All You Have To Do Is Listen

Rob Kapilow

Rob Kapilow has been helping audiences hear more in great music for almost twenty years with his What Makes It Great? series on NPR, at Lincoln Center, and in concert halls throughout the US and Canada. In this book, he gives you a set of tools you can use when listening to any piece of music in order to hear its “plot”—its story told in notes. The musical examples are available free for download to help you hear the ideas presented. Whether you are an experienced concertgoer or a newcomer to classical music, the listening principles Kapilow shares will help you "get" music in an exciting, fresh new way. "Kapilow gets audiences in tune with classical music at a deeper and more immediate level than many of them thought possible." —Los Angeles Times "Rob Kapilow is awfully good at what he does. We need him." —The Boston Globe "A wonderful guy who brings music alive!" —Katie Couric "Rob Kapilow leaps into the void dividing music analysis from appreciation and fills it with exhilarating details and sensations." —The New York Times "You could practically see the light bulbs going on above people's heads. . . . The audience could decipher the music in a new, deeper way. It was the total opposite of passive listening."

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Experimental book profileGenerated by GPT-5.4 nano · may contain inaccuracies

This is an unverified interpretation of the catalog description, offered as an opt-in discovery experiment—not as bibliographic fact.

  1. 01 Central figures

    None extracted with sufficient confidence.

  2. 02 Central places

    None extracted with sufficient confidence.

  3. 03 Suggested argument

    The book provides listening tools that let readers hear any piece of music’s “plot”—the story it tells in notes—thereby making music more immediate and decipherable.

    Model confidence 72%

  4. 04 Reading orientation

    30 / 100 academic

    Serious trade

    An estimate of intended readership and scholarly apparatus—not quality or importance.

Confidence percentages are the model's own estimates. Profile confidence: 66%.