Contextual Mood Analysis with Knowledge Graph Representation for Hindi
Song Lyrics in Devanagari Script
- URL: http://arxiv.org/abs/2108.06947v1
- Date: Mon, 16 Aug 2021 07:44:20 GMT
- Title: Contextual Mood Analysis with Knowledge Graph Representation for Hindi
Song Lyrics in Devanagari Script
- Authors: Makarand Velankar, Rachita Kotian and Parag Kulkarni
- Abstract summary: The proposed system performs contextual mood analysis of Hindi song lyrics in Devanagari text format.
The testing results show 64% accuracy for the mood prediction.
- Score: 7.379078963413671
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Lyrics play a significant role in conveying the song's mood and are
information to understand and interpret music communication. Conventional
natural language processing approaches use translation of the Hindi text into
English for analysis. This approach is not suitable for lyrics as it is likely
to lose the inherent intended contextual meaning. Thus, the need was identified
to develop a system for Devanagari text analysis. The data set of 300 song
lyrics with equal distribution in five different moods is used for the
experimentation. The proposed system performs contextual mood analysis of Hindi
song lyrics in Devanagari text format. The contextual analysis is stored as a
knowledge base, updated using an incremental learning approach with new data.
Contextual knowledge graph with moods and associated important contextual terms
provides the graphical representation of the lyric data set used. The testing
results show 64% accuracy for the mood prediction. This work can be easily
extended to applications related to Hindi literary work such as summarization,
indexing, contextual retrieval, context-based classification and grouping of
documents.
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