Name
Abstract | ||
|---|---|---|
We present a new anthropometry-based method to personalize Head-Related Transfer Functions (HRTFs) using manifold learning in both azimuth and elevation angles with a single nonlinear regression model. The core element of our approach is a domain-specific nonlinear dimensionality reduction technique, denominated Isomap, over the intraconic component of HRTFs resulting from a spectral decomposition. HRTF intraconic components encode the most important cues for HRTF individualization, leaving out subject-independent cues. First, we modify the graph construction procedure of Isomap to integrate relevant prior knowledge of spatial audio into a single manifold for all subjects by exploiting the existing correlations among HRTFs across individuals, directions, and ears. Then, with the aim of preserving the multifactor nature of HRTFs (i.e. subject, direction and frequency), we train a single artificial neural network to predict low-dimensional HRTFs from anthropometric features. Finally, we reconstruct the HRTF from its estimated low-dimensional version using a neighborhood-based reconstruction approach. Our findings show that introducing prior knowledge in Isomap’s manifold is a powerful way to capture the underlying factors of spatial hearing. Our experiments show, with p-values less than 0.05, that our approach outperforms using, either a PCA linear reduction, or the full HTRF, in its intermediate stages. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TASLP.2016.2517565 | IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP) |
Keywords | Field | DocType |
Manifold Learning,Spatial Audio,Virtual Auditory Displays | Speech processing,Computer science,Artificial intelligence,Artificial neural network,Nonlinear dimensionality reduction,Manifold,Computer vision,Pattern recognition,Matrix decomposition,Speech recognition,Transfer function,Principal component analysis,Isomap | Journal |
Volume | Issue | ISSN |
PP | 99 | 2329-9290 |
Citations | PageRank | References |
3 | 0.41 | 19 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Felipe Grijalva | 1 | 19 | 2.31 |
| Luiz Martini | 2 | 14 | 1.87 |
| Dinei Florêncio | 3 | 162 | 13.09 |
| Siome Goldenstein | 4 | 618 | 47.43 |