text to speech python

Text to speech (TTS) in Python is the process of converting text into synthesized speech using the Python library. TTS can be used in many applications such as audiobook reading, virtual assistant systems, GPS navigation systems, etc. There are several popular Python libraries used for TTS including gTTS, pyttsx3, speech_recognition, etc.

gTTS (Google Text-to-Speech) is a simple library that allows text-to-speech conversion using Google’s TTS API. It does not require complicated speech synthesizer installation and allows saving output audio as mp3 files. To use gTTS, it is necessary to first install the library using the command “pip install gTTS”. Then enter the text and language as arguments to gTTS’s tts function to create the TTS object. Finally call the save() method to save the output audio.
pyttsx3 is a more advanced TTS library that allows customization of many features such as speaking speed, volume, voice, etc. It supports many speech synthesis engines such as sapi5, nsss, espeak. To use pyttsx3, it is necessary to install the library using the command “pip install pyttsx3”. Then instantiate the engine object and use the say() method to convert text to speech.
Additionally, the speech_recognition library allows speech-to-text conversion in Python. It allows recording voice from microphone and converting to text. This is very useful for speech recognition applications. Other libraries like pyaudio, sounddevice also support recording and playing audio in Python.

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Thus, Python provides many powerful libraries to handle text to speech and speech to text. TTS helps create synthesized speech from text, while STT converts speech to text. Applications such as virtual assistants, audiobook readers, and voice recognition all use these techniques. TTS and STT are becoming increasingly popular and effective thanks to the development of deep learning and natural language processing models.