audio-detect | Experimenting with Python and librosa to do Audio Event | Audio Utils library

by craigfrancis Python Version: Current License: BSD-3-Clause

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | audio-detect Summary

audio-detect is a Python library typically used in Audio, Audio Utils applications. audio-detect has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Identify when a sound effect is played multiple times in an audio file (e.g. an MP3). Otherwise known as Audio Event Detection.

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audio-detect has a low active ecosystem.

It has 19 star(s) with 2 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 4 have been closed. On average issues are closed in 1 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of audio-detect is current.

Quality

audio-detect has 0 bugs and 0 code smells.

Security

audio-detect has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

audio-detect code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

audio-detect is licensed under the BSD-3-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

audio-detect releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 808 lines of code, 2 functions and 10 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed audio-detect and discovered the below as its top functions. This is intended to give you an instant insight into audio-detect implemented functionality, and help decide if they suit your requirements.

Compute the Fourier Transform for a TimeSeries .
Calculate audio data from an audio file .

Get all kandi verified functions for this library.

audio-detect Key Features

No Key Features are available at this moment for audio-detect.

audio-detect Examples and Code Snippets

No Code Snippets are available at this moment for audio-detect.

Community Discussions

Trending Discussions on audio-detect

find the timestamp of a sound sample of an mp3 with linux or python

QUESTION

find the timestamp of a sound sample of an mp3 with linux or python

Asked 2020-Jun-30 at 02:32

I am slowly working on a project which where it would be very useful if the computer could find where in an mp3 file a certain sample occurs. I would restrict this problem to meaning a fairly exact snippet of the audio, not just for example the chorus in a song on a different recording by the same band where it would become more some kind of machine learning problem. Am thinking if it has no noise added and comes from the same file, it should somehow be possible to locate the time at which it occurs without machine learning, just like grep can find the lines in a textfile where a word occurs.

In case you don't have an mp3 lying around, can set up the problem with some music available on the net which is in the public domain, so nobody complains:

...

ANSWER

Answered 2020-Jun-25 at 15:55

MP3 is an interesting format. The underlying data is stored in 'Frames', each 0.026 seconds long. Each frame is a Fast Fourier transform of the sound wave, encoded with varying degrees of quality depending on the size and bitrate, etc.. In your case, are you certain that the mp3s have matching bitrates? If they do, a relatively straightforward grep-style approach should be possible, given that you select on Frame boundaries. However, it is entirely likely and possible that this is not the case.

For a true solution, you need to process the mp3 file to some degree, to abstract away the encoding. However, there is no guarantee that the resulting wave match even for matching sounds, as bitrates and possibly frame alignment may differ. This small degree of chance makes it much harder.

I will give you my approach to this problem, but it is worth noting that this is not the perfect way to do things, just my best swing. Even though its the same file, there's no guarantee that frame boundaries are aligned, so I think you need to take a very wave-oriented approach, rather than a data-oriented one.

First, convert the mp3s to waves. I know that it'd be great to leave it compressed, but again I think wave-oriented is our only hope. Then, use a high-pass filter to try to remove any artifacts of audio compression that would differ between samples. Once you have two waveforms, it should be relatively straight forward to find the wavelet in the wave. You can iterate through possible starting positions and subtract the waves. When you get close to zero, you know you're close.

Source https://stackoverflow.com/questions/62524604

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install audio-detect

You can download it from GitHub.
You can use audio-detect like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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