Real-time wind buffet noise detection
The probability of speech being present in a microphone signal (112) subject to wind buffet noise (eg. in a vehicle) is estimated by starting a state classifier 200 in an assumed no buffeting, no speech state and transitioning to a buffet noise, no speech state when the difference between the averag...
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| creator | Matthew R Kirsch |
| description | The probability of speech being present in a microphone signal (112) subject to wind buffet noise (eg. in a vehicle) is estimated by starting a state classifier 200 in an assumed no buffeting, no speech state and transitioning to a buffet noise, no speech state when the difference between the average speech presence probabilities in two frequency bands (lower and higher) exceeds a threshold. When this threshold is no longer exceeded, the state is further transitioned to speech + buffet, speech without buffet or no speech no buffet depending on the difference between short-term low frequency energy and the long-term energy floor. |
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When this threshold is no longer exceeded, the state is further transitioned to speech + buffet, speech without buffet or no speech no buffet depending on the difference between short-term low frequency energy and the long-term energy floor.</description><language>eng</language><subject>ACOUSTICS ; MUSICAL INSTRUMENTS ; PHYSICS ; SPEECH ANALYSIS OR SYNTHESIS ; SPEECH OR AUDIO CODING OR DECODING ; SPEECH OR VOICE PROCESSING ; SPEECH RECOGNITION</subject><creationdate>2018</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20180711&DB=EPODOC&CC=GB&NR=2558164A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20180711&DB=EPODOC&CC=GB&NR=2558164A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Matthew R Kirsch</creatorcontrib><title>Real-time wind buffet noise detection</title><description>The probability of speech being present in a microphone signal (112) subject to wind buffet noise (eg. in a vehicle) is estimated by starting a state classifier 200 in an assumed no buffeting, no speech state and transitioning to a buffet noise, no speech state when the difference between the average speech presence probabilities in two frequency bands (lower and higher) exceeds a threshold. 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| subjects | ACOUSTICS MUSICAL INSTRUMENTS PHYSICS SPEECH ANALYSIS OR SYNTHESIS SPEECH OR AUDIO CODING OR DECODING SPEECH OR VOICE PROCESSING SPEECH RECOGNITION |
| title | Real-time wind buffet noise detection |
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