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Isolated Speech Recognition Using Artificial Neural Networks
| Content Provider | Semantic Scholar |
|---|---|
| Author | Polur, Prasad D. Zhou, Ruobing Yang, Jun Adnani, Fedra Hobson, Rosalyn S. |
| Copyright Year | 2001 |
| Abstract | Abstract-In this project Artificial Neural Networks are used as research tool to accomplish Automated Speech Recognition of normal speech. A small size vocabulary containing the words YES and NO is chosen. Spectral features using cepstral analysis are extracted per frame and imported to a feed-forward neural network which uses a backpropagation with momentum training algorithm. The network is trained to recognize and classify the incoming words into the respective categories. The output from the neural network is loaded into a pattern search function, which matches the input sequence with a set of target word patterns. The level of variability in input speech patterns limits the vocabulary and affects the reliability of the network. The results from the first stage of this work are satisfactory and thus the application of artificial neural networks in conjunction with cepstral analysis in isolated word recognition holds promise. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.dtic.mil/get-tr-doc/pdf?AD=ADA409964 |
| Alternate Webpage(s) | http://www.dtic.mil/dtic/tr/fulltext/u2/a409964.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Algorithm Artificial neural network Backpropagation Categories Cepstrum Extraction Feedforward neural network Heart rate variability Pattern search (optimization) Speech recognition Stage level 1 Vocabulary |
| Content Type | Text |
| Resource Type | Article |
