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Self-Learning Speaker Identification
A System for Enhanced Speech Recognition
Engels
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Current speech recognition systems suffer from variation of voice §characteristics between speakers as they are usually based on speaker §independent speech models. In order to resolve this issue, adaptation §methods have been developed in many state-of-the-art systems. However, §information acquired over time is still lost whenever another speaker intermittently§uses the recognition system. This work therefore develops an integrated§approach for speech and speaker recognition in order to improve the§self-learning opportunities of the system. A speaker adaptation scheme§is introduced. It is suited for fast short-term and detailed long-term§adaptation. These adaptation profiles are then used for an efficient§speaker recognition system. The speaker identification enables the§speaker adaptation to track different speakers which results in an§optimal long-term adaptation.
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