Version 1.5.0 available!
Version 1.5.0 available!


Acoustic Voice Quality Analysis:  Simple | Standardized | Intuitive

We have developed VOXplot with the aim of providing a tool for acoustic voice analysis that is based on proven and reliable algorithms and at the same time easy and intuitive to use. VOXplot is open source and available for free for Windows, macOS and Linux.

Simple and Reliable

VOXplot's user interface is designed to be simple, robust, and reliable. A complete acoustic analysis of voice quality requires just a few clicks.

VOXplot is multilingual. The user interface is available in three languages: English, German, Dutch. Valid analysis parameters are currently available for 11 languages: German, Dutch, Spanish, Japanese, Korean, Brazilian Portuguese, Malayalam, Kannada, Persian/Farsi, Italian (w/o ABI), and Finnish (w/o ABI).

Standardized Analysis

VOXplot is developed in close cooperation with scientific advisor Prof. Ben Barsties v. Latoszek.

The analysis of a total of 19 acoustic parameters and two multidimensional indices is based on proven Praat algorithms with scientifically based presets. It follows the recommendations for the analysis of acoustic voice quality parameters published in the works on the voice quality indices AVQI[1] and ABI[2].

Intuitive Visualization

VOXplot generates a voice quality profile with all examination data and measured values on a single PDF page.

In addition to numerical values, the result can be easily and intuitively assessed using a norm-value circle of 12 acoustic parameters assessing hoarseness and breathiness.

Further assessment of the sustained vowel is supported by means of a narrowband spectrogram.

User Interface

The clear user interface of VOXplot provides a simple workflow that can be applied without a long training period. The user interface is currently available in three languages: German, English, Dutch.

In the left area of the main window, examination data can be entered (optional). The right area of the main window is used to select two voice samples: Continuous speech and a sustained vowel (preferably the vowel [a:]). These two voice samples are necessary for the calculation of the voice quality indices AVQI and ABI. For this purpose, a text passage (content and length of the passage is language-depend) and the vowel [a:] with a duration of 3 sec. are required.

VOXplot main window

VOXplot main window

For AVQI and ABI analysis, 9 analysis languages are currently available in VOXplot, which can be selected in the settings. The language selection is based on validation studies in German[3], Japanese[4,5], Korean[6], Dutch[7,8], Spanish[9], Brazilian Portuguese[10,11], the South Indian languages Malayalam and Kannada[15,16], and Persian/Farsi.

Italian[17] and Finnish[18] are also available, but with AVQI only so far; evaluation studies for ABI are currently implemented. A validation study for English (AVQI and ABI) is in preparation[12].

Analysis of only one voice sample (coninuous speech or sustained vowel) is possible. However, AVQI and ABI calculation is then omitted.

If voice samples are already available as WAV files, they can simply be loaded into VOXplot. If necessary, the signal section to be included in the analysis can still be adjusted after loading. VOXplot tries to determine the recording date of voice samples automatically. If this fails, the date can be corrected manually.

VOXplot signal editor

Adjust signal section

Of course, voice samples can also be recorded, trimmed, and saved directly with VOXplot.

VOXplot can use all recording devices that are connected to the computer and are recognized and supported by the operating system.

As soon as at least one voice sample is available, the analysis can be started. A duration of 3 sec. is assumed for analysis of the sustained vowel. When loading existing samples, you will be automatically informed if the vowel duration does not meet this requirement; vowels that are too long can be trimmed within VOXplot.

By clicking on the green button, all relevant acoustic voice parameters are calculated fully automatically, no further input is required. (Depending on the performance of the computer, the analysis may take a few seconds).

VOXplot start analysis

Start analysis

Acoustic Analysis

VOXplot uses Praat version 6.0.48, which has been validated in several AVQI or ABI studies, to calculate the following acoustic voice parameters (Praat is already included in the executable VOXplot packages and does not need to be installed separately):

  • Slope (dB)
  • Tilt (dB)
  • HF noise (dB)
  • HNR-D (dB)
  • H1H2 (dB)
  • CPPS (dB)
  • Jitter local (%)
  • Jitter ppq5 (%)
  • Shimmer (%)
  • Shimmer (dB)
  • HNR (dB)
  • PSD (ms)
  • Voice breaks
  • GNE
  • Pitch mean (Hz)
  • Pitch min (Hz)
  • Pitch max (Hz)
  • Pitch sd (Hz)
  • Pitch range (st)

If two voice samples are available (continuous speech/CS & sustained vowel/SV), all parameters (except pitch) are also calculated for the combination of both samples (Combi) and the two voice quality indices Acoustic Voice Quality Index (AVQI) and Acoustic Breathiness Index (ABI) are computed.

In order to be able to better assess the analysis results, norm values are provided for most vowel parameters. Norm values are based on the analysis of over 200 voices. A publication on this topic is in preparation; we will keep you up to date in the News.

Due to the close cooperation with the scientific consultant Prof. Ben Barsties v. Latoszek, VOXplot is characterized by high quality and reliable analysis procedures. Prof. Barsties v. Latoszek is an active researcher in the field of acoustic voice analysis with a special focus on multiparametric voice quality indices (AVQI & ABI), and publishes regularly in internationally renowned journals (Journal of Voice; The Laryngoscope; Clinical Otolaryngology; Journal of Speech, Language, and Hearing Research; Logopedics Phoniatrics Vocology etc.).

Voice Profile

Analysis results are presented as a voice profile on a single PDF page. The profile contains examination data, numerical analysis results of the vowel sample (incl. norm values), a narrowband spectrogram of the vowel sample, and a norm-value circle that highlights deviations of the vowel sample in 12 acoustic dimensions using an intuitive traffic light system (norm range: green / deviation: red).

The left half of the diagram shows six parameters that best correspond to the voice abnormality of hoarseness. The right half shows six parameters that best correspond to the pathological subcomponent of hoarseness: breathiness of a voice. This assignment of parameters is based on an as yet unpublished study of more than 200 voices analyzed in VOXplot and the findings from meta-analyses[13,14].

The voice profile can be archived as a PDF, PNG or JPG file. In addition, numerical analysis results can be exported in CSV format for further processing, e.g. in Excel.



Barsties B, Maryn Y. External validation of the Acoustic Voice Quality Index version 03.01 with extended representativity. Ann Otol Rhinol Laryngol. 2016;125(7):571-583.


Barsties v. Latoszek B, Kim GH, Delgado Hernández J, et al. The validity of the Acoustic Breathiness Index in the evaluation of breathy voice quality: A Meta-Analysis. Clin Otolaryngol. 2021;46(1):31-40.


Barsties v Latoszek B, Lehnert B, Janotte B. Validation of the Acoustic Voice Quality Index version 03.01 and Acoustic Breathiness Index in German. J Voice. 2020;34(1):157.e17-157.e25.


Hosokawa K, Barsties v. Latoszek B, Iwahashi T, et al. The Acoustic Voice Quality Index version 03.01 for the Japanese-speaking population. J Voice. 2019;33(1):125.e1-125.e12.


Hosokawa K, Barsties v. Latoszek B, Ferrer-Riesgo CA, et al. Acoustic Breathiness Index for the Japanese-speaking population: Validation study and exploration of affecting factors. J Speech Lang Hear Res. 2019;62(8):2617-2631.


Kim GH, Barsties v. Latoszek B, Lee YW. Validation of Acoustic Voice Quality Index version 3.01 and Acoustic Breathiness Index in Korean population [published online ahead of print, 2019 Nov 7]. J Voice. 2019;S0892-1997(19)30342-X.


Barsties B, Maryn Y. The improvement of internal consistency of the Acoustic Voice Quality Index. Am J Otolaryngol. 2015;36(5):647-656.


Barsties v. Latoszek B, Maryn Y, Gerrits E, et al. The Acoustic Breathiness Index (ABI): A multivariate acoustic model for breathiness. J Voice. 2017;31(4):511.e11-511.e27.


Delgado Hernández J, León Gómez NM, Jiménez A, et al. Validation of the Acoustic Voice Quality Index Version 03.01 and the Acoustic Breathiness Index in the Spanish language. Ann Otol Rhinol Laryngol. 2018;127(5):317-326.


Englert M, Barsties v. Latoszek B, Maryn Y, et al. Validation of the Acoustic Voice Quality Index, version 03.01, to the Brazilian Portuguese language. J Voice. 2021;35(1):160.e15-160.e21.


Englert M, Barsties v. Latoszek B, Maryn Y, et al. Validation of the Acoustic Breathiness Index to the Brazilian Portuguese language [published online ahead of print, 2021 Jan 6]. Logoped Phoniatr Vocol. 2021;1-7.


Castillo A, Codino J, Rubin A, Barsties v. Latoszek B, Hunter EJ. Validation of the Acoustic Voice Quality Index Version 03.01 and the Acoustic Breathiness Index in American English.


Maryn Y, Roy N, De Bodt M, et al. Acoustic measurement of overall voice quality: a meta-analysis. J Acoust Soc Am. 2009;126(5):2619-2634.


Barsties v. Latoszek B, Maryn Y, Gerrits E, et al. A meta-analysis: Acoustic measurement of roughness and breathiness. J Speech Lang Hear Res. 2018;61(2):298-323.


Jayakumar T, Rajasudhakar R, Benoy J J. Comparison and Validation of Acoustic Voice Quality Index Version 2 and Version 3 among South Indian Population. J Voice. 2022; in press.


Jayakumar T, Benoy J J. Validation of Acoustic Breathiness Index (ABI) in the South Indian Population. J Voice. 2022; in press.


Fantini M, Ricci Maccarini A, Firino A, et al. Validation of the Acoustic Voice Quality Index (AVQI) Version 03.01 in Italian. J Voice. 2021; in press.


Kankare E, Rantala L, Ikävalko T, Barsties v. Latoszek B, Laukkanen A-M. Akustisen Äänenlaatuindeksin (AVQI) Version 03.01 Validointi Suomenkielisille Puhujille. Puhe ja kieli. 2020;40(3):165–182.