# `voice` vignette

### version 0.5.6

#### Filipe J. Zabala

#### 2026-05-13

## 0. Basic installation

    # Development version from GitHub
    install.packages('devtools')
    devtools::install_github('filipezabala/voice')

    # Stable version from CRAN
    install.packages('voice')

### 0.1 For Windows Users

If you’re compiling R packages from source, you may need to install RTools, a collection of Windows-specific build tools for R.

### 0.2 For macOS Users

If you’re compiling packages, ensure you have Xcode Command Line Tools installed. You also may need macOS tools.

    # Install Xcode on MacOS
    xcode-select --install

More details may be found at https://github.com/filipezabala/voice.

## 1. Extract features

### 1.1 Load packages and audio files

    # packs
    library(voice)
    library(tidyverse)

    # get path to audio file
    wavDir <- list.files(system.file('extdata', package = 'wrassp'),
                         pattern = glob2rx('*.wav'), full.names = TRUE)

### 1.2 Extract features

    # minimal usage
    M <- voice::extract_features(wavDir)
    glimpse(M)
    #> Rows: 1,196
    #> Columns: 13
    #> $ section_seq      <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16…
    #> $ section_seq_file <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16…
    #> $ wav_path         <chr> "/Library/Frameworks/R.framework/Versions/4.6/Resourc…
    #> $ f0               <dbl> NA, NA, NA, NA, NA, NA, NA, 115.8593, 108.9439, 107.4…
    #> $ f1               <int> NA, NA, NA, NA, 185, 260, 254, 277, 261, 231, 177, 19…
    #> $ f2               <int> 1854, 1886, 1749, 1888, 1962, 1973, 2026, 2037, 2130,…
    #> $ f3               <int> NA, 2893, 2676, 2659, 2639, 2676, 2993, 2932, 3016, 2…
    #> $ f4               <int> 3113, 3708, 3509, 3658, 3248, 3239, 3830, 3479, 3561,…
    #> $ f5               <int> 4191, 4678, 4502, 4331, 3653, 3836, 4602, 4585, 4720,…
    #> $ f6               <int> 5226, 5659, 5035, 5177, 5208, 5146, 5233, 5390, 5366,…
    #> $ f7               <int> 6077, 6725, 6526, 6518, 6493, 6567, 6603, 6532, 6510,…
    #> $ f8               <int> 6675, NA, NA, NA, 7681, 7751, 7803, NA, 7835, 7614, 7…
    #> $ gain             <dbl> 21.63347, 22.76034, 28.52825, 29.67069, 36.25124, 43.…

## 2. Tag

    # creating Extended synthetic data
    E <- dplyr::tibble(subject_id = c(1,1,1,2,2,2,3,3,3), wav_path = wavDir)
    E
    #> # A tibble: 9 × 2
    #>   subject_id wav_path
    #>        <dbl> <chr>
    #> 1          1 /Library/Frameworks/R.framework/Versions/4.6/Resources/library/wra…
    #> 2          1 /Library/Frameworks/R.framework/Versions/4.6/Resources/library/wra…
    #> 3          1 /Library/Frameworks/R.framework/Versions/4.6/Resources/library/wra…
    #> 4          2 /Library/Frameworks/R.framework/Versions/4.6/Resources/library/wra…
    #> 5          2 /Library/Frameworks/R.framework/Versions/4.6/Resources/library/wra…
    #> 6          2 /Library/Frameworks/R.framework/Versions/4.6/Resources/library/wra…
    #> 7          3 /Library/Frameworks/R.framework/Versions/4.6/Resources/library/wra…
    #> 8          3 /Library/Frameworks/R.framework/Versions/4.6/Resources/library/wra…
    #> 9          3 /Library/Frameworks/R.framework/Versions/4.6/Resources/library/wra…

    # minimal usage
    voice::tag(E)
    #> # A tibble: 9 × 7
    #>   wav_path   f0_tag_mean f0_tag_sd f0_tag_vc f0_tag_median f0_tag_iqr f0_tag_mad
    #>   <chr>            <dbl>     <dbl>     <dbl>         <dbl>      <dbl>      <dbl>
    #> 1 /Library/…        85.4      17.6     0.206          76.1       29.4       7.53
    #> 2 /Library/…        85.4      15.6     0.183          80.1       27.8      14.4
    #> 3 /Library/…        84.6      13.0     0.154          78.8       23.9      14.0
    #> 4 /Library/…        84.8      14.5     0.171          79.1       28.1      11.9
    #> 5 /Library/…        86.0      14.7     0.170          78.7       30.0      11.0
    #> 6 /Library/…        82.9      15.6     0.188          74.8       23.8       4.78
    #> 7 /Library/…        78.2      16.2     0.207          73.5       13.4       6.82
    #> 8 /Library/…        84.5      14.5     0.172          78.1       17.8       8.95
    #> 9 /Library/…        81.0      12.2     0.151          75.9       23.1       9.14

    # canonical data
    voice::tag(E, groupBy = 'subject_id')
    #> # A tibble: 3 × 7
    #>   subject_id f0_tag_mean f0_tag_sd f0_tag_vc f0_tag_median f0_tag_iqr f0_tag_mad
    #>        <dbl>       <dbl>     <dbl>     <dbl>         <dbl>      <dbl>      <dbl>
    #> 1          1        85.1      15.3     0.180          78.3       26.8      11.9
    #> 2          2        84.6      14.9     0.176          76.4       28.3       7.97
    #> 3          3        81.0      14.6     0.180          75.6       21.6       8.68

## 3. Visualization

### 3.1 Get audio

    url0 <- 'https://github.com/filipezabala/voiceAudios/raw/refs/heads/main/wav/doremi.wav'
    download.file(url0, paste0(tempdir(), '/doremi.wav'), mode = 'wb')
    voice::embed_audio(url0) # See https://github.com/mccarthy-m-g/embedr for more details.

### 3.2 Media data

    M <- voice::extract_features(tempdir())
    summary(M)

### 3.3 Plot

    voice::piano_plot(M, 0) # f0
    voice::piano_plot(M, 0:1) # f0 + f1

### 3.4 Assign notes

    (f0_spn <- voice::assign_notes(M, fmt = 0, min_points = 22, min_percentile = .85)) # f0
    (f1_spn <- voice::assign_notes(M, fmt = 1, min_points = 22, min_percentile = .85)) # f1

### 3.5 Sheet music

Must have MuseScore and gm.

#### 3.5.1 Notes sequence of f0

    library(gm)
    line_0 <- gm::Line(as.character(f0_spn))
    m0 <- gm::Music() +
      gm::Meter(4, 4) +
      line_0
    gm::show(m0, to = c('score', 'audio'))

#### 3.5.2 Notes sequences of f0 and f1

    line_0 <- gm::Line(as.character(f0_spn))
    line_1 <- gm::Line(as.character(f1_spn))
    m1 <- gm::Music() +
      gm::Meter(4, 4) +
      line_0 + line_1
    gm::show(m1, to = c('score', 'audio'))

## 4. Advanced installation

Python-based functions `diarize` and `extract_features` (when the latter is inferring `f0_praat` and `fmt_praat` features) require a configured Python environment.

### 4.1 Ubuntu

The following steps are used to fully configure `voice` on Ubuntu 24.04 LTS (Noble Numbat). Reports of inconsistencies are welcome.

#### 4.1.1. Curl

Command line tool and library for transferring data with URLs.

    # installing dependencies
    sudo apt-get update
    sudo apt-get install -y libssl-dev autoconf libtool make
    # installing curl
    sudo apt install curl
    # verify installation
    curl --version

#### 4.1.2. ffmpeg

ffmpeg is a cross-platform solution to record, convert and stream audio and video.

    sudo apt-get update
    sudo apt-get install ffmpeg

#### 4.1.3. Audio drivers and extra packages

    sudo apt-get update
    sudo apt-get install portaudio19-dev libasound2-dev libfontconfig1-dev libmagick++-dev libxml2-dev libharfbuzz-dev libfribidi-dev libgdal-dev cmake cmake-doc ninja-build

#### 4.1.4. MuseScore

MuseScore is an open source notation software.

    sudo add-apt-repository ppa:mscore-ubuntu/mscore-stable
    sudo apt-get update
    sudo apt-get install musescore

#### 4.1.5. R

R is a free software environment for statistical computing and graphics. To find out your Ubuntu distribution use `lsb_release -a` at terminal.

    sudo sh -c 'echo "deb https://cloud.r-project.org/bin/linux/ubuntu focal-cran40/" >> /etc/apt/sources.list.d/cran.list'
    sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E084DAB9
    sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 51716619E084DAB9
    gpg -a --export E084DAB9 | sudo apt-key add -

    sudo add-apt-repository ppa:c2d4u.team/c2d4u4.0+

    sudo apt-get update && sudo apt-get upgrade
    sudo apt-get install r-base r-base-dev

#### 4.1.6. RStudio

RStudio is an Integrated Development Environment (IDE) for R. Check for updates here.

    sudo apt-get update
    sudo apt-get install gdebi-core
    wget https://download1.rstudio.org/electron/jammy/amd64/rstudio-2025.05.0-496-amd64.deb
    sudo gdebi rstudio-2025.05.0-496-amd64.deb

#### 4.1.9. R packages

“Packages are the fundamental units of reproducible R code.” Hadley Wickham and Jennifer Bryan. The installation may take several minutes. At terminal run:

    sudo R

Running R as super user paste the following, row by row:

    packs <- c('audio','reticulate','R.utils','seewave','tidyverse','tuneR','wrassp')
    install.packages(packs, dep = TRUE)
    update.packages(ask = FALSE)
    devtools::install_github('egenn/music')
    devtools::install_github('flujoo/gm')

To configure the `gm` package.

    usethis::edit_r_environ()

Add the line `MUSESCORE_PATH=/usr/bin/mscore` to `/root/.Renviron` file. To exit use `:wq` at VI. Save and restart the R/RStudio session.

#### 4.1.10. Miniconda

Miniconda is a free minimal installer for conda, an open source package, dependency and environment management system for any language—Python, R, Ruby, Lua, Scala, Java, JavaScript, C/ C++, FORTRAN and more, that runs on Windows, macOS and Linux.
Follow the instructions at https://docs.conda.io/en/latest/miniconda.html.

At terminal:

    cd ~/Downloads/
    wget -r -np -k https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
    cd repo.anaconda.com/miniconda/
    bash Miniconda3-latest-Linux-x86_64.sh

Do you accept the license terms? [yes|no] `yes`.

Miniconda3 will now be installed into this location: /home/user/miniconda3 [ENTER]

You can undo this by running `conda init --reverse $SHELL`? `yes`

Do you wish the installer to initialize Miniconda3 by running conda init? `yes`.

Close and reopen terminal.

    conda update -n base -c defaults conda

The following packages will be INSTALLED/REMOVED/UPDATED/DOWNGRADED:… Proceed ([y]/n)? `y`

    conda create -n pyvoice python=3.12

The following (NEW) packages will be downloaded/INSTALLED:… Proceed ([y]/n)? `y`

    conda activate pyvoice
    pip install -r https://raw.githubusercontent.com/filipezabala/voice/master/requirements.txt

### 4.2 MacOS

The following steps are used to fully configure `voice` on MacOS Sonoma and Tahoe. Reports of inconsistencies are welcome.

#### 4.2.1. Homebrew

Install Homebrew, ‘The Missing Package Manager for macOS (or Linux)’ and remember to `brew doctor` eventually. At terminal (`command + space 'terminal'`) run:

    /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

#### 4.2.2. wget

GNU Wget is a free software package for retrieving files using HTTP, HTTPS, FTP and FTPS, the most widely used Internet protocols. It is a non-interactive commandline tool, so it may easily be called from scripts, cron jobs, terminals without X-Windows support, etc.

    brew install wget

#### 4.2.3. Python

Python is a programming language that integrate systems. According to this post, it is recommended to install Python 3.8 and 3.9 and make it consistent.

    brew install python@3.12
    python3 --version
    pip3 --version

#### 4.2.4. ffmpeg

ffmpeg is a cross-platform solution to record, convert and stream audio and video. The installation may take several minutes.

    brew install ffmpeg

#### 4.2.5. XQuartz

The XQuartz project is an open-source effort to develop a version of the X.Org X Window System that runs on macOS.

- Download and run https://github.com/XQuartz/XQuartz/releases/download/XQuartz-2.8.5/XQuartz-2.8.5.pkg
- Will take around 320 MB of disk space
- Send XQuartz-2.8.5.dmg to Trash

#### 4.2.6. MacPorts

Follow the instructions from https://guide.macports.org/chunked/installing.macports.html.

#### 4.2.7. tcllib

    sudo port selfupdate && sudo port upgrade tcllib
    sudo port install tcllib

#### 4.2.8. MuseScore

MuseScore is an open source notation software.

- Download and run https://musescore.org/en/download/musescore.dmg
- Drag MuseScore 4 to Applications folder
- Will take around 320 MB of disk space
- Unmount MuseScore-4.2.1 virtual disk and send MuseScore-4.2.1.240230937.dmg to Trash

#### 4.2.9. R

R is a free software environment for statistical computing and graphics.

- Download and run the pkg file according to you architecture from https://cran.r-project.org/bin/macosx/
- Will take around 180 MB of disk space

#### 4.2.10. RStudio

RStudio is an Integrated Development Environment (IDE) for R.

- Download and run https://download1.rstudio.org/electron/macos/RStudio-2025.05.0-496.dmg
- Drag RStudio to Applications folder
- Will take around 770 MB of disk space
- Unmount RStudio virtual disk and send RStudio-2025.05.0-496.dmg to Trash
- Type `command + space 'rstudio'`
- Tools > Global Options… > Appearance > Merbivore (Restart required)

#### 4.2.11. R packages

“Packages are the fundamental units of reproducible R code.” Hadley Wickham and Jennifer Bryan. Type `command + space 'terminal'`

    sudo R

Running R as super user paste the following, one line at a time.

    packs <- c('audio','reticulate','R.utils','seewave','tidyverse','tuneR','wrassp')
    install.packages(packs, dep = TRUE)
    update.packages(ask = FALSE)
    devtools::install_github('egenn/music')
    devtools::install_github('flujoo/gm')

#### 4.2.12. Miniconda

Miniconda is a free minimal installer for conda, an open source package, dependency and environment management system for any language—Python, R, Ruby, Lua, Scala, Java, JavaScript, C/ C++, FORTRAN and more, that runs on Windows, macOS and Linux.

For 64-bit version use

    cd ~/Downloads
    wget -r -np -k https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
    cd repo.anaconda.com/miniconda/
    bash Miniconda3-latest-MacOSX-x86_64.sh

For M1 version use

    cd ~/Downloads
    wget -r -np -k https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh
    cd repo.anaconda.com/miniconda/
    bash Miniconda3-latest-MacOSX-arm64.sh

In order to continue the installation process, please review the license agreement. Please, press ENTER to continue `ENTER`.

You can undo this by running `conda init --reverse $SHELL`? `yes`

Close and reopen terminal.

    export PATH="~/miniconda3/bin:$PATH"
    conda update -n base -c defaults conda

The following packages will be INSTALLED/REMOVED/UPDATED/DOWNGRADED:… Proceed ([y]/n)? `y`

    conda create -n pyvoice python=3.12

The following (NEW) packages will be downloaded/INSTALLED:… Proceed ([y]/n)? `y`

Close and reopen terminal.

    conda activate base
    conda activate pyvoice
    pip install -r https://raw.githubusercontent.com/filipezabala/voice/master/requirements.txt

## 5. Diarize

    # download
    url0 <- 'https://github.com/filipezabala/voiceAudios/raw/main/wav/sherlock0.wav'
    wavDir <- normalizePath(tempdir())
    download.file(url0, paste0(wavDir, '/sherlock0.wav'), mode = 'wb')

Diarization can be performed to detect speaker segments (i.e., ‘who spoke when’).

    # diarize
    voice::diarize(fromWav = wavDir, toRttm = wavDir, token = 'YOUR_TOKEN')

The `voice::diarize()` function creates Rich Transcription Time Marked (RTTM)1 files, space-delimited text files containing one turn per line defined by NIST - National Institute of Standards and Technology. The RTTM files can be read using `voice::read_rttm()`.

    # read_rttm
    (rttm <- voice::read_rttm(wavDir))

Finally, the audio waves can be automatically segmented.

    # split audio wave
    voice::splitw(fromWav = wavDir, fromRttm = wavDir, to = wavDir)
    dir(wavDir, pattern = '.[Ww][Aa][Vv]$')

1. See Appendix C at https://www.nist.gov/system/files/documents/itl/iad/mig/KWS15-evalplan-v05.pdf.↩︎