Computational Methods for Underdetermined Convolutive Speech Localization and Separation via Model-based Sparse Component Analysis
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Speaker turn detection is an important task for many speech processing applications. However, accurate segmentation can be hard to achieve if there are multiple concurrent speakers (overlap), as is typically the case in multi-party conversations. In such c ...
Assessing the quality of a speaker localization or tracking algorithm on a few short examples is difficult, especially when the ground-truth is absent or not well defined. One step towards systematic performance evaluation of such algorithms is to provide ...
This paper proposes a technique that segments into speaker turns based on their location, essentially implementing a discrete source tracking system. In many multi-party conversations, such as meetings or teleconferences, the location of participants is re ...
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Speaker turn detection is an important task for many speech processing applications. However, accurate segmentation can be hard to achieve if there are multiple concurrent speakers (overlap), as is typically the case in multi-party conversations. In such c ...
This paper proposes a technique that segments into speaker turns based on their location, essentially implementing a discrete source tracking system. In many multi-party conversations, such as meetings or teleconferences, the location of participants is re ...