<p><br>Current speech recognition systems suffer from variation of voice <br>characteristics between speakers as they are usually based on speaker <br>independent speech models. In order to resolve this issue, adaptation <br>methods have been developed in many state-of-the-art systems. However, <br>
Self-Learning Speaker Identification
- Publisher
- Springer Berlin Heidelberg
- Year
- 2011
- Edition
- 1st Edition.
- Category
- Fiction
No coin nor oath required. For personal study only.
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<p><br>Current speech recognition systems suffer from variation of voice <br>characteristics between speakers as they are usually based on speaker <br>independent speech models. In order to resolve this issue, adaptation <br>methods have been developed in many state-of-the-art systems. However, <br>
Current speech recognition systems are based on speaker independent speech models and suffer from inter-speaker variations in speech signal characteristics. This work develops an integrated approach for speech and speaker recognition in order to gain space for self-learning opportunities of the syst
A voice is much more than just a string of words. Voices, unlike fingerprints, are inherently complex. They signal a great deal of information in addition to the intended message: the speakers' sex, for example, or their emotional state, or age. Although evidence from DNA analysis grabs the headline
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