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Telematics\ Infotainment Solutions
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One Alternative
Wind noise reduction
Anti-echo boom
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Improving Voice Quality
Mic positioned a long way away from
users mouth
High power speaker
positioned close to mic
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Headsets Have Come a Long Way
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Noise Considerations
ASRImpacts:• Dialog Design• Grammars• Discreet / Continuous• Word / Phrase
Non-Impacts:• Languages• Processing Reqts• Memory
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Hands Free Considerations
Acoustic Echo Cancellation
• Effect on far end speech recognition• Echo Return Loss• Capability to handle speaker distortion• Ability to adapt to changing Acoustic environment• Varied Acoustic Coupling• Beating with other echo cancellers • Double Talk• Barge In
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Hands Free Considerations
Noise Suppression
• SNR improvement• Distortion• Interaction with vocoder• Voice Quality• Time to Converge• Noise types• Ability to adapt to acoustic
environmental factors• Automatic Gain Control• Microphone Interaction
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Algorithms Must Mimic Human Processing
1) Sound waves cause the ear drum to vibrate in the middle ear
2) Vibration in the middle ear is translated into fluid motion in the cochlea
3) The hair cells in the inner ear vibrate in a unique pattern corresponding to the frequency spectrum characteristic of the incoming sound
4) The motion of each hair is converted to electrical pulses which are transmitted to the brain
5) The brain separates speech from other sound components for analysis
How humans hear How ASR engines hear
A/D
Component Extraction
Voice Extraction
1) Sound pressure is converted to electrical waves by the microphone
2) Electrical waves are converted to a digital representation (numbers) by the analog to digital converter
3) The numbers are processed into frequency components which are analogous to the output of the cochlea
4) The independent frequency components are subjected to temporal analysis and correlated to distinguish speech from noise
5) Speech is extracted from the noisy signal for subsequent processing
Independent Component
Analysis
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Algorithms Enable Superior Noise Suppression
Component Extraction
Voice Component
Analysis
Voice Extraction Synthesis
Voice Extraction
The voice extractor modifies each frequency component according to the voice and noise model. The Voice Extractor takes advantage of psychoacoustics principals to minimize noise floor artifacts and perceived voice distortion
Voice Analysis
The voice analysis block considers temporal and correlative properties of speech and noise to develop a predictive model of the speech components
Component Extraction
The audio signal is converted to the frequency domain and partitioned according to critical voice components
Synthesis
The extracted voice components are recombined and converted into the time domain
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Subband Adaptive
Filter
F3
Residual Echo
Canceller
Programmable Non-Linear Processing
Near End
Tx
RxD/A
A/D
F3 Residual Echo Cancellation
Uses proprietary estimation methods to improve Echo Return Loss introducing speech degradation
Subband Adaptive Filter
Uses CSR Detroit’s Proprietary Restored Estimator Reutilization method to quickly model the linear transfer function between the reference signal and the microphone. Allows for rapid and more accurate plant estimation
Algorithms create a new approach to Acoustic Echo Cancellation
Environment Restoration
Algorithms Enable Natural Conversation
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One Alternative
Wind noise reduction
Anti-echo boom
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But the real mass market is still in the future….
What will make headsets attractive to everyone for the auto?
Work with any phone
Batteries last 8 hours (longer for stereo)
Looks nice
Great sound quality (at least as good as the phone)
Natural to use
Not too expensive
Noise Suppression
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DSPs enhance Bluetooth
Bluetooth Multimedia devices were launched more than 2 years ago and has more than 10MU
Next step: More powerful Bluetooth Multimedia; realising the vision
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Name announcing – improving safety
John Smith calling
Eyes stay on the road
With name announcing Bluetooth headsets can contribute further to road safety
