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.

Use of Multi-Layered Networks for Coding Speech with Phonetic Features

Cosi P;
1989

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.
1989
Istituto di Scienze e Tecnologie della Cognizione - ISTC
Istituto di Scienze e Tecnologie della Cognizione - ISTC
Inglese
D.S. Touretzky
Advances in Neural Information Processing Systems
224
231
1-558-60015-9
http://books.nips.cc/papers/files/nips01/0224.pdf
MORGAN KAUFMANN
Palo Alto
STATI UNITI D'AMERICA
Multi-Layered Networks
Coding
Speech
Phonetic Features
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.
1
02 Contributo in Volume::02.01 Contributo in volume (Capitolo o Saggio)
268
none
Bengio Y.; Cardin R.; Cosi P.; De Mori R.
info:eu-repo/semantics/bookPart
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/200323
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