Starts a shiny app for manually editing pitch contours. IMPORTANT: please use
Firefox on a Linux or Windows PC. A bug in Chrome interferes with correct
audio playback; Mac OS is not supported due to an unresolved issue with png
transparency. The settings in the panels on the left correspond to arguments
analyze - see '?analyze' and the vignette on acoustic
analysis for help and examples. You can verify the pitch contours first, and
then feed them back into
analyze (see examples).
The app produces a .csv file with one row per audio file. Apart from the usual descriptives from analyze(), there are two additional columns: "time" with time stamps (the midpoint of each STFT frame, ms) and "pitch" with the manually corrected pitch values for each frame (Hz). To process pitch contours further in R, do something like:
1 2 3
Start by setting the basic analysis settings such as pitchFloor, pitchCeiling, silence, etc. Then click "Load audio" to upload one or several audio files (wav/mp3). Long files will be very slow, so please cut your audio into manageable chunks (ideally <10 s). If Shiny complains that maximum upload size is exceeded, you can increase it, say to 30 MB, with 'options(shiny.maxRequestSize = 30 * 1024^2)'. Once the audio has been uploaded to the browser, fine-tune the analysis settings as needed, edit the pitch contour in the first file to your satisfaction, then click "Next" to proceed to the next file, etc. Remember that setting a reasonable prior is often faster than adjusting the contour one anchor at a time. When done, click "Save results". If working with many files, you might want to save the results occasionally in case the app crashes (although you should still be able to recover your data if it does - see below).
How to edit pitch contours
Left-click to add a new anchor, double-click to remove it or unvoice the frame. Each time you make a change, the entire pitch contour is re-fit, so making a change in one frame can affect the path through candidates in adjacent frames. You can control this behavior by changing the settings in Out/Path and Out/Smoothing. If correctly configured, the app corrects the contour with only a few manual values - you shouldn't need to manually edit every single frame. For longer files, you can zoom in/out and navigate within the file. You can also select a region to voice/unvoice or shift it as a whole or to set a prior based on selected frequency range.
Recovering lost data
Every time you click "next" or "last" to move in between files in the queue, the output you've got so far is saved in a backup file called "temp.csv". If the app crashes or is closed without saving the results, this backup file preserves your data. To recover it, access this file manually on disk or simply restart pitch_app() - a dialog box will pop up and ask whether you wank to append the old data to the new one. Path to backup file: "[R_installation_folder]/soundgen/shiny/pitch_app/www/temp.csv", for example, "/home/allgoodguys/R/x86_64-pc-linux-gnu-library/3.6/soundgen/shiny/pitch_app/www/temp.csv"
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
## Not run: # Recommended workflow for analyzing a lot of short audio files path_to_audio = '~/Downloads/temp' # our audio lives here # STEP 0: set up Firefox as default browser either system-wide or just in R. # For ex., on Linux, run: options('browser' = '/usr/bin/firefox') # path to the executable # STEP 1: extract manually corrected pitch contours pitch_app() # runs in Firefox df1 = read.csv('~/Downloads/output.csv') # saved output from pitch_app() # STEP 2: run analyzeFolder() with manually corrected pitch contours to obtain accurate descriptives like the proportion of energy in harmonics above f0, etc. This also gives you formants and loudness estimates (disabled in pitch_app to speed things up) df2 = analyzeFolder(path_to_audio, pitchMethods = NULL, # don't need to re-analyze pitch nFormants = 5, # now we can measure formants as well pitchManual = df1 # df1 contains our manually corrected contours ) # STEP 3: add other acoustic descriptors, for ex. df3 = segmentFolder(path_to_audio) df4 = modulationSpectrumFolder(path_to_audio) # STEP 4: merge df2, df3, df4, ... in R or a spreadsheet editor to have all acoustic descriptives together ## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.