Speech-to-Text: Azure Speech to Text vs Google Cloud Speech to Text
Azure Speech to Text
Microsoft Azure Speech to Text is one of the most advanced voice-recognition platforms around. As part of Microsoft's Cognitive Speech Services product range, it makes use of deep learning algorithms to overcome poor sound quality and can adapt to diverse speaking styles for accurate audio transcriptions.
The key Azure Speech to Text feature is the access it grants to Microsoft’s powerful natural language processing system. Over the past few years, Microsoft’s speech AI has reached several important milestones. This means it can now complete tasks that were previously impossible for a speech recognition service, such as accurately transcribing cross-talk during small group conversations.
Google Cloud Speech-to-Text
Google Cloud Speech API is a part of Google Cloud infrastructure. It allows converting human speech into text. This API supports more than 110 languages. The system supports customization in the form of providing the list of possible words to be recognized (this thing is especially useful if you want to use speech recognition in some devices or other situations where the list of possible words is limited). API can work both in batch and real-time modes. It is stable against side noises in the audio. For some languages the filter for inappropriate words is available. The system is built using deep neural networks and can be improved over time. The files you want to process can be directly fed to the API or be stored on the Google Cloud Storage.
The most effective way to compare these two engines is to test them: the performance can truely depend on your data and your needs. It is to facilitate the testing and use of this type of engine that we have developed Eden AI: a unique API connected to the best AI engines and combined with a powerful management platform.