[aubio-user] Offset detection

[Paul Brossier]

Hi Lukasz and all,

On 10/01/2014 03:08, Lukasz Tracewski wrote:
>
>> I assume you mean free and open source software, not freeware?
> You are right of course; somehow 'freeware' got associated in my
> mind with open software, though naturally they have little in common.
> I only just begun my adventure with open source; here is my
> project's page: https://github.com/tracek/Ornitokrites It's still
> very immature and under heavy development. Most important part is
> still missing: machine learning.
>
> Your library is one of its crucial ingredients. If things work as
> intended the program will be used for aiding efforts in nature
> conservation (initially kiwi protection). Of course it will properly
> cite and credit all used publications and libraries. Please let me
> know if there are any licensing issues.

no issue at all, I am glad to know aubio can be used to help nature and
kiwis!

>> It would help to have an example of the kind of annotations you
>> want.
> In essence I need to know beginning and end of anything that could
> be a bird call - if this is what you are asking. Examples will
> follow.
>
>
>> You could just use aubiopitch. by setting the confidence and
>> silence thresholds appropriately, you should get 0.00 when the
>> bird is not singing.
> Thanks! I will try that.
>
>
>
>> By the way, I would be very interested to have a small sample of
>> songs and the 'ground-truth' annotations you are looking for.

> Here you will find some examples:
> https://drive.google.com/folderview?id=0B46Cy3WOKgyJb216cHYwSE1yeTA&usp=sharing
>
>
>
Three folders contain respectively: - Original audio recording ...
> and output of my script: - Spectrogram with beginnings and ends of a
> probable audio features(e.g. a bird call) marked by vertical lines.
> Currently the latter are created in a naive fashion: [detected_onset
> - 0.2 second , detected_onset + 0.8 second], giving 1 second-long
> samples. Of course these hard-coded intervals won't do in general. -
> Shorter recording containing only audio features. This one is
> created
	>  by extracting areas marked on a spectrogram and performing noise
> reduction: high-pass filter and spectral subtraction. The latter
> creates so-called musical tones (tin-like sounds) and one of my
> goals is to make it smarter (like "noise removal" in Audacity).
>
> For convenient download I also included a zip file with all three
> folders.
>
> My aim is to identify which recordings contain kiwi calls. By the
> way, if you are interested in how kiwi sounds:
> https://www.kiwisforkiwi.org/about-kiwi/kiwi-facts-characteristics/kiwi-calls/
>
>
>  The site also contains a lot of other great kiwi material :-).
>
>
> Regards, Lucas


ok, excellent, I will look into that!

let me know how everything is going.

Best, Paul


>
>>
>>
>> Regards, Paul
>>
>>>
>>>
>>> Cheers, Lucas
>>>
>>> On 04/01/14, *Paul Brossier * <piem at piem.org> wrote:
>>>> On 04/01/2014 06:00, Lukasz Tracewski wrote:
>>>>> Hi,
>>>>>
>>>>> Aubio has a plethora of great onset detection methods. How
>>>>> about offset detection? I can imagine that running algorithm
>>>>> on reverse-ordered data should provide me with offsets, but
>>>>> maybe there is a smarter approach that I am missing.
>>>>
>>>> Hi Lukasz,
>>>>
>>>> There is no offset detection method in aubio (yet). The onset
>>>> detection functions will sometimes peak during the transient
>>>> sound created by the release of a note, but these peaks are
>>>> expected be small compared to the ones produced by note
>>>> onsets.
>>>>
>>>> So far, offsets times are assumed to be where the level of the
>>>>  signal drops under a given threshold. aubionotes for instance
>>>> uses a simple silence gate to determine the end of notes.
>>>>
>>>> What kind of offsets are you looking at? Do you have a specific
>>>> algorithm in mind?
>>>>
>>>> There is the work of Emmanouil Benetos and Simon Dixon, who
>>>> use a Hidden Markov Model to determine whether a pitch track
>>>> is active or not:
>>>>
>>>> http://www.eecs.qmul.ac.uk/~simond/pub/2011/Benetos-Dixon-ICASSP2011.pdf
>>
>>>>
>>>>
>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>> Best, Paul
>>>>
>>>>
>>>>>
>>>>> Thanks, Lucas
>>>>>
>>>>>
>>>>> _______________________________________________ aubio-user
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>>>>>