29-06-2022: Kimia Nadjahi receives the IP Paris Best Thesis 2022 award
ADASP is proud of its former PhD student Kimia Nadjahi receiving the IP Paris Best Thesis 2022 award! The results will be announced at the IP Paris PhD Gradu... ≥≥
The ADASP group (Audio Data Analysis and Signal Processing, formerly known as the AAO group) is a research group associated to the S²A team, and affiliated with Telecom Paris’ in-house research laboratory: the LTCI.
A significant fraction of our research is performed within national and international collaborative projects, with numerous academic and industrial partners.
ADASP is proud of its former PhD student Kimia Nadjahi receiving the IP Paris Best Thesis 2022 award! The results will be announced at the IP Paris PhD Gradu... ≥≥
Professor Gaël Richard, executive director of Hi! Paris and Professor at Télécom Paris, Institut Polytechnique de Paris, was awarded of an advanced ERC grant... ≥≥
P. Magron presents an overview of his work on sound source separation. ≥≥
Our group is welcoming applications for multiple PhD student, postdoc and research engineer positions in machine listening, MIR and audio/music DSP to start ... ≥≥
The kick-off of our new joint-lab on machine listening: LISTEN took place today. This research initiative sponsored by our partners: Valeo, Bruitparif and Mu... ≥≥
Originally published on the MIP-frontiers website on July 28, 2021. ≥≥
T. Parcollet presents SpeechBrain to ADASP. ≥≥
M. Fuentes talks to ADASP about her research in audio data analysis, between music and sound scene analysis. ≥≥
Our group is hiring a Master intern on the topic “Deep learning for joint detection and tracking of mobile sound sources via a moving microphone array”. ≥≥
R. Serizel talks to ADASP about his experience with the organisation of DCASE task 4. ≥≥
PhD candidate Laure Prétet will defend soon her PhD thesis, entitled “Metric Learning for Video to Music Recommendation”. ≥≥
Karim Ibrahim will defend soon his PhD thesis, entitled “Informed Audio Source Separation with Deep Learning in Limited Data Settings”. ≥≥
Giorgia Cantisani will defend soon her PhD thesis, entitled ““Neuro-steered Music Source Separation”. ≥≥
Kilian Schulze-Forster will defend soon his PhD thesis, entitled “Informed Audio Source Separation with Deep Learning in Limited Data Settings”. ≥≥
Four papers from the team were presented at ISMIR 2021! The 22nd International Society for Music Information Retrieval Conference was held online. ≥≥
A paper from the team has been presented at ICML 2021 as a long talk (among 3 % of all submissions): ≥≥
One paper from the team will be presented at Interspeech 2021. It was accepted for presentation at the session on Neural Networks training techniques for ASR. ≥≥
K. Yoshii presents a unified theory of blind source separation. ≥≥
In this work, we propose to exploit a temporal segmentation provided by the user indicating when each instrument is active, in order to fine-tune a pre-train... ≥≥
Télécom Paris & CentraleSupélec are welcoming applications for a fully-funded PhD fellowship in computational music analysis, audio indexing, and machine... ≥≥
NoPdb is a programmatic (non-interactive) debugger for Python. This means it gives you access to debugger-like superpowers directly from your code. With NoPd... ≥≥