Name
Abstract | ||
|---|---|---|
An analysis of intelligibility measurements of ideal binary masked speech in noise for a group of normal hearing listeners is presented. In the proposed model, speech cues in the processed mixtures are encoded by two information channels: a noisy speech channel and a vocoded noise channel. Results indicate that the former dominates for dense binary mask patterns, and the latter for sparse binary mask patterns, as controlled by a local SNR criterion used for forming the ideal mask. Moreover, speech cues from the target part of the processed mixture may be better utilized by the listeners as a result of the ideal binary masking. Finally, the analysis is extended to show a good qualitative agreement with several previous studies of intelligibility of ideal binary masked noisy speech. |
Year | Venue | Keywords |
|---|---|---|
2010 | European Signal Processing Conference | noise measurement,speech,time frequency analysis,signal to noise ratio,predictive models,speech processing |
Field | DocType | ISSN |
Masking (art),Pattern recognition,Computer science,Communication channel,Speech recognition,Artificial intelligence,Intelligibility (communication),Binary number | Conference | 2219-5491 |
Citations | PageRank | References |
2 | 0.52 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ulrik Kjems | 1 | 150 | 40.43 |
| Michael Syskind Pedersen | 2 | 81 | 11.33 |
| Jesper Bünsow Boldt | 3 | 9 | 4.09 |
| Thomas Lunner | 4 | 3 | 2.59 |
| DeLiang Wang | 5 | 49 | 2.71 |