← all works
A binaural heterophasic adaptive beamformer and its deep learning assisted implementation
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.
The three-model screen
all 1,000 screened works →All three models called this out of scope.
stratum: aff_core · design weight: 5595.24 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: empirical
about Canada: no
confidence: high
Signal processing paper on a binaural adaptive beamformer with deep learning implementation.
GPT-5.6 (high)OUT
genre: empirical
about Canada: no
confidence: high
It proposes a beamformer for speech and audio processing, not a method for conducting research.
Grok 4.5OUT
genre: empirical
about Canada: no
confidence: high
Title-only signal processing paper on binaural beamforming; domain engineering.
Abstract
No abstract. This is not a gap in this database — OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
The record
- Venue
- Pattern Recognition Letters
- Topic
- Speech and Audio Processing
- Field
- Computer Science
- Canadian institutions
- Institut National de la Recherche ScientifiqueUniversité du Québec à Montréal
- Funders
- National Key Research and Development Program of ChinaNorthwestern Polytechnical UniversityNational Natural Science Foundation of China
- Keywords
- MonauralBinaural recordingBeamformingComputer scienceAdaptive beamformerSpeech recognitionIntelligibility (philosophy)ReverberationNoise (video)AcousticsArtificial intelligenceTelecommunications
- Has abstract in OpenAlex
- no