Robust Training Algorithm for Noisy Speech Recognition with Acoustic Modeling of Hidden Conditional Random Field
Autor: | Chiou-Fen Li, 李秋芬 |
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Rok vydání: | 2009 |
Druh dokumentu: | 學位論文 ; thesis |
Popis: | 97 In coordination with the robust training and discriminative training technique, a novel algorithm is proposed in this thesis for generating a set of compact hidden conditional random fields (HCRF)-based acoustic models. Among the related issues and techniques we explore are: 1. Derive the compensation operations with HCRF-based models for noise and channel bias distorted conditions. 2. Apply the robust training algorithm for noisy speech recognition with HCRF-based models. 3. Apply the discriminative training technique with HCRF-based models under multi-conditions training database for adverse speech recognition. |
Databáze: | Networked Digital Library of Theses & Dissertations |
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