This article assesses the communication of the European Central Bank (ECB) using Natural Language Processing (NLP) techniques. We show the evolution of discourse over time and capture the main themes of interest for the central bank that go beyond its traditional mandate of maintaining price stability, enlightening main concerns and themes of discussion among board members. We also built sentiment signals compatible with any form of language, both formal and informal, an important step as the ECB aims to enhance communication with non-expert audiences. In a second step, we measure the impact of the ECB’s communication on the EUR/USD exchange rate. We found that our quantitative series, both topics and sentiment, improve financial-linked models consistently in all periods analyzed (2.5% on average). Meaningful signals comprise a broad range of subjects and vary in time. This suggests that overall ECB’s talk matters for asset prices, including themes not directly related to monetary policy. This result is particularly important in a context in which the ECB, as well as other major central banks, are moving towards integrating issues closer to the society into their scope of action, implying that subjects, which were considered peripheral, may become central. This emphasizes the importance for markets to effectively track central banks’ communication to improve investment processes.