Publication: Speaker Identification for Swiss German with Spectral and Rhythm Features
Speaker Identification for Swiss German with Spectral and Rhythm Features
Date
Date
Date
Citations
Lykartsis, A., Weinzierl, S., & Dellwo, V. (2017, June). Speaker Identification for Swiss German with Spectral and Rhythm Features. 2017 AES International Conference on Semantic Audio. 2017 AES International Conference on Semantic Audio (June 2017), Erlangen. https://doi.org/10.17743/aesconf.2017.978-1-942220-15-2
Abstract
Abstract
Abstract
We present results of speech rhythm analysis for automatic speaker identification. We expand previous experiments using similar methods for language identification. Features describing the rhythmic properties of salient changes in signal components are extracted and used in an speaker identification task to determine to which extent they are descriptive of speaker variability. We also test the performance of state-of-the-art but simple-to-extract frame-based features. The paper focus is the evaluation on one corpus (swiss german, TEVO
Metrics
Additional indexing
Creators (Authors)
- Lykartsis, Athanasios
- Weinzierl, Stefan
Event Title
Event Title
Event Title
Event Location
Event Location
Event Location
Event Start Date
Event Start Date
Event Start Date
Event End Date
Event End Date
Event End Date
Item Type
Item Type
Item Type
Dewey Decimal Classifikation
Dewey Decimal Classifikation
Dewey Decimal Classifikation
Language
Language
Language
Date available
Date available
Date available
ISBN or e-ISBN
ISBN or e-ISBN
ISBN or e-ISBN
OA Status
OA Status
OA Status
Free Access at
Free Access at
Free Access at
Publisher DOI
Funder name
Funder name
Funder name
Project Title
Project Title
Project Title
Metrics
Citations
Lykartsis, A., Weinzierl, S., & Dellwo, V. (2017, June). Speaker Identification for Swiss German with Spectral and Rhythm Features. 2017 AES International Conference on Semantic Audio. 2017 AES International Conference on Semantic Audio (June 2017), Erlangen. https://doi.org/10.17743/aesconf.2017.978-1-942220-15-2
