PyAudio

PyAudio is a Python library for handling audio streams, built on top of PortAudio, and supports cross-platform audio recording, playback, and real-time processing. It allows developers to work directly with raw audio data, making it suitable for developing voice recognition frontends, audio visualization tools, and recording applications. Although its API is relatively low-level, it provides flexible control over audio input and output.

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SpeechRecognition

SpeechRecognition is a user-friendly speech recognition library that wraps multiple engines and APIs, including Google Web Speech, Sphinx, Wit.ai, and Microsoft Bing Voice. With just a few lines of code, users can extract text from microphones or audio files, making it ideal for beginners exploring speech recognition projects.

pyttsx3

pyttsx3 is an offline Text-to-Speech (TTS) library that works on Windows, macOS, and Linux without requiring an internet connection. It offers a simple interface for converting text into spoken output, making it suitable for building voice assistants, screen readers, and educational software.

gTTS

gTTS is a Python library based on Google Translate's Text-to-Speech service, capable of converting text into natural-sounding speech and supporting multiple languages. It generates audio files by calling Google's online TTS API, making it suitable for applications requiring high-quality voice output, such as voice announcements and video narration.

LibROSA

LibROSA is a Python library specialized in music and audio analysis, widely used in areas such as audio feature extraction, tempo detection, and pitch recognition. It provides a rich set of functions for loading, visualizing, transforming, and analyzing audio signals, commonly used in machine learning for audio preprocessing and feature engineering. Built on NumPy and SciPy, LibROSA offers strong performance and extensibility.

DeepSpeech

Mozilla DeepSpeech is an open-source speech recognition engine built using deep learning and TensorFlow. It implements the Deep Speech architecture developed by Baidu and supports custom training and local deployment with high accuracy and low latency. DeepSpeech is particularly well-suited for offline speech recognition scenarios, such as embedded devices and privacy-sensitive applications.