About
The AI Voice Inspector POC build leverages deep learning techniques to differentiate between real and synthetically generated audio speech samples. Key aspects: Feature Engineering: Extracts spectral and temporal features from audio waveforms using advanced signal processing techniques. Cybersecurity Application: Reliably detecting synthetic and deep fake audio content, providing a robust defence mechanism against such emerging audio-based attacks. Core deep learning model: Keras Bidirectional GRU and FN architecture engineered to deliver robust accuracy and generalisation. Diverse Dataset: Synthetic audio from cutting-edge open-source TTS/vocoder models, and real speaker recordings from a recognised speech corpus. Continuous development: Further training on additional speech corpora for robustness against evolving audio synthesis techniques. Advanced Model Variation: In development. This cutting-edge build has the potential for reliable synthetic audio detection, maintaining privacy and security against AI-driven threats.
