I'm just flying from the International Bioacoustics Congress 2017, held in Haridwar in the north of India. It was a really interesting time. I'm glad that IBAC was successfully brought to India, i.e. to a developing country with a more fragmented bioacoustics community (I think!) than in the west. For me, getting to know some of the Indian countryside, the people, and the food was ace. Let me make a few notes about research themes that were salient to me:
- "The music is not in the notes, but in the silence between" - this Mozart quote which Anshul Thakur used is a lovely byline for his studies - as well as some studies by others - on using the durations of the gaps between units in a birdsong, for the purposes of classification/analysis. Here's who investigated gaps:
- Anshul Thakur howed how he used the gap duration as an auxiliary feature, alongside the more standard acoustic classification, to improve quality.
- Florencia Noriega discussed her own use of gap durations, in which she fitted a Gaussian mixture model to the histogram of log-gap-durations between parrot vocalisation units, and then used this to look for outliers. One use that she suggested was that this could be a good way to look for unusual vocalisation sequences that could be checked out in more detail by further fieldwork.
- (I have to note here, although I didn't present it at IBAC, that I've also been advocating the use of gap durations. The clearest example is in our 2013 paper in JMLR in which we used them to disentangle sequences of bird sounds.)
- Tomoko Mizuhara presented evidence from a perceptual study in zebrafinches, that the duration of the gap preceding a syllable exhibits some role in the perception of syllable identity. The gap before? Why? - Well one connection is that the gap before an event might relate if it's the time the bird takes to breathe in, and thus there's an empirical correlation, whether the bird is using that purely empirically or for some more innate reason.
Machine learning methods in bioacoustics - this is the session that I organised, and I think it went well - I hope people found it useful. I won't go into loads of detail here since I'm mostly making notes about things that are new to me. One notable thing though was Vincent Lostanlen announcing a dataset "BirdVox-70k" (flight calls of birds recorded in the USA, annotated with the time and frequency of occurrence) - I always like it when a dataset that might be useful for bird sound analysis is published under an open licence! No link yet - I think that's to come soon. (They've also done other things such as this neat in-browser audio annotation tool.)
Software platforms for bioacoustics. When I do my research I'm often coding my own Python scripts or suchlike, but that's not a vernacular that most bioacousticians speak. It's tricky to think what the ideal platform for bioacoustics would be, since there are quite some demands to meet: for example ideally it could handle ten seconds of audio as well as one year of audio, yet also provide an interface suitable for non-programmers. A few items on that theme:
- Phil Eichinski (standing in for Paul Roe) presented QUT's Eco-Sounds platform. They've put effort into making it work for big audio data, managing terabytes of audio and optimising whether to analyse the sound proactively or on-demand. The false-colour "long duration spectrograms" developed by Michael Towsey et al are used to visualise long audio recordings. (I'll say a bit more about that below.)
- Yves Bas presented his Tadarida toolbox for detection and classification.
- Ed Baker presented his BioAcoustica platform for archiving and analysing sounds, with a focus on connecting deposits to museum specimens and doing audio query-by-example.
- Anton Gradisek, in our machine-learning session, presented "JSI Sound: a machine learning tool in Orange for classification of diverse biosounds" - this is a kind of "machine-learning as a service" idea.
- Then a few others that might or might not be described as full-blown "platforms":
- Tomas Honaiser wasn't describing a new platform, but his monitoring work - I noted that he was using the existing AMIBIO project to host and analyse his recordings.
- Sandor Zsebok presented his Ficedula matlab toolbox which he's used for segmenting and clustering etc to look at cultural evolution in the Collared flycatcher.
- Julie Elie mentioned her lab's SoundSig Python tools for audio analysis.
- Oh by the way, what infrastructure should these projects be built upon? The QUT platform is built using Ruby, which is great for web developers but strikes me as an odd choice because very few people in bioacoustics or signal processing have even heard of it - so how is the team / the community going to find the people to maintain it in future? (EDIT: here's a blog article with background information that the QUT team wrote in response to this question.) Yves Bas' is C++ and R which makes sense for R users (fairly common in this field). BioAcoustica - not sure if it's open-source but there's an R package that connects to it. --- I'm not an R user, I much prefer Python, because of its good language design, its really wide user base, and its big range of uses, though I recognise that it doesn't have the solid stats base that R does. People will debate the merits of these tools for ever onwards - we're not going to all come down on one decision - but it's a question that I often come back to, how best to build software tools to ensure they're useable and maintainable and solid.
So about those false-colour "long duration spectrograms". I've been advocating this visualisation method ever since I saw Michael Towsey present it (I think at the Ecoacoustics meeting in Paris). Just a couple of months ago I was at a workshop at the University of Sussex and Alice Eldridge and colleagues had been playing around with it too. At IBAC this week, ecologist Liz Znidersic talked really interestingly about how she had used them to detect a cryptic (i.e. hard-to-find) bird species. It shows that the tool helps with "needle in a haystack" problems, including those where you might not have a good idea of what needle you're looking for.
In Liz's case she looked at the long-duration spectrograms manually, to spot calling activity patterns. We could imagine automating this, i.e. using the long-dur spectrogam as a "feature set" to make inferences about diurnal activity. But even without automation it's still really neat.
Anyway back to the thematic listings...
- Trills in bird sounds are fascinating. These rapidly-frequency-modulated sounds are often difficult and energetic to do, and this seems to lead to them being used for specific functions.
- Tereza Petruskova presented a poster of her work on tree pipits, arguing for different roles for the "loud trill" and the "soft trill" in their song.
- Christina Masco spoke about trills in splendid fairywrens (cute-looking birds those!). They can be used as a call but can also be included at the end of a song, which raises the question of why are they getting "co-opted" in this way. Christina argued that the good propagation properties of the trill could be a reason - there was some discussion about differential propagation and the "ranging hypothesis" etc.
- Ole Larsen gave a nice opening talk about signal design for private vs public messages. It was all well-founded, though I quibbled his comment that strongly frequency-modulated sounds would be for "private" communication because if they cross multiple critical bands they might not accumulate enough energy in a "temporal integration window" to trigger detection. This seems intuitively wrong to me (e.g.: sirens!) but I need to find some good literature to work this one through.
- Hybridisation zones are interesting for studying birdsong, since they're zones where two species coexist and individuals of that species might or might not breed with individuals of the other species. For birds, song recognition might play a part in whether this happens. It's quite a "strong" concept of perceptual similarity, to ask the question "Is that song similar enough to breed with?"!
- Alex Kirschel showed evidence from a suboscine (and so not a vocal learner) which in some parts of Africa seems to hybridise and in some parts seems not to - and there could be some interplay with the similarity of the two species' song in that region.
- Irina Marova also talked about hybridisation, in songbirds, but I failed to make a note of what she said!
- Duetting in birdsong was discussed by a few people, including Pedro Diniz and Tomasz Osiejuk. Michal Budka argued that his playback studies with Chubb's cisticola showed they use duet for territory defence and signalling commitment but not for "mate-guarding".
- Oh and before the conference, I was really taken by the duetting song of the grey treepie, a bird we heard up in the Himalayan hills. Check it out if you can!
As usual, my apologies to anyone I've misrepresented. IBAC has long days and lots of short talks (often 15 minutes), so it can all be a bit of a whirlwind! Also of course this is just a terribly partial list.
(PS: from the archives, here's my previous blog about IBAC 2015 in Murnau, Germany.)