In recent years, big companies such as Amazon, Apple, Google, and Microsoft have invested in speech technology. Speech technology implementation can be through software, hardware, and hybrid software and hardware. Speech technology usually uses Artificial Intelligence methods to detect and recognize speech or voice and then perform something based on the speech/voice input. Amazon Echo and Google Home are samples of speech technology implementations in hybrid hardware and software. They can be called smart speaker machines.

In general, a smart speaker machine consists of microphone and speaker devices as sensor and actuator. The speaker can record human voice and then convert it to analog values. A speaker can be used to generate sounds based on signal parameters such as frequency and amplitude. Human voice in analog form is converted to digital form so we can process it easily. In digital form, we can implement various algorithms to it in a computer. One of these tasks is to convert human speech to text. It is usually called speech-to-text. Alternatively, we also can synthesize human voice from text. We need a specific algorithm based in AI to convert text to human speech/voice. You can see a general design of a smart speaker machine here:

Designing a smart speaker machine usually involved integrating a machine learning program such as speech-to-text and text-to-speech. In this case, we'll build a program to recognize human speech in digital form and then convert it into text.

After we obtain text from human speech, we can perform text processing. For instance, if we get the text "turn on LED", we'll perform actions to turn on the LED. It involves text processing to obtain meaning from text. You can see a general design of a text meaning system here: