http://www.cnr.it/ontology/cnr/individuo/prodotto/ID241059
Connected Digit Recognition Experiments with the OGI Toolkit's Neural Network and HMM-Based Recognizers (Contributo in atti di convegno)
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- Connected Digit Recognition Experiments with the OGI Toolkit's Neural Network and HMM-Based Recognizers (Contributo in atti di convegno) (literal)
- Anno
- 1998-01-01T00:00:00+01:00 (literal)
- Alternative label
Cosi P., Hosom J.P., Shalkwyk J., Sutton S., Cole R.A. (1998)
Connected Digit Recognition Experiments with the OGI Toolkit's Neural Network and HMM-Based Recognizers
in Interactive Voice Technology for Telecommunications Applications, 1998. 1998 IEEE 4th Workshop IVTTA-ETWR '98, Turin, Italy, 29-30 September, 1998
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- Cosi P., Hosom J.P., Shalkwyk J., Sutton S., Cole R.A. (literal)
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- Cosi P., Hosom J.P., Shalkwyk J., Sutton S., Cole R.A.
Connected Digit Recognition Experiments with the OGI Toolkit's Neural Network and HMM-Based Recognizers
Proceedings of Interactive Voice Technology for Telecommunications Applications, 1998.
1998 IEEE 4th Workshop IVTTA-ETWR '98
Turin, Italy
29-30 September, 1998
pp. 135-140
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- Proceedings of 4th IEEE Workshop on Interactive Voice Technology for Telecommunications Applications (literal)
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- ISTC CNR, UOS Padova
Cosi P.
Center for Spoken Language Understanding (CSLU)
Oregon Graduate Institute of Science and Technology (OGI)
P.O. Box 91000, Portland Oregon 97291-1000 USA
Hosom J.P., Shalkwyk J., Sutton S., Cole R.A. (literal)
- Titolo
- Connected Digit Recognition Experiments with the OGI Toolkit's Neural Network and HMM-Based Recognizers (literal)
- Abstract
- This paper describes a series of experiments that compare different approaches to training a speaker-independent continuous-speech digit recognizer using the CSLU Toolkit. Comparisons are made between the Hidden Markov Model (HMM) and Neural Network (NN) approaches. In addition, a description of the CSLU Toolkit research environment is given.
The CSLU Toolkit is a research and development software environment that provides a powerful and flexible tool for creating and using spoken language systems for telephone and PC applications. In particular, the CSLU-HMM, the CSLU-NN, and the CSLU-FBNN development environments, with which our experiments were implemented, will be described in detail and recognition results will be compared.
Our speech corpus is OGI 30K-Numbers, which is a collection of spontaneous ordinal and cardinal numbers, continuous digit strings and isolated digit strings. The utterances were recorded by having a large number of people recite their ZIP code, street address, or other numeric information over the telephone. This corpus represents a very noisy and difficult recognition task.
Our best results (98% word recognition, 92% sentence recognition), obtained with the FBNN architecture, suggest the effectiveness of the CSLU Toolkit in building real-life speech recognition systems. (literal)
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