Invention Grant
US09367612B1 Correlation-based method for representing long-timescale structure in time-series data
有权
用于表示时间序列数据中的长时间尺度结构的相关方法
- Patent Title: Correlation-based method for representing long-timescale structure in time-series data
- Patent Title (中): 用于表示时间序列数据中的长时间尺度结构的相关方法
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Application No.: US13300057Application Date: 2011-11-18
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Publication No.: US09367612B1Publication Date: 2016-06-14
- Inventor: Douglas Eck , Jay Yagnik
- Applicant: Douglas Eck , Jay Yagnik
- Applicant Address: US CA Mountain View
- Assignee: GOOGLE INC.
- Current Assignee: GOOGLE INC.
- Current Assignee Address: US CA Mountain View
- Agency: Lowenstein Sandler LLP
- Main IPC: G06F17/00
- IPC: G06F17/00 ; G06F17/30

Abstract:
A system identifies a set of initial segments of a time-based data item, such as audio. The segments can be defined at regular time intervals within the time-based data item. The initial segments are short segments. The system computes a short-timescale vectorial representation for each initial segment and compares the short-timescale vectorial representation for each initial segment with other short-timescale vectorial representations of the segments in a time duration within the time-based data item (e.g., audio) immediately preceding or immediately following the initial segment. The system generates a representation of long-timescale information for the time-based data item based on a comparison of the short-timescale vectorial representations of the initial segments and the short-timescale vectorial representations of immediate segments. The representation of long-timescale information identifies an underlying repetition structure of the time-based data item, such as rhythm or phrasing in an audio item.
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