This book offers a comprehensive guide to voice, speech, and speaker recognition, blending theory, coding, datasets, and real-world applications. It traces speech technology’s evolution from early prototypes to modern transformer-based systems, highlighting applications in virtual assistants, accessibility, and biometrics. Covering speech anatomy, audio preprocessing, and feature extraction techniques like MFCC, it explains libraries such as Librosa and PyDub. Machine learning and deep learning models, including CNNs, RNNs, and hybrid approaches, are detailed with code examples. Practical projects use datasets like CommonVoice and LibriSpeech, culminating in voice-controlled applications. The book emphasizes future trends, challenges, and career opportunities in speech AI.
