CORDIS
EU research results

CORDIS

English EN

Intelligent systems' Holistic Evolving Analysis of Real-life Universal speaker characteristics

Objective

"Recently, automatic speech and speaker recognition has matured to the degree that it entered the daily lives of thousands of Europe's citizens, e.g., on their smart phones or in call services. During the next years, speech processing technology will move to a new level of social awareness to make interaction more intuitive, speech retrieval more efficient, and lend additional competence to computer-mediated communication and speech-analysis services in the commercial, health, security, and further sectors. To reach this goal, rich speaker traits and states such as age, height, personality and physical and mental state as carried by the tone of the voice and the spoken words must be reliably identified by machines. In the iHEARu project, ground-breaking methodology including novel techniques for multi-task and semi-supervised learning will deliver for the first time intelligent holistic and evolving analysis in real-life condition of universal speaker characteristics which have been considered only in isolation so far. Today's sparseness of annotated realistic speech data will be overcome by large-scale speech and meta-data mining from public sources such as social media, crowd-sourcing for labelling and quality control, and shared semi-automatic annotation. All stages from pre-processing and feature extraction, to the statistical modelling will evolve in ""life-long learning"" according to new data, by utilising feedback, deep, and evolutionary learning methods. Human-in-the-loop system validation and novel perception studies will analyse the self-organising systems and the relation of automatic signal processing to human interpretation in a previously unseen variety of speaker classification tasks. The project's work plan gives the unique opportunity to transfer current world-leading expertise in this field into a new de-facto standard of speaker characterisation methods and open-source tools ready for tomorrow's challenge of socially aware speech analysis."
Leaflet | Map data © OpenStreetMap contributors, Credit: EC-GISCO, © EuroGeographics for the administrative boundaries

Principal Investigator

Bjoern Wolfgang Schuller (Prof.)

Host institution

UNIVERSITAT PASSAU

Address

Innstrasse 41
94032 Passau

Germany

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 1 244 766,90

Principal Investigator

Bjoern Wolfgang Schuller (Prof.)

Administrative Contact

Sabine Wiendl (Ms.)

Beneficiaries (2)

Sort alphabetically

Sort by EU Contribution

Expand all

UNIVERSITAT PASSAU

Germany

EU Contribution

€ 1 244 766,90

TECHNISCHE UNIVERSITAET MUENCHEN

Germany

EU Contribution

€ 253 433,10

Project information

Grant agreement ID: 338164

Status

Closed project

  • Start date

    1 January 2014

  • End date

    31 December 2018

Funded under:

FP7-IDEAS-ERC

  • Overall budget:

    € 1 498 200

  • EU contribution

    € 1 498 200

Hosted by:

UNIVERSITAT PASSAU

Germany