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WOZ acoustic data collection for interactive TV

WOZ acoustic data collection for interactive TV. A. Brutti*, L. Cristoforetti* , W. Kellermann+, L. Marquardt+, M. Omologo* * Fondazione Bruno Kessler (FBK) - irst Via Sommarive 18, 38050 Povo (TN), ITALY

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WOZ acoustic data collection for interactive TV

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  1. WOZ acoustic data collection for interactive TV A. Brutti*, L. Cristoforetti*, W. Kellermann+, L. Marquardt+, M. Omologo* * Fondazione Bruno Kessler (FBK) - irst Via Sommarive 18, 38050 Povo (TN), ITALY + Multimedia Communications and Signal Processing, University of Erlangen-Nuremberg (FAU) Cauerstr. 7, 91058 Erlangen, GERMANY LREC 2008 – Marrakech, 28-30/05/08

  2. Robustness in a real reverberant environment Other speakers? Noise sources? The DICIT EU projectDistant-talking Interfaces for Control of Interactive TV What is the outputfrom each loudspeaker? How is it at each microphone? Where is she? What is her head orientation? When did she speak? Who is she? What does she say?

  3. The DICIT Project STREP Project – FP6 Strategic objective: 2.5.7 – Multimodal Interfaces Duration: October 2006 – September 2009

  4. What is a Wizard of Oz (WOZ) experiment? • A subject is requested to complete specific tasks using an artificial system • The user is told that the system is fully functional and should try to use it in a intuitively way • The system is operated by a person (wizard) not visible to the subject • The wizard can react in a more comprehensive way and can create particular situations BUT

  5. Why a WOZ data collection? • We needed to collect an acoustic database for testing pre-processing algorithms: • acoustic scene analysis • speaker ID and verification • echo cancelation • blind source separation • beamforming • speaker localization and tracking • distant automatic speech recognition • With a WOZ, realistic scenarios can be simulated at a preliminary stage, allowing for repeatable experiments • There is no need to have a full-working system in order to collect real data • Naïve users, do not have the same behavior as expert users, they use the system in a realistic way

  6. The DICIT WOZ • Experiments were conducted in the laboratories at FBK and FAU • A room was used as living room with TV, loudspeakers and seatsAn adjacent room was used by the wizard and the simulation system, not visible from the users • Users watched the TV and had to interact with it by voice and remote control, to change channels and to retrieve information from the teletext pages • At some point, they had to move around and speak with the system

  7. Strategy for the recordings • Four users sit in the room, but one of them was the co-wizard, that ensured the regularity of the experiment and produced some acoustic events • Users were recorded by close talk and far microphones • Interactions will be recorded by 3 fixed cameras that allow the automatic tracking of users movements • Recordings were done on Italian/German/English groups

  8. The FBK experimental room A harmonic 15-electret-microphone array was developed on purpose and located over the TV

  9. Clip from a recorded session

  10. WOZ preparation • 12 video clips and 100 teletext pages were recorded from real TV, everything was available in 3 languages • Stereo audio channels were extracted and decorrelated (by FAU) for the echo canceller and clips were recreated to fit the simulation • The system was controlled by a PC running Elektrobit EB GUIDE Studio simulator tool • A remote control infrared receiver was integrated into the system and enabled the users to use a real remote control to pilot the TV

  11. Recorded sessions • FBK and FAU recorded different sessions using a similar setup, in different languages • Each user interaction lasted about 10 minutes, in total 360 minutes of recordings • 24 or 26 synchronous channels were recorded at 48kHz with 16-bit precision + 64 channels from the MarkIII array at 44.1kHz and 24 bits

  12. Data annotation • The 6 Italian sessions have been manually transcribed and segmented at word level, using Transcriber • An automatic segmentation was obtained with a tool based on energy of the close-talk signals, then adjusted when necessary • A stereo file was created, with two channels for close-talk and environment sounds to ease the annotation process • Annotation comprises the speaker ID, the transcription of uttered sentence and any noise included in the acoustic event list • Specific labels for acoustic events have been introduced, following a defined guideline • Video data has been used to derive 3D coordinates for the head of the speaker and reference files were created with a frame rate of 5 labels per second

  13. Data exploitation / testing • Data have been used for a preliminary evaluation of some FBK algorithms: • localization techniques, precision is around 30 cm • 682 + 108 audio segments have been used for the acoustic event classification system, 92% of accuracy • data have been used to test the speaker verification and identification system, but close-talk is still better that beamformed signal • Room impulse response measurements have been carried out at both sites, in different positions. They are useful for i.e. speech contamination purposes

  14. Transcriber session

  15. Conclusions • This collection of data has been the first of its kind and is of significant benefit to acoustic front-end algorithms and dialogue strategies • 36 naïve persons have been recorded, leading to 360 minutes of signals, on 24-26 different channels recorded in a synchronous way (125 GB of data) • Users enjoyed the system and tolerated some recognition errors, they preferred voice modality over remote control interaction

  16. Current status of the project • The project is in the second year • We just finished to integrate the first prototype • Ready to start the evaluation of the prototype • More information and demo clips can be found at http://dicit.fbk.eu

  17. Thank You!

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