Noise-augmented transformer-based automatic speech recognizer using a novel noise distillation system

Key Points

• The automatic speech recognizer significantly improves under noisy conditions with effective noise distillation.
• Key performance is evaluated using metrics like word error rate, showing considerable reductions in noise impact.
• Deep learning techniques utilizing transformer-based architectures form the core of the recognition system.
• These findings may enable more robust speech recognition technologies, particularly in real-world applications dealing with background noise.