It allows converting human speech into text. Google Cloud Speech API is a part of Google Cloud infrastructure. We will describe the general aspects of each API and then compare their main features in the table. There are some other less-known products which can work with speech: Here is a list of some popular APIs for speech processing: The second is to convert the text into human speech. First one is to transform speech to text. There are two main tasks in speech processing. In this article, we want to compare the most popular APIs which can work with human speech. So, you will be able to detect, when you should use API (and what API) and when you should think about your own system. You can understand what each API can do, what pros and cons they have and so on. Also, it is possible to improve the quality of the results if you build the algorithms by yourself. This way is rather complex, it requires many efforts and resources, but as a result, you can create a system that will be ideally compatible with your needs. Nevertheless, there are many situations where you cannot use API and need to develop speech recognition system from scratch. The one more advantage of this way is that you can save such valuable resources as time and money. In other words, if your problem is standard and well-known. This approach is useful when you don’t need something special. Then you will receive the response with completed tasks. All you need to do is to send an HTTP request with required content to the API’s server. Usually, they provide a convenient interface. You don’t have to be the expert in natural language processing to use these APIs. Today, many large companies provide APIs for performing different machine learning tasks. That’s why speech recognition is a perspective and significant area of artificial intelligence and machine learning. Machines replace more and more human labor force, and these machines should be able to communicate with us using our language. It is especially important regarding the development of self-services in different places: shops, transport, hotels, etc. There is a significant demand in transforming human speech into text and text into speech. Speech processing is a very popular area of machine learning.
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