Objective
Audio communication is a major tool for businesses to maintain their competitiveness in the global market. This market is expected to treble by 2020 to $2.145 billion and creates a great demand for novel ideas, such as acoustic pattern recognition technologies. Similarly, the explosion in big data is calling for new data classification methods for improved data indexation and real-time monitoring of the data streams.
We have developed acoustic pattern classification methods that are able to detect and recognise a large number of different types of sounds in various everyday contexts. Current acoustic monitoring solutions are able to detect only a small number of very prominent sound events (e.g. baby crying, doorbell), and are not able to operate in realistic environments, where other interfering sounds and reverberation is present. In real life sound recognition recordings, we have recently advanced the deep neural network state-of-the-art by a large margin.
The advancement of the methods has enabled recognition of new types of sounds in realistic environments, which were considered infeasible just a few years ago, allowing development of novel applications of sound analysis. We’d expect our technology find its way to various applications, such as 1) surveillance of homes and other buildings for threat detection, 2) navigation, interaction and self-awareness of robots as well as interconnected smart devices, and 3) data indexation operations in video management, just to name few.
Within this PoC project, we will prove the efficiency of our technology in real life setting. The goals of the PoC project are to establish the technical feasibility of our idea, implement a commercial prototype of the proposed software and establish its commercialisation potential via various activities.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences software
- natural sciences computer and information sciences data science big data
- natural sciences computer and information sciences artificial intelligence pattern recognition
- natural sciences computer and information sciences artificial intelligence computational intelligence
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-POC - Proof of Concept Grant
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2016-PoC
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
33100 Tampere
Finland
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.