Diarization problem is well known problem in the world of speech recognition and speech processing.
Our project goal is Speaker diarization in recorded conversation. We try a new approach for solving this problem, using dimension reduction algorithm (LLE).
The results are compared to a famous method for solving this problem, using Bottom-Up algorithm.
We tested our method on merged TIMIT files, and recordings we recorded by ourselves.

Collaboration:
Published Paper:
Speaker Diarization Using Locally Linear Embbeding Dimension Reduction, International Conference on the Science of Electrical Engineering (ICSEE 2016) , Eilat Israel.
,