A Scalable Algorithm for Physically Motivated and Sparse Approximation of Room Impulse Responses With Orthonormal Basis Functions
- Submitting institution
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The University of Surrey
- Unit of assessment
- 33 - Music, Drama, Dance, Performing Arts, Film and Screen Studies
- Output identifier
- 9023648_4
- Type
- D - Journal article
- DOI
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10.1109/TASLP.2017.2700940
- Title of journal
- IEEE/ACM Transactions on Audio, Speech, and Language Processing
- Article number
- -
- First page
- 1547
- Volume
- 25
- Issue
- 7
- ISSN
- 2329-9290
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- 12 - Engineering
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
-
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Factual information about significance: The significance of this paper comes from its new insight into the relationship between OBFs and modal decomposition of room acoustics, and the novel algorithm it develops to fit parameters of OBF room acoustics models. This allows the generation of scalable models that achieve greater accuracy in room impulse response (RIR) prediction than the state of the art, with greater high-order stability. This has potential to improve the performance of algorithms and systems for echo/feedback cancellation (e.g. video conferencing), room equalization (e.g. consumer audio system tuning) and dereverberation (e.g. speech recognition), many of which rely on RIR estimation.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -