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Data driven methods have long been used in Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) synthesis and have more recently been introduced for dialogue management, spoken language understanding, and Natural Language Generation. Machine learning is now present ¿end-to-end¿ in Spoken Dialogue Systems (SDS). However, these techniques require data collection and annotation campaigns, which can be time-consuming and expensive, as well as dataset expansion by simulation. In this book, we provide an overview of the current state of the field and of recent advances, with a specific focus on adaptivity.
| Leidėjas: | Springer US |
| Išleidimo metai: | 2012 |
| Knygos puslapių skaičius: | 188 |
| ISBN-10: | 1461448026 |
| ISBN-13: | 9781461448020 |
| Formatas: | 241 x 160 x 15 mm. Knyga kietu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Data-Driven Methods for Adaptive Spoken Dialogue Systems: Computational Learning for Conversational Interfaces“
