Goal: Simply to make a simple dialogue between a human being and an agent
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We need to install the required dependencies
pip install requirements.txt -
(Speech-To-Text)
STT- Use google speech recognition api
- calibrates the microphone to the ambient noise for 2 seconds
- plays a beep sound after calibration, so the user can say his/her words
- audio file is sent to google speech recognition api to be analyzed and return the text
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(Text-To-Speech)
TTS- two approaches (one is by using google text to speech, and the other by using python native library pyttsx3)
- both of them takes a text as input, and say it using PC speakers, however, using google we can specify the language
- we can save the dialog as well
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(Understanding Natural Language)
NLP- Named Entity Recognition
NER- extracting information from unstructured text to classify named entities into a set of predefined categories, for example person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc.
- Part-of-speech Tagging
POS- to get better understanding of the text, we need to understand what are the properties -or predicates- of the nouns in a given text
- Named Entity Recognition
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Putting it all together, this mini project was built using few strings for the bot to speak out
TTS, and afterwards, waiting for the user input -after mic calibration-STT, these words from the user were analyzed using `spa
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