Semantic Speech Tagging: Towards Combined Analysis of Speaker Traits

Schuller B, Wöllmer M, Eyben F, Rigoll G, Arsic D. Semantic Speech Tagging: Towards Combined Analysis of Speaker Traits. In: AES Conference: 42nd International Conference: Semantic Audio. Audio Engineering Society; 2011.pp. 2-1:1-9. Available from: https://aes.org/publications/elibrary-page/?id=15947

@inproceedings{Schuller2011_15947,
  author = {Schuller, Björn and Wöllmer, Martin and Eyben, Florian and Rigoll, Gerhard and Arsic, Dejan},
  title = {{Semantic Speech Tagging: Towards Combined Analysis of Speaker Traits}},
  booktitle = {AES Conference: 42nd International Conference: Semantic Audio},
  pages = {2-1:1-9},
  year = {2011},
  month = jul,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=15947}
}

TY  - CPAPER
TI  - Semantic Speech Tagging: Towards Combined Analysis of Speaker Traits
AU  - Schuller, Björn
AU  - Wöllmer, Martin
AU  - Eyben, Florian
AU  - Rigoll, Gerhard
AU  - Arsic, Dejan
T2  - AES Conference: 42nd International Conference: Semantic Audio
SP  - 1
EP  - 9
M1  - Paper 2-1
PY  - 2011
DA  - 2011/07/06
UR  - https://aes.org/publications/elibrary-page/?id=15947
PB  - Audio Engineering Society
LA  - en
AB  - A number of paralinguistic problems are often dealt with in isolation, such as emotion, health state or personality. However, there are also good examples of mutual benefit, mostly incorporating speaker gender knowledge. In this paper we deal with the question how further paralinguistic information, such as speaker age, height, or race can provide beneficial information when their ground truth knowledge is provided within single-task speaker classification. Tests with openSMILE's 1.5 k Paralinguistic Challenge Feature set on the TIMIT corpus of 630 speakers reveal significant boost in accuracy or cross-correlation|depending on the representation form of the problem at hand.
ER  -