Sound Synthesis and Acoustic Analysis

Parametric source-filter synthesis of harmonic-noise signals, such as animal vocalizations and human voice, with control over pitch, formants, noise, amplitude modulation, nonlinear phenomena, and morphing. General signal processing tools for audio analysis and manipulation: pitch tracking, formant and vocal tract length estimation, reassigned and auditory spectrograms, modulation spectra and psychoacoustic roughness, self-similarity and surprisal, audio segmentation, pitch and formant shifting, etc. Includes four interactive web apps for audio synthesis, annotation, formant analysis, and manually correcting pitch contours. Reference: Anikin (2019) .

Parametric source-filter synthesis of harmonic-noise signals, such as animal vocalizations and human voice, with control over pitch, formants, noise, amplitude modulation, nonlinear phenomena, and morphing. General signal processing tools for audio analysis and manipulation: pitch tracking, formant and vocal tract length estimation, reassigned and auditory spectrograms, modulation spectra and psychoacoustic roughness, self-similarity and surprisal, audio segmentation, pitch and formant shifting, etc. Includes four interactive web apps for audio synthesis, annotation, formant analysis, and manually correcting pitch contours.

Key functions

Visualization

• spectrogram Ordinary (STFT) spectrograms
• audSpectrogram Auditory spectrograms
• modulationSpectrum Modulation spectra and roughness (see Anikin 2025)
• ssm Self-similarity matrices, acoustic novelty (see Anikin 2026)
• phasegram Nonlinear analysis, phasegrams (see Anikin & Herbst 2025)

Acoustic analysis

• analyze General-purpose acoustic analysis (extracts nearly everything: spectral descriptives, pitch, formants, loudness, roughness, …)
• segment Audio segmentation, analysis of rhythm and temporal structure of sequences
• getSurprisal Shannon and autocorrelation-based surprisal, Bayesian surprise (see Anikin 2026)
• estimateVTL, schwa Formant analysis (see Anikin et al. 2024)

Interactive acoustic analysis

• pitch_app Manually corrected formant measurement
• formant_app Manually corrected pitch tracking
• annotation_app Audio annotation

Sound synthesis

• soundgen The main function for sound and voice synthesis (see Anikin 2019)
• soundgen_app Interactive version of the soundgen() function
• morph Morphing of two sounds based on their soundgen code

Sound modification

• normalizeFolder Peak / RMS etc normalization of recordings
• timeStretch, shiftPitch, prosody, shiftFormants Selective modification of fundamental frequency, duration, and/or resonance frequency
• noiseRemoval, compressor, addAM, resample, etc: various audio effects

Vignettes

• https://cogsci.se/soundgen/spectrograms.html
• https://cogsci.se/soundgen/sound_generation.html
• https://cogsci.se/soundgen/acoustic_analysis.html
• https://cogsci.se/soundgen/matching/matching.html

References

• Anikin, A. (2019). Soundgen: an open-source tool for synthesizing nonverbal vocalizations. Behavior Research Methods, 51(2), 778-792.
• Anikin, A., Barreda, S. & Reby, D. (2024) A practical guide to calculating vocal tract length and scale-invariant formant patterns. Behavior Research Methods 56, 5588–5604.
• Anikin, A. (2025) Acoustic estimation of voice roughness. Attention, Perception, & Psychophysics 87: 1771–1787.
• Anikin, A. & Herbst, C.T. (2025) How to analyze and manipulate nonlinear phenomena in voice recordings. Philosophical Transactions B 380: 20240003.
• Anikin, A. (2026) Measuring surprisal in sound sequences. Behavior Research Methods.

Example of sound synthesis

Use the soundgen() function to create a breathy moan:

s = soundgen(
  sylLen = 230,               # duration of voiced part, ms
  pitch = c(305, 280),        # pitch, Hz (goes down from 305 to 380 Hz)
  ampl = c(0, -20),           # amplitude, dB (gradual fade-out by 20 dB)
  rolloff = -30,              # strong f0, weak harmonics
  temperature = 0.05,         # some stochasticity in generation
  formants = c(260, 960, 1500, 2200,  # F1-F8 formant frequencies, Hz
               2600, 3600, 4200, 4500),
  noise = data.frame(
    time = c(-50, 120, 700),  # time of noise anchors
    value = c(-25, -15, -40)   # noise amplitude, dB
  ),
  rolloffNoise = 0,           # flat noise spectrum before adding formants
  addSilence = 0, samplingRate = 44100, pitchSamplingRate = 44100,
  plot = TRUE, osc = TRUE, ylim = c(0, 6)
)

Example of acoustic analysis

Use the analyze() function to detect pitch and obtain other spectral descriptives of the sound we have just synthesized:

a = analyze(s, 44100, plot = TRUE, ylim = c(0, 6))
#> The sound is too short to be analyzed with amRes = 1 Hz. Actual amRes ~=  1.31

a$detailed[1:5, c('time', 'pitch', 'HNR', 'ampl', 'loudness')]
#>        time    pitch       HNR       ampl  loudness
#> 1  25.00000       NA        NA 0.03313867  6.039053
#> 2  49.98866 298.2525  5.656488 0.18586389 14.131545
#> 3  74.97732 304.5555 15.080634 0.41149933 23.273527
#> 4  99.96599 300.9743 17.070995 0.53578982 27.618641
#> 5 124.95465 296.9162 14.551249 0.49568060 26.568438
colnames(a$detailed)
#>  [1] "duration"           "duration_noSilence" "time"               "amEnvDep"          
#>  [5] "amEnvDepVoiced"     "amEnvFreq"          "amEnvFreqVoiced"    "amEnvPurity"       
#>  [9] "amEnvPurityVoiced"  "amMsFreq"           "amMsFreqVoiced"     "amMsPurity"        
#> [13] "amMsPurityVoiced"   "ampl"               "ampl_noSilence"     "amplVoiced"        
#> [17] "CPP"                "dom"                "domVoiced"          "entropySh"         
#> [21] "entropyShVoiced"    "entropyW"           "entropyWVoiced"     "epoch"             
#> [25] "f1_freq"            "f1_width"           "f2_freq"            "f2_width"          
#> [29] "f3_freq"            "f3_width"           "fluctuation"        "fluctuationVoiced" 
#> [33] "flux"               "fmDep"              "fmFreq"             "fmPurity"          
#> [37] "harmEnergy"         "harmHeight"         "HNR"                "HNRVoiced"         
#> [41] "loudness"           "loudnessVoiced"     "novelty"            "noveltyVoiced"     
#> [45] "peakFreq"           "peakFreqVoiced"     "pitch"              "quartile25"        
#> [49] "quartile25Voiced"   "quartile50"         "quartile50Voiced"   "quartile75"        
#> [53] "quartile75Voiced"   "roughness"          "roughnessVoiced"    "sharpness"         
#> [57] "sharpnessVoiced"    "specCentroid"       "specCentroidVoiced" "specSlope"         
#> [61] "specSlopeVoiced"    "subDep"             "subRatio"           "voiced"