Python is a powerful programming language widely used in many AI and natural language processing applications. Therefore, Python is also an ideal tool for developing text-to-speech (TTS) applications.
There are several useful Python libraries that allow us to build TTS systems. Such as Google’s gTTS library, pyttsx3 library, speech_recognition library,… These libraries provide functions and APIs to synthesize speech from text easily.
To develop a TTS program in Python, the main steps include:
Text input and preprocessing: remove special characters, normalize text.
Analyze the grammar and semantics of the text to determine its correct reading.
Generate phonetic text containing pronunciation information.
Use the TTS library to synthesize speech from phonetic text.
Export speech in desired audio format (MP3, WAV,…).
The advantage of Python is that it is easy to expand and customize TTS applications to have more features such as voice recognition, language translation, etc. Thanks to that, many smart TTS products can be built. Python-based.
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Overall, with its powerful capabilities and rich libraries, Python is the ideal tool for developing natural language processing applications such as text-to-speech. Python simplifies the process of building and extending TTS systems.