Remember the settings I mentioned earlier? There are two of them that can make analysis slower or faster. Last.fm for example requires, that "You will not make more than 5 requests per originating IP address per second, averaged over a 5 minute period, without prior written consent" ( Terms of Service ยง4.4). This means that analysis speed is limited by your network bandwidth, server load, and possible throttling dictated by third party terms of service. Last but not least, other, non-computational tasks-like missing metadata and Last.fm tag import-always depend on an online service, no matter what analysis options you use. And if you must use an external drive, try to connect it via USB 3-it's substantially faster than its predecessor. The best case is currently a fast internal SSD. So while a NAS is very convenient for your home entertainment system, for analysis it's not the greatest idea. a slow spinning disk connected via USB 2 or an old wireless network. For disk IO the worst case is a music collection on a slow external device that's connected via a slow interface, e.g. Keep in mind that analysis speed is bound by two factors: disk IO and processing power ( Table 1). Table 1: Disk IO and effort of computational analysis tasks So when you enable those analysis tasks and need results quickly for thousands of songs, think about what you really want: Each checked task adds more analysis time. And in the case of album replay gain, multiple files have to be read. Replay gain calculation also dictates that the whole file must be decoded and analyzed. Automatic segmentation on the other hand, requires beaTunes to read the whole file and do some hefty computations. Assuming a steady beat, beaTunes does not need to look at the whole file when analyzing just for BPM. It's worth noting though, that some of these require much more effort than others (see Table 1). ![]() Regarding online lookup, pretty much the same rules apply to the other computation tasks-namely segmentation, color, key, replay gain, and silence detection. But if you have lots of local processing power, fast disks, and like to stay in control, not using the online database may be the better choice. In the end, you might want to use online resources, if computing values locally is too slow and you don't care much about tweaking the algorithm. And if you don't use online services for any task, analysis speed only depends on your personal hardware and some settings. Additionally, you get to choose which algorithm beaTunes will use ( OnsetPeak is the more modern algorithm). Assuming you know what general tempo your music is in, this can help you to avoid the octave error. If you decide not to use online resources, you can force beaTunes to calculate a BPM value in a certain range, e.g. And when you're online, analysis speed depends on your Internet connection's bandwidth and the general load on the database server. Plus, you cannot use this feature when you are offline. There is no way to increase the octave accuracy via tweaks. But the fact remains: you give up control over the largest error source. This is not all bad-the database uses some fancy heuristics to ignore bad values and attempts to pick the "right" ones. Doing so, you give up any control over the BPM range (or octave) as well as the used algorithm. When downloading values from the database, you are downloading values computed or entered by other beaTunes users. ![]() ![]() This so called octave error is the biggest problem in automatic BPM detection. While accuracy differs depending on genre, overall state-of-the-art BPM analysis is currently roughly 74% accurate-94%, if you are willing to tolerate x2 and x0.5 errors. Let's take the BPM analysis as an example. ![]() To trigger this download-first-behavior, you must check the box Use online resources in the analysis options dialog-that's the dialog that pops up, when you click on Analyze (see screenshot below). If the value cannot be found, beaTunes falls back on its built-in algorithm. For most analysis tasks, beaTunes offers to simply download the desired value instead of computing it.
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