Audio segmentation with energy-weighted bandwidth bias

Details Audio segmentation with energy-weighted bandwidth bias Audio segmentation with energy-weighted bandwidth bias

2007-07-10

2007-07-10

{hacek over (S)}mits, Talivaldis Ivars (Department: 2626)

Data processing: speech signal processing, linguistics, language

Speech signal processing

For storage or transmission

C704S208000

Reexamination Certificate

active

10279720

ABSTRACT:
A method (200) and apparatus (100) for segmenting a sequence of audio samples into homogeneous segments (550and555) are disclosed. The method (200) forms a sequence of frames (701to704) along the sequence of audio samples, and extracts, for each frame, a data feature. The data features form a sequence of data features. Transition points in the sequence of data features are thin detected by applying the Bayesian Information Criterion to the sequence of data features. The transition points define the homogeneous segments (550and555). Preferably the data feature is single-dimensional and a leptokurtic distribution is used as an event model in the Bayesian Information Criterion.

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Scott Shaobing Chen, et al., “Speaker, Environment And Channel Change Detection And Clustering Via The Bayesian Information Criterion”, IBM T.J. Watson Research Center.
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