/portaudio/pull/504

In my testing with Mixxx, PipeWire works better with the JACK API than PulseAudio. With PulseAudio I got frequent crackles with Mixxx using this PortAudio branch. Using PipeWire via the JACK API, I get the same performance at low latencies as JACK.

Here's a code example: https://github.com/PortAudio/portaudio/blob/master/examples/paex_saw.c

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.