Blog Archives

Welcoming new Lecturer: Bhusan Chettri

We’re pleased to welcome new Lecturer Bhusan Chettri to our group! Bhusan started a full-time role this month as Lecturer in Data Analytics. He says: “I completed my Ph.D. degree from QMUL in August 2020 under the supervision of Dr.

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Suggested reading: getting going with deep learning

Based on a conversation we had in the Machine Listening Lab last week, here are some blogs and other things you can read when you’re – say – a new PhD student who wants to get started with applying/understanding deep

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Turing Fellowship success for the Machine Listening Lab

Two of the Machine Listening Lab’s lead academics, Dan Stowell and Emmanouil Benetos, have been awarded Turing Fellowships. The Alan Turing Institute (ATI) is a new UK national institute for data science and artificial intelligence (founded in 2015). Our university

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Machine Listening Lab symposium 2018

On 29th March 2018 we held a Machine Listening Lab symposium to gather together people across the university who are doing work in machine listening. Katerina Kosta (Jukedeck) The programme of talks included: Emmanouil Benetos (QMUL): Machine listening for music

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Machine Listening Lab 2017: The year in review

2017 has been a fascinating year for the Machine Listening Lab. Here are the headlines! Grant success and projects: Rob Lachlan, along with David Clayton and Dan Stowell, were awarded a BBSRC grant for a £659,000 project to study “Machine

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“Machine Learning Methods in Bioacoustics” – Call for Abstracts, IBAC 2017

DEADLINE EXTENDED: 30th May 2017 We are pleased to announce a symposium on “Machine Learning Methods in Bioacoustics”, to be held as part of the 2017 International Bioacoustics Congress (Haridwar, India, 8-13 October 2017). To submit an abstract, see: http://www.ibac2017india.com/abstracts/

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Bird Audio Detection: tips on building robust detectors

Recently we launched the Bird Audio Detection Challenge, providing new datasets and a contest to improve the state of the art in general-purpose bird detection in audio. In our previous post we talked about the problem of generalisation, demonstrating that

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Bird Audio Detection: baseline tests – and the problem of generalisation

Recently we launched the Bird Audio Detection Challenge, providing new datasets and a contest to improve the state of the art in general-purpose bird detection in audio. So what is the state of the art? For a thorough answer, you

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Announcing the Bird Audio Detection Challenge

On behalf of the organising committee and the IEEE AASP TC,* we invite you to consider the first Bird Audio Detection Challenge: http://machine-listening.eecs.qmul.ac.uk/bird-audio-detection-challenge/ Detecting bird sounds in audio is an important basic task in various applications. The current generation of

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Three Awards at ISMIR 2016!

Researchers at the Machine Listening Lab at QMUL won three of five awards at the 2016 International Symposium on Music Information Retrieval! “Best Student Paper” was awarded to Maria Panteli, Emmanouil Benetos and Simon Dixon: Learning a Feature Space for

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