Speech segmentation using multilevel hybrid filters
This work addresses speech segmentation for applications such as phonetically-segmented speech coders, but it appears incremental as it builds on existing filter methods.
The paper tackles speech segmentation by proposing a multilevel hybrid filter approach, achieving accurate transition location and good performance in noisy environments like Gaussian and impulsive noise.
A novel approach for speech segmentation is proposed, based on Multilevel Hybrid (mean/min) Filters (MHF) with the following features: An accurate transition location. Good performance in noisy environments (gaussian and impulsive noise). The proposed method is based on spectral changes, with the goal of segmenting the voice into homogeneous acoustic segments. This algorithm is being used for phoneticallysegmented speech coder, with successful results.