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PhD Position in Explainable and Frugal Audio Scene Description
Il y a 2 mois
We are seeking a highly motivated PhD researcher to join our team at INRIA, working on a project focused on explainable and frugal audio scene description. The successful candidate will have the opportunity to contribute to the development of innovative audio processing techniques and work closely with our team of experts in the field.
Research ObjectivesThe main objective of this PhD project is to propose a general framework for processing audio recordings for intelligence purposes. This involves defining a high-level application that adapts to the needs of end users, favoring the presentation of a recording in the form of a summary report to highlight its salient points.
Key Responsibilities- Develop and evaluate deep learning systems for audio scene description
- Define a new task, corpus, and evaluation protocol for audio scene analysis
- Work on the alignment between self-supervised representations of the speech signal and large language models
- Train a weakly supervised system for audio scene description
- Evaluate the performance of the system
To be eligible for this position, you should have a Master's degree in computer science, mathematics, or phonetics. You should also have a strong interest in applied research and experience with deep learning toolkits such as PyTorch or Keras. Additionally, you should have knowledge of signal processing and machine learning, as well as experience with speech processing and open-source toolkits such as Kaldi or SpeechBrain.
BenefitsWe offer a competitive salary, subsidized meals, partial reimbursement of public transport costs, and a range of benefits including annual leave, RTT (statutory reduction in working hours), and the possibility of teleworking and flexible organization of working hours. Our team also offers a dynamic and supportive work environment, with opportunities for professional development and growth.
