18434773. AUDIO DATA PROCESSING simplified abstract (Tencent Technology (Shenzhen) Company Limited)

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AUDIO DATA PROCESSING

Organization Name

Tencent Technology (Shenzhen) Company Limited

Inventor(s)

Xin Feng of Shenzhen (CN)

AUDIO DATA PROCESSING - A simplified explanation of the abstract

This abstract first appeared for US patent application 18434773 titled 'AUDIO DATA PROCESSING

The method described in the abstract involves processing media by extracting audio track data related to a signal source type from audio data containing multiple data segments. This audio track data includes time periods determined to be associated with the signal source type. Weight values are allocated to the data segments in the audio data based on the audio track data, and then concatenated to form a weight value sequence. Audio features are extracted from the data segments and concatenated to form an audio feature sequence. The audio feature sequence is encoded to obtain an attention parameter sequence, which is then fused with the weight value sequence to obtain fusion parameters for the data segments. Recommendation parameters are determined based on this process.

  • Extract audio track data related to a signal source type from audio data
  • Allocate weight values to data segments based on the audio track data
  • Concatenate weight values to form a weight value sequence
  • Extract audio features from data segments and concatenate them to form an audio feature sequence
  • Encode the audio feature sequence to obtain an attention parameter sequence
  • Fuse the attention parameter sequence with the weight value sequence to obtain fusion parameters for the data segments
  • Determine recommendation parameters based on the fusion parameters

Potential Applications: - Audio processing and analysis in various industries such as music, film, and telecommunications - Personalized content recommendations based on audio features and signal sources

Problems Solved: - Efficient extraction and processing of audio data for signal source identification - Improved recommendation systems based on audio content analysis

Benefits: - Enhanced user experience through personalized recommendations - Streamlined audio data processing for better content understanding

Commercial Applications: Title: "Advanced Audio Processing Technology for Personalized Recommendations" This technology can be utilized in streaming services, radio stations, and content recommendation platforms to enhance user engagement and satisfaction by providing tailored content suggestions based on audio features and signal sources.

Questions about Audio Processing Technology: 1. How does this technology improve the accuracy of content recommendations? - This technology improves recommendation accuracy by analyzing audio features and signal sources to provide personalized suggestions to users. 2. What industries can benefit the most from this advanced audio processing technology? - Industries such as music streaming, film production, and telecommunications can benefit greatly from this technology by enhancing content recommendations and user experiences.


Original Abstract Submitted

A method of media processing includes extracting audio track data for at least a signal source type from audio data. The audio data includes multiple data segments, the audio track data includes at least a time period that is determined to be related to the signal source type. The method further includes allocating weight values respectively to the data segments in the audio data according to the audio track data, concatenating the weight values to form a weight value sequence of the audio data, extracting audio features respectively from the data segments, concatenating the audio features of the data segments to form an audio feature sequence of the audio data, encoding the audio feature sequence to obtain an attention parameter sequence of the audio data, fusing the attention parameter sequence and the weight value sequence to obtain fusion parameters respectively for the data segments, and determining recommendation parameters accordingly.