http://www.cnr.it/ontology/cnr/individuo/prodotto/ID238307
Use of Multi-Layered Networks for Coding Speech with Phonetic Features (Contributo in volume (capitolo o saggio))
- Type
- Label
- Use of Multi-Layered Networks for Coding Speech with Phonetic Features (Contributo in volume (capitolo o saggio)) (literal)
- Anno
- 1989-01-01T00:00:00+01:00 (literal)
- Alternative label
Bengio Y., Cardin R., Cosi P., De Mori R. (1989)
Use of Multi-Layered Networks for Coding Speech with Phonetic Features
MORGAN KAUFMANN, Palo Alto (Stati Uniti d'America) in Advances in Neural Information Processing Systems, 1989
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Bengio Y., Cardin R., Cosi P., De Mori R. (literal)
- Pagina inizio
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
- Bengio Y., Cardin R., Cosi P., De Mori R.
Use of Multi-Layered Networks for Coding Speech with Phonetic Features
in Advances in Neural Information Processing Systems 1
D.S. Touretzky editor
Morgan Kaufmann Publisher
1989
http://books.nips.cc/papers/files/nips01/0224.pdf
http://www2.pd.istc.cnr.it/Papers/PieroCosi/cp-NIPS89.pdf
pages 224-231. (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://books.nips.cc/papers/files/nips01/0224.pdf (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- Advances in Neural Information Processing Systems (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
- Note
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- ISTC CNR, UOS Padova
Cosi P.
Computer Science Departement, Mc Gill University, Montreal Quebec, CANADA
Bengio Y., Cardin R.,De Mori R. (literal)
- Titolo
- Use of Multi-Layered Networks for Coding Speech with Phonetic Features (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
- Abstract
- Preliminary results on speaker-independant speech recognition are reported. A method that combines expertise on neural networks with expertise on speech recognition is used to build the recognition systems. For transient sounds, event-driven property extractors with variable resolution in the time and frequency domains are used. For sonorant speech, a model of the human auditory system is preferred to FFT as a front-end module. (literal)
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