In the config.py file, create a variable called api_key and store the API key you copied from AssemblyAI. Next download the audio we will transcribe to text into the project directory from this audio link. Now, create a new folder on your desktop, give it any name of your choice and open it with a text editor (VS Code).Ĭreate two files in the root directory and name them config.py and main.py respectively. The API will start transcribing our audio to text.Upload the mp3 file to the AssembyAI API.The transcription process can be divided into 3 simple steps: When working with the AssemblyAI Speech-to-Text API, the process is pretty much simple.ĪssemblyAI API allows us to use a locally stored file or a URL pointing to the mp3 stored on a server, Google Cloud bucket, Amazon S3 bucket or anywhere on the internet. Most of the best Speech-to-Text APIs have deep learning teams working continuously to improve the accuracy and usability of their API. Nowadays, Artificial Intelligence Speech-to-Text recognition transcription accuracy has improved with a high accuracy approaching human accuracy levels. To find your API key move to the Made for developers section then copy the API key and store it as an environment variable or a variable in a different configuration file. Start by creating an account on AssemblyAI then you would be brought to a dashboard like this. You’ll need an API key from AssemblyAI before you can use AssemblyAI’s Speech-to-Text API. I wouldn’t recommend you to upload video or audio files that may contain sensitive information or personal data like credit card numbers, phone numbers, medical history, social security numbers and more. Some companies use the data you upload to train their models to be more accurate and also use them for their own research. When selecting a speech-to-Text API it is highly recommended to put your data privacy as a top priority before thinking of accuracy. When working with Speech-to-Text APIs, you may have questions like what happens to the files you upload for transcription? SpeechBrain is a Pytorch-based toolkit for Speech-to-Text transcription. It’s Facebook AI Research’s Automatic Speech Recognition Toolkit. Wav2Letter is an open-source library written in C++ and uses the ArrayFire tensor library. DeepSpeechĭeepSpeech is an open-source embedded Speech-to-Text library that uses end-to-end model architecture to run in real-time on a variety of devices. Speech-to-Text Transcription Engines are an alternative to Speech-to-Text APIs, they are open source and completely free. Popular Open Source Speech-to-Text Engines Unlike Google Speech-to-Text API, AWS Transcribe has lower accuracy and only supports transcribing files stored in an Amazon S3 bucket.ĪWS Transcribe offers 60 minutes of free transcription per month for the first 12 months of use. Other than that, automatic transcription will save you plenty of labor time and a voice recorder mobile app will give you the freedom to record on-the-go.At the time of writing this article, AssembyAI only supports English transcription but their API supports every audio and video file format out-of-the-box. While MP3 audio is better when it comes to storage space, WAV files are crisper and better for fine-tune editing. Don’t forget to check out recording files’ formats. The ability to download separate participant tracks is also helpful in giving you more editing control. You’ll want tools for automatic noise suppression, echo cancellation, and easy audio clip creation. The better your recording quality, the less editing but for quick fixes look for software that already comes with some easy editing tools. Find online software with local recording that can record your voice in high resolution without worrying about internet issues getting in the way. With the right audio recorder, you don’t need to compromise resolution because you’re recording online. The most important thing to consider when looking for an online voice recorder is quality.
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