Acoustic Voice Quality Index (AVQI) using pladdrr

Computes the Acoustic Voice Quality Index (AVQI) from continuous speech and sustained vowel recordings using pladdrr's Praat bindings. Supports both AVQI v2.03 (Maryn et al. 2010) and v3.01 (Barsties & Maryn 2015).

Usage

lst_avqi(svDF, csDF, version = "v2.03", min.sv = 1000, toFile = FALSE, return_jstf = FALSE, explicitExt = "avqi", outputDirectory = NULL, verbose = TRUE)

Arguments

svDF: Data frame with sustained vowel samples. Must contain columns: listOfFiles, start, end (in milliseconds)
csDF: Data frame with continuous speech samples. Must contain columns: listOfFiles, start, end (in milliseconds)
version: Character. AVQI version: "v2.03" (default) or "v3.01"
min.sv: Minimum sustained vowel duration in milliseconds (default: 1000)
toFile: Logical. If TRUE, write results to JSTF file. Default FALSE.
return_jstf: Logical. Return JsonTrackObj instead of data.frame? Default FALSE. When both toFile and return_jstf are TRUE, the file is written AND the object returned.
explicitExt: Character. File extension for output. Default "avqi".
outputDirectory: Character. Output directory path. Default NULL (use input directory).
verbose: Logical. Print progress messages (default TRUE)

Value

If toFile=FALSE (default), a list with AVQI measurements. If toFile=TRUE, invisibly returns the path to the written JSTF file.

The list contains:

version: AVQI version used
avqi: Acoustic Voice Quality Index (0-10 scale)
cpps: Cepstral Peak Prominence Smoothed (dB)
hnr: Harmonics-to-Noise Ratio (dB)
shimmer_local: Local shimmer (percent)
shimmer_db: Local shimmer in dB
slope: LTAS slope (dB)
tilt: LTAS tilt (dB)

Details

The AVQI combines 6 acoustic measures: CPPS, HNR, shimmer (local and dB), LTAS slope, and LTAS tilt into a single voice quality index (0-10 scale).

References

(Maryn et al. 2010)

(Barsties and Maryn 2015)

Examples

if (FALSE) { # \dontrun{
# Define sustained vowel samples
sv <- data.frame(
  listOfFiles = c("sv1.wav", "sv2.wav"),
  start = c(100, 150),  # milliseconds
  end = c(2500, 2800)
)

# Define continuous speech samples
cs <- data.frame(
  listOfFiles = c("cs1.wav", "cs2.wav"),
  start = c(80, 120),
  end = c(3500, 4000)
)

# Compute AVQI (v2.03)
result <- lst_avqi(sv, cs)
print(result$avqi)

# Compute AVQI v3.01
result_v3 <- lst_avqi(sv, cs, version = "v3.01")

# Write to JSTF file
lst_avqi(sv, cs, toFile = TRUE)
track <- read_track("sv1.avqi")
df <- as.data.frame(track)
} # }