Fine-grained radio station audio content personalized organization recommendation method

A recommendation method and fine-grained technology, applied in speech analysis, electrical components, speech recognition, etc., can solve the problems of content marking and searching inconvenience, time-consuming and labor-intensive, limiting the reorganization and utilization of audio media assets, etc., to improve the accuracy of text analysis degree of effect

Active Publication Date: 2017-07-14
北京中瑞鸿程科技开发有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, when a radio station is producing a program or recording a live program, usually a piece of independent audio is relatively long, and content marking and searching are extremely inconvenient
For example, a 30-minute news program is composed of more than a dozen independent news items, including domestic news, international news, sports news, social news, entertainment news, etc. However, I want to recommend a section about "CBA Finals" to users. " sports news, it is difficult to find the exact audio content paragraph
It is time-consuming and labor-intensive to use manual labeling of audio, which limits the reorganization and utilization of audio media assets
[0004] At the same time, although the existing mobile phone audio radio APPs have different focuses, the user experience is limited to: listening to similar programs on the same channel, simple continuous broadcast of the same theme programs, or real-time live broadcast of radio stations, etc.

Method used

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  • Fine-grained radio station audio content personalized organization recommendation method
  • Fine-grained radio station audio content personalized organization recommendation method
  • Fine-grained radio station audio content personalized organization recommendation method

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Embodiment Construction

[0104] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention.

[0105] figure 1 It is the system framework of the automatic segmentation and labeling system of the present invention

[0106] First, the frame window function selects the Hamming window. The definition of the Hamming window is as follows:

[0107]

[0108] The present invention adopts the least square method to fit and eliminate the trend item.

[0109] The invention adopts the improved spectrum subtraction method of multi-window spectrum estimation for noise reduction.

[0110] The pre-emphasized filter of the present invention is set as

[0111] H(z)=1-αz -1

[0112] The feature that the present invention extracts can include but not limited to the feature of table 1:

[0113] Table 1 Extraction features

[0114]

[0115] The present invention adopts the evolutiv...

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Abstract

The invention discloses a fine-grained radio station audio content personalized organization recommendation method, which includes the steps of automatically segmenting and marking audio programs of a radio station according to semantics, mining user preferences based on the Internet big data, automatically arranging a personalized program list and real-timely pushing programs, and relates to the fields of audio processing, machine learning, big data analysis, recommendation systems, data mining and the like. According to the method, an algorithm process of automatically segmenting and marking traditional broadcast audio programs based on the semantics is provided, a technical scheme for personalized content recommendation based on the Internet big data is also provided, and a fine-grained audio content personalized organization recommendation method is achieved. According to the method disclosed by the invention, the cold start problem is integrated into account, the program list organization and generation, real-time program switching, real-time program push and other factors during the listening time of the user are combined, a simple mode that the current radio station transplants the FM live broadcast to the Internet streaming media for playback is changed, and from the view point of audience users, the needs that the users listen to the contents of interested programs at right time can be met.

Description

technical field [0001] The patent of the present invention relates to a fine-grained method for personalized organization and recommendation of radio audio content, which automatically divides and marks the audio programs of the radio station according to semantics, mines user preferences based on Internet big data, automatically arranges personalized program lists and pushes real-time programs , involving audio processing, machine learning, big data analysis, recommendation system, data mining and other fields. Background technique [0002] The advantage of broadcasting lies in sound, which is used to convey information and value. Traditional radio stations use radio waves to transmit sound programs to audiences in a certain area through the working mode of collecting, editing, and producing; limited by the transmission mechanism, they have been hit by an unprecedented impact in the huge wave of traditional media transformation. However, with the help of big data and new m...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L29/08H04L29/06H04L12/58G10L15/04G10L15/14G10L21/0216G06F17/30
CPCG06F16/9535G10L15/04G10L15/14G10L21/0216H04L51/52H04L65/611H04L67/535H04L67/55
Inventor 宋明丽曹轶臻王琦张小平
Owner 北京中瑞鸿程科技开发有限公司
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