AudioDistance
✖
AudioDistance

returns a distance measure between the audio tracks of video1 and video2.
Details and Options




- AudioDistance computes a dissimilarity measure between audio objects that may compare waveforms or other features of the signals, using different distance functions.
- If audio1 and audio2 are of different durations, the distance is computed on the trimmed signals to the shorter duration by default.
- The following options can be specified:
-
DistanceFunction Automatic the distance function to use Masking Automatic the audio intervals to use for comparison PartitionGranularity Automatic audio partitioning specification SampleRate Automatic sample rate for conforming audioi - By default, using DistanceFunction->Automatic, the EuclideanDistance of audio waveforms is computed. Compute other measures using different distance functions or different features.
- The following distance functions are computed from the Fourier transform of audioi:
-
"SpectralEuclidean" Euclidean applied to the power spectra (default) "SpectralItakuraSaito" maximum likelihood of LPC-derived spectral envelopes "SpectralMagnitudePhaseDistortion" the average of magnitude and phase spectral distances "SpectralRMSLog" Euclidean applied to the log of power spectra "SpectralFirstOrderDifferential" distance between first-order derivatives of power spectra "SpectralSecondOrderDifferential" distance between second-order derivatives of power spectra "Cepstral" Euclidean applied to the power cepstra - Additional DistanceFunction settings are also available and can work on different audio features:
-
EuclideanDistance Euclidean distance SquaredEuclideanDistance squared Euclidean distance NormalizedSquaredEuclideanDistance normalized squared Euclidean distance RootMeanSquare root mean square distance ManhattanDistance Manhattan or "city block" distance CosineDistance angular cosine distance CorrelationDistance correlation coefficient distance WarpingDistance dynamic time warping (DTW) distance f an arbitrary function f - By default, WarpingDistance is computed from the "MFCC" features and all other distances are computed from "AudioData".
- Using DistanceFunction->{method,FeatureExtractor->f}, a different feature extractor can be specified.
- Possible settings for FeatureExtractor include:
-
"AudioData" audio data "Formants" frequencies of the formants of the signal "LPC" linear prediction coefficients "MelSpectrogram" mel-scale audio spectrogram "MFCC" mel-frequency cepstral coefficients vectors sequence "Novelty" estimated measure for significant changes "Spectrogram" spectrogram - By default, AudioDistance is computed on the trimmed signals to the shorter duration.
- Use the Masking option to compute the distance measure on different intervals. Possible settings include:
-
Automatic trim to the shorter duration (default) All pad to the longer duration {t1,t2} compare the signals between times t1 and t2 {{t11,t12},{t21,t22}} t11 to t12 from audio1 compared to t21 to t22 from audio2 - Using Masking->{{t22,t12}},{t21,t22}}, the duration of the two intervals should be the same.
- PartitionGranularity is only used with features that work on partitioned audio, like "MFCC", and ignored otherwise.
- By default, SampleRate->Automatic takes the highest sample rate in all audioi.
Examples
open allclose allBasic Examples (1)Summary of the most common use cases
Scope (2)Survey of the scope of standard use cases
Distance of two audio signals with different lengths:

https://wolfram.com/xid/0b0lajyqolu-sll80f

The longer signal is trimmed to the shorter duration:

https://wolfram.com/xid/0b0lajyqolu-5bcgrl

Distance of the audio tracks of two videos:

https://wolfram.com/xid/0b0lajyqolu-1pxdss

Options (13)Common values & functionality for each option
DistanceFunction (6)
By default, the "SpectralEuclidean" distance is used:

https://wolfram.com/xid/0b0lajyqolu-lilh2m

Various distances are computed on the sample values of the audio signals:

https://wolfram.com/xid/0b0lajyqolu-3y65ix

https://wolfram.com/xid/0b0lajyqolu-hbn91l

Distances computed on the spectrum compare the frequency content rather than the sample values:

https://wolfram.com/xid/0b0lajyqolu-7oo4eu

https://wolfram.com/xid/0b0lajyqolu-2syd88

Phase differences of the signals do not affect the computed spectral distance:

https://wolfram.com/xid/0b0lajyqolu-vhk7i

https://wolfram.com/xid/0b0lajyqolu-4uatgs

By default, any distance measure uses the most suitable audio feature:

https://wolfram.com/xid/0b0lajyqolu-kup5d6

Most distances use "AudioData" as the default feature:

https://wolfram.com/xid/0b0lajyqolu-88q0zt

With WarpingDistance, the "MFCC" feature is used by default:

https://wolfram.com/xid/0b0lajyqolu-ft8ocp


https://wolfram.com/xid/0b0lajyqolu-236u


https://wolfram.com/xid/0b0lajyqolu-68k5dr

All features other than "AudioData" are computed from the signal's short-time Fourier transform:

https://wolfram.com/xid/0b0lajyqolu-rc4ozn

Masking (4)
If two signals have different lengths, the longer is trimmed to the shorter duration:

https://wolfram.com/xid/0b0lajyqolu-g85gr5

https://wolfram.com/xid/0b0lajyqolu-zg1o6w


To compare the full length of the signals, use Masking->All:

https://wolfram.com/xid/0b0lajyqolu-4uub7n

Use the Masking option to compare a specific interval of two audio objects:

https://wolfram.com/xid/0b0lajyqolu-jvjbdb

https://wolfram.com/xid/0b0lajyqolu-76lcgy

As long as the duration of the intervals is the same, they can be chosen from different times:

https://wolfram.com/xid/0b0lajyqolu-bnkgyj


https://wolfram.com/xid/0b0lajyqolu-tqyuq0

https://wolfram.com/xid/0b0lajyqolu-v7xtru

Use MaskingAll to compare the full length of the signals:

https://wolfram.com/xid/0b0lajyqolu-tsnjdl

https://wolfram.com/xid/0b0lajyqolu-3zgtmb

PartitionGranularity (2)
Use the PartitionGranularity option to control the computation of the features:

https://wolfram.com/xid/0b0lajyqolu-rss7l3

https://wolfram.com/xid/0b0lajyqolu-ib8kwo


https://wolfram.com/xid/0b0lajyqolu-3c6y7a

If the selected feature is "AudioData", the PartitionGranularity option is ignored:

https://wolfram.com/xid/0b0lajyqolu-x0hejk

https://wolfram.com/xid/0b0lajyqolu-yg68z0


https://wolfram.com/xid/0b0lajyqolu-0471at

SampleRate (1)
Wolfram Research (2018), AudioDistance, Wolfram Language function, https://reference.wolfram.com/language/ref/AudioDistance.html (updated 2024).
Text
Wolfram Research (2018), AudioDistance, Wolfram Language function, https://reference.wolfram.com/language/ref/AudioDistance.html (updated 2024).
Wolfram Research (2018), AudioDistance, Wolfram Language function, https://reference.wolfram.com/language/ref/AudioDistance.html (updated 2024).
CMS
Wolfram Language. 2018. "AudioDistance." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2024. https://reference.wolfram.com/language/ref/AudioDistance.html.
Wolfram Language. 2018. "AudioDistance." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2024. https://reference.wolfram.com/language/ref/AudioDistance.html.
APA
Wolfram Language. (2018). AudioDistance. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/AudioDistance.html
Wolfram Language. (2018). AudioDistance. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/AudioDistance.html
BibTeX
@misc{reference.wolfram_2025_audiodistance, author="Wolfram Research", title="{AudioDistance}", year="2024", howpublished="\url{https://reference.wolfram.com/language/ref/AudioDistance.html}", note=[Accessed: 09-July-2025
]}
BibLaTeX
@online{reference.wolfram_2025_audiodistance, organization={Wolfram Research}, title={AudioDistance}, year={2024}, url={https://reference.wolfram.com/language/ref/AudioDistance.html}, note=[Accessed: 09-July-2025
]}