Deep and Shallow: Machine Learning in Music and Audio
暫譯: 深度與淺度：音樂與音頻中的機器學習

本書將信號與語言模型結合在一起，探討聲音如何被計算機系統表示和操作，以及我們的設備如何通過信息理論的視角來識別特定的聲音模式，使其具有音樂意義或創造性。

Shlomo Dubnov is a Professor in the Music Department and Affiliate Professor in Computer Science and Engineering at the University of California, San Diego. He is best known for his research on poly-spectral analysis of musical timbre and inventing the method of Music Information Dynamics with applications in Computer Audition and Machine improvisation. His previous books on The Structure of Style: Algorithmic Approaches to Understanding Manner and Meaning and Cross-Cultural Multimedia Computing: Semantic and Aesthetic Modeling were published by Springer.

Ross Greer is a PhD Candidate in Electrical & Computer Engineering at the University of California, San Diego, where he conducts research at the intersection of artificial intelligence and human agent interaction. Beyond exploring technological approaches to musical expression, Ross creates music as a conductor and orchestrator for instrumental ensembles. Ross received his B.S. and B.A. degrees in EECS, Engineering Physics, and Music from UC Berkeley, and an M.S. in Electrical & Computer Engineering from UC San Diego.

Shlomo Dubnov 是加州大學聖地亞哥分校音樂系的教授及計算機科學與工程系的兼任教授。他以對音樂音色的多頻譜分析研究而聞名，並發明了音樂資訊動態（Music Information Dynamics）的方法，該方法在計算機聽覺（Computer Audition）和機器即興（Machine improvisation）中有應用。他之前的著作包括《風格的結構：理解方式與意義的演算法方法》（The Structure of Style: Algorithmic Approaches to Understanding Manner and Meaning）和《跨文化多媒體計算：語義與美學建模》（Cross-Cultural Multimedia Computing: Semantic and Aesthetic Modeling），均由Springer出版。

Ross Greer 是加州大學聖地亞哥分校電機與計算機工程的博士候選人，他的研究集中於人工智慧與人類代理互動的交集。除了探索音樂表達的技術方法外，Ross 還作為指揮和編曲家為器樂合奏創作音樂。Ross 在加州大學伯克利分校獲得電機與計算機科學（EECS）、工程物理和音樂的學士學位，並在加州大學聖地亞哥分校獲得電機與計算機工程的碩士學位。