System 4[18] consists of three decoupled elements: speech/non-speech segmentation, acoustic change detection, and clustering of speech segments.
But the signals from different speakers have similar components when divided into speech segments.
To obtain the polynomial trajectory from speech segments, we modify the design matrix to include transitional information for contiguous frames.
Abstract: For a number of speech tasks, it can be useful to represent speech segments of arbitrary length by fixed-dimensional vectors, or embeddings.
The test dataset includes 500 speech segments and 500 non-speech segments.
Some sophisticated features are combined to represent the speech segments.
Natural speech consists of speech segments, silence, and background noise.
We use a development dataset containing 200 speech segments and 200 non-speech segments to choose the optimal feature subset.
For feature selection, we choose 2000 speech segments and 2000 non-speech segments, with only 400 randomly chosen labeled segments.
Therefore, detecting whispered speech segments in a normally phonated speech signal and recognizing the detected whispered speech segments separately can improve the performance of speech recognition systems.
The speaker segmentation strategy divides the input audio signal into speech and non-speech segments, and speech segments are also divided into shorter segments according to their speaker.
