<p><div><div><div><div data-show-faces="false" data-height="21" data-width="100" data-layout="button_count" data-send="true" data-href="https://www.r-bloggers.com/book-review-sound-analysis-and-synthesis-with-r/"></div></div><div></div></div><div></div></div>
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(This article was first published on <strong><a href="https://walczak.org/2018/11/book-review-sound-analysis-and-synthesis-with-r/"> R-bloggers – Eryk Walczak</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>R might not be the most obvious tool when it comes to analysing audio data. However, an increasing number of packages allows analysing and synthesising sounds. One of such packages is seewave. <a rel="nofollow" href="https://scholar.google.com/citations?user=wH4U0ygAAAAJ&hl=en" target="_blank">Jerome Sueur</a>, one of the authors of <a rel="nofollow" href="https://cran.r-project.org/web/packages/seewave/seewave.pdf" target="_blank">seewave</a>, now wrote a book about working with audio data in R. The book is entitled <a rel="nofollow" href="https://www.springer.com/us/book/9783319776453" target="_blank">Sound Analysis and Synthesis with R</a> and was published by Springer in 2018. I highly recommend it to anyone working with audio data.</p>
<p><a rel="nofollow" href="https://www.springer.com/us/book/9783319776453" target="_blank"><img sizes="(max-width: 289px) 100vw, 289px" src="https://i1.wp.com/walczak.org/wp-content/uploads/2018/10/Sound-Analysis-and-Synthesis-with-R-book-cover.png?resize=289%2C439&ssl=1" alt="" width="289" class="wp-image-637" data-recalc-dims="1" height="439"></a></p>
<p>The book starts with a general explanation of sound. Then it introduces R to readers who have no experience using it. Over the 17 chapters the author describes basic audio analyses that can be conducted with R. The underlying concepts are explained using both mathematical equations and R code. There is also some material on sound synthesis, but this is a minor point when compared to the space devoted to the analysis. <a rel="nofollow" href="https://link.springer.com/chapter/10.1007%2F978-3-319-77647-7_1" target="_blank">Additional materials</a> include sound samples used across the book.</p>
<p>As mentioned before the main topic of the book is the analysis of sound, predominantly in scientific settings. Researchers (or data scientists) typically would want to load, visualise, play, and quantify a particular sound that they work on. These basic steps are desribed in this book with code examples that are simple to follow and richly illustrated with R-generated plots. Check the book preview <a rel="nofollow" href="https://books.google.co.uk/books?id=zfVeDwAAQBAJ&lpg=PR1&pg=PR13#v=onepage&q&f=false" target="_blank">here</a>.</p>
<p>If you ever need to paste, delete, repeat or reverse audio files with R then recipes for these tasks can be found in this book. The book contains twenty <em>DIY Boxes</em> which show alternative ways to use already coded functions and demonstrate new tasks. These boxes cover topics ranging from loading audio files, plotting to frequency and amplitude analysis.</p>
<p>Even though the author created his own package, the book shows how to use a wide range of audio-specific R package like <a rel="nofollow" href="https://cran.r-project.org/web/packages/tuneR/index.html" target="_blank">tuneR</a> or <a rel="nofollow" href="https://cran.r-project.org/web/packages/warbleR/index.html" target="_blank">warbleR</a>.</p>
<p>I can only wish that this book had been released earlier. It would have saved me a lot of pain conducting audio analyses.</p>
<p>Final verdict: <strong>5/5</strong></p>
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