By Tanay Pant
Build a voice-controlled digital assistant utilizing speech-to-text engines, text-to-speech engines, and dialog modules. This e-book exhibits you ways to application the digital assistant to assemble information from the net (weather facts, information from Wikipedia, facts mining); play tune; and take notes. every one bankruptcy covers development a mini project/module to make the digital assistant larger. you will advance the software program on Linux or OS X earlier than moving it in your Raspberry Pi, prepared for deploying on your personal home-automation or net of items applications.
Building a digital Assistant for Raspberry Pi walks you thru a number of STTs and TTSs and the implementation of those parts with assistance from Python. After that you'll commence enforcing common sense for dealing with consumer queries and instructions, in order that the person may have conversations with Melissa. you are going to then paintings to enhance common sense dealing with to become aware of what the consumer desires Melissa to do. additionally, you will paintings on construction a few precious applications/modules for Melissa, on the way to let you achieve fascinating info from Melissa akin to the time, climate info, and knowledge from Wikipedia.
You will increase a track enjoying program in addition to a word taking program for Melissa, laying the rules for a way Melissa might be additional prolonged. ultimately, you are going to the right way to installation this software program on your Raspberry Pi and the way you could extra scale Melissa to make her extra clever, interactive and the way you should use her in different tasks corresponding to domestic automation as well.
What you will Learn
- Design the workflow and realize the ideas of establishing a voice managed assistant
- Develop modules for having conversations with the assistant
- Enable the assistant to retrieve details from the internet
- Build utilities like a song participant and a observe taking software for the digital assistant
- Integrate this software program with a Raspberry Pi
Who This publication Is For
This e-book is for an individual who has equipped a house automation venture with Raspberry Pi and now are looking to improve it through making it voice-controlled. The publication could additionally curiosity scholars from laptop technology or similar disciplines.
Read or Download Building a Virtual Assistant for Raspberry Pi: The practical guide for constructing a voice-controlled virtual assistant PDF
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Extra info for Building a Virtual Assistant for Raspberry Pi: The practical guide for constructing a voice-controlled virtual assistant
Yaml file: music_path: . py. py. mp3gen(music_path) Finally, edit the brain() function to look like the following: brain(name, speech_text, music_path, city_name, city_code, proxy_username, proxy_password) It’s time to program the module itself! lower())) return music_list def music_player(file_name): """ This function takes the name of a music file as an argument and plays it depending on the OS. join(words_of_message) music_listing = mp3gen(music_path) for i in range(0, len(music_listing)): if cleaned_message in music_listing[i]: music_player(music_listing[i]) Starting from the beginning, you import the built-in os, sys, and random.
To test the program, you can add the following additional line at the bottom of the code: tts("Hi handsome, this is Melissa") Save the code, and run the Python file. It should execute successfully. Repeat What I Say For the sake of exercise and fun, construct a Python program that detects whatever you say and repeats it. This involves a combination of the STT and TTS engines. recognize_google(audio) 16 CHAPTER 2 ■ UNDERSTANDING AND BUILDING AN APPLICATION WITH STT AND TTS Integrating STT and TTS in Melissa As discussed in Chapter 1, you are past the stages of learning concepts and prototyping STT and TTS; now it’s time to integrate the STT engine as well as the TTS engine in Melissa in a proper, reusable fashion.
You revisit this file later to edit the code and improve check_message(). close() # Functioning Variables name = profile_data['name'] city_name = profile_data['city_name'] tts('Welcome ' + name + ', systems are now ready to run. py. Inside the main() function, you add brain(), where you pass the name and speech_text arguments. Your program is now ready to run and to be tested. ” into the microphone. ” There are two problems with the existing system: 1. The library of conversation clauses is limited and static.