Hands-free control by voice and eye tracking

With its expertise in audio-signal conditioning and advanced voice-control technology, Philips Applied Technologies is working with medical specialists to develop breakthrough solutions for hands-free control of medical equipment in a sterile environment. 

Hands-free control by voice and eye tracking- Philips Applied Technologies

Our contributions

   
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Audio-signal conditioning

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Adaptive beam-forming technology

- Speech recognition
- Digital noise reduction
- Text-to-speech synthesis

Voice-control systems are set to revolutionize diagnostic and interventional procedures by allowing clinicians to interact and control medical equipment via speech even from several meters away. Clinical trials of such systems are already proving highly successful by providing clinicians with a convenient, reliable and accurate means of hands-free control that allows them greater freedom to concentrate on their patients.  

 

Audio-signal conditioning

The use of headsets or clip-ons to communicate with the equipment, however, is inconvenient as it risks compromising the sterile conditions. While the use of ‘distant-talk’ microphones overcomes this problem, they risk picking up other signals such as background noise, conversations and reverberation, all of which degrade the audio quality of the voice commands, often to the level where they can no longer be reliably processed by a speech-recognizer. Drawing on its world-class expertise in audio-signal conditioning, Philips Applied Technologies has addressed this issue by developing a range of audio preconditioning solutions to maintain the high quality of the signal path from the speaker to the microphones.  

 

Adaptive beam-forming technology

The voice-control system we developed incorporates sophisticated adaptive beam-forming technology that uses an array of microphones to locate and track the person speaking. Once the speaker has been identified, digital noise reduction algorithms filter out background and extraneous speech and noise, enabling the system to ‘lock on’ to the speaker, thus greatly improving the performance of the voice recognizer. The system is triggered to lock on to the speaker by means of a spoken wake-up call, after which it is capable of following the speaker over the limited distance necessary to perform the clinical procedure. Once locked on, the system enhances the user’s voice commands and eliminates background noise and other people’s voices, thus greatly improving the performance of the voice recognizer. The head-tracking system combined with the eye-tracking system allows the orientation of the head to be measured.  

 

An extra level of tracking reliability is provided by supplementing the beam-forming technology with video tracking. We are currently conducting feasibility studies on a new face-identification algorithm developed by Philips Research.  

 

Hands-free control by voice and eye tracking- Philips Applied TechnologiesTo allow natural communication via the voice-control system, between for example a surgeon and a patient or other member of the clinical staff, Philips Applied Technologies has also introduced techniques to allow full duplex communication. These include a proprietary acoustic echo cancellation technique for suppressing acoustic feedback or ringing. This was initially developed by Philips for the mobile-phone and conference phone markets and has been optimized by Philips Applied Technologies for use in voice control.  

 

Text-to-speech

A sophisticated text-to-speech synthesizer, we developed in close cooperation with Philips Research, is also being incorporated into the voice-control system. This vocalizes selected on-screen text to enable the clinician to receive prompts and other information without the need to look at the monitor screen. The synthesizer is characterized by high flexibility – generating naturally-sounding speech in a variety of voices, accents and moods, and by very low implementation complexity – running not only on PCs but also on telephones and other equipment using relatively low-cost (e.g. ARM 7) processors.


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