We combine modern methods from Speech Emotion Recognition and Natural Language Processing with high-frequency financial data to precisely analyze how the vocal emo-tions and language of ECB President Mario Draghi affect the yields and yield spreads of major euro area economies. This novel approach to central bank communication reveals that vocal and verbal emotions significantly impact the yield curve, with effects varying in magnitude and direction. Positive signals raise German and French yields, while negative signals increase Italian yields. Our analysis of bond spreads indicates that positive communication influences the risk-free yield component, whereas nega-tive communication affects the risk premium. Additionally, our study contributes by constructing a synchronized dataset for voice and language analysis.