Name
Title | ||
|---|---|---|
Performance analysis of smart audio pre-processing for noise-robust text-independent speaker recognition. |
Abstract | ||
|---|---|---|
This paper presents a study on the performance of a speaker identification system in challenging environmental conditions, such as in the presence of noise and at a distance. We propose a robust speaker recognition algorithm, which includes a smart pre-processing method based on Voice Activity Detection (VAD), capable to boost the system accuracy. Results show that our solution is able to improve the correct classification rate of traditional speaker recognition systems, even in case of distant audio acquisition and noisy environments. |
Year | Venue | Field |
|---|---|---|
2017 | GlobalSIP | Speaker identification,Voice activity detection,Computer science,Support vector machine,Speech recognition,Speaker recognition,Classification rate |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Igor Bisio | 1 | 395 | 43.23 |
| Chiara Garibotto | 2 | 2 | 4.08 |
| Andrea Sciarrone | 3 | 100 | 16.60 |
| Fabio Lavagetto | 4 | 216 | 35.19 |