Deep learning methods for speech to text systems
Giannetti, Jacopo (A.A. 2020/2021) Deep learning methods for speech to text systems. Tesi di Laurea in Artificial intelligence and machine learning, Luiss Guido Carli, relatore Marco Querini, pp. 46. [Bachelor's Degree Thesis]
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Abstract/Index
Motivation. Methodology. State of the art. Systems. Python libraries. Background. The history of artificial neural networks. Neural networks. Deep learning. Convolutional neural network. Recurrent neural network. Long short-term memory neural networks (LSTM). Regularization. Research. Speech recognition using recurrent neural networks. Speech-to-speech translation using deep learning. Keyword spotting system. Keyword spotting system. Dataset. Creation and training of the CNN. Experiments.
References
Bibliografia: pp. 43-45. Sitografia: p. 46.
| Thesis Type: | Bachelor's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Bachelor's Degree Programs > Bachelor's Degree Program in Management and Computer Science, English language (L-18) |
| Chair: | Artificial intelligence and machine learning |
| Thesis Supervisor: | Querini, Marco |
| Academic Year: | 2020/2021 |
| Session: | Summer |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 22 Oct 2021 12:32 |
| Last Modified: | 22 Oct 2021 12:32 |
| URI: | https://tesi.luiss.it/id/eprint/30515 |
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