Ujlambkar et al., 2012 - Google Patents

Mood classification of Indian popular music

Ujlambkar et al., 2012

Document ID
6202114980896257783
Author
Ujlambkar A
Attar V
Publication year
Publication venue
Proceedings of the CUBE international information technology conference

External Links

Snippet

Music has been an inherent part of human life when it comes to recreation; entertainment and much recently, even as a therapeutic medium. Music is closely related to human emotions. We often choose to listen to a song or music which best fits our mood at that …
Continue reading at dl.acm.org (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3074—Audio data retrieval
    • G06F17/30755—Query formulation specially adapted for audio data retrieval
    • G06F17/30758—Query by example, e.g. query by humming
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3074—Audio data retrieval
    • G06F17/30743—Audio data retrieval using features automatically derived from the audio content, e.g. descriptors, fingerprints, signatures, MEP-cepstral coefficients, musical score, tempo
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3074—Audio data retrieval
    • G06F17/30749—Audio data retrieval using information manually generated or using information not derived from the audio data, e.g. title and artist information, time and location information, usage information, user ratings
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30017—Multimedia data retrieval; Retrieval of more than one type of audiovisual media
    • G06F17/30023—Querying
    • G06F17/30038—Querying based on information manually generated or based on information not derived from the media content, e.g. tags, keywords, comments, usage information, user ratings
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30017—Multimedia data retrieval; Retrieval of more than one type of audiovisual media
    • G06F17/30023—Querying
    • G06F17/30029—Querying by filtering; by personalisation, e.g. querying making use of user profiles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30017—Multimedia data retrieval; Retrieval of more than one type of audiovisual media
    • G06F17/3005—Presentation of query results
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30781—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F17/30784—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10H—ELECTROPHONIC MUSICAL INSTRUMENTS
    • G10H2210/00—Aspects or methods of musical processing having intrinsic musical character, i.e. involving musical theory or musical parameters or relying on musical knowledge, as applied in electrophonic musical tools or instruments
    • G10H2210/031—Musical analysis, i.e. isolation, extraction or identification of musical elements or musical parameters from a raw acoustic signal or from an encoded audio signal
    • G10H2210/061—Musical analysis, i.e. isolation, extraction or identification of musical elements or musical parameters from a raw acoustic signal or from an encoded audio signal for extraction of musical phrases, isolation of musically relevant segments, e.g. musical thumbnail generation, or for temporal structure analysis of a musical piece, e.g. determination of the movement sequence of a musical work
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10H—ELECTROPHONIC MUSICAL INSTRUMENTS
    • G10H2240/00—Data organisation or data communication aspects, specifically adapted for electrophonic musical tools or instruments
    • G10H2240/121—Musical libraries, i.e. musical databases indexed by musical parameters, wavetables, indexing schemes using musical parameters, musical rule bases or knowledge bases, e.g. for automatic composing methods
    • G10H2240/131—Library retrieval, i.e. searching a database or selecting a specific musical piece, segment, pattern, rule or parameter set
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10H—ELECTROPHONIC MUSICAL INSTRUMENTS
    • G10H1/00—Details of electrophonic musical instruments
    • G10H1/0008—Associated control or indicating means
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L17/00—Speaker identification or verification
    • G10L17/26—Recognition of special voice characteristics, e.g. for use in lie detectors; Recognition of animal voices
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10H—ELECTROPHONIC MUSICAL INSTRUMENTS
    • G10H2240/00—Data organisation or data communication aspects, specifically adapted for electrophonic musical tools or instruments
    • G10H2240/075—Musical metadata derived from musical analysis or for use in electrophonic musical instruments
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass

Similar Documents

Publication Publication Date Title
Hizlisoy et al. Music emotion recognition using convolutional long short term memory deep neural networks
Celma Music recommendation
Kim et al. Music emotion recognition: A state of the art review
Hasib et al. Bmnet-5: A novel approach of neural network to classify the genre of bengali music based on audio features
Zhuang et al. Music genre classification with transformer classifier
Ujlambkar et al. Mood classification of Indian popular music
Singhal et al. Classification of Music Genres using Feature Selection and Hyperparameter Tuning
Ujlambkar et al. Automatic mood classification model for indian popular music
Xu et al. Source separation improves music emotion recognition
Lu et al. Boosting for multi-modal music emotion
Gupta Deep audio embeddings and attention based music emotion recognition
Chi et al. The power of words: Enhancing music mood estimation with textual input of lyrics
Herrera et al. SIMAC: Semantic interaction with music audio contents
Laurier et al. Music mood annotator design and integration
Ahsan et al. Multi-label annotation of music
Yeh et al. Popular music representation: chorus detection & emotion recognition
Patra et al. Music emotion recognition system
Özseven et al. A Content Analysis of the Research Approaches in Music Genre Recognition
Joseph et al. Machine Learning Approaches for Emotion Classification of Music: A Systematic Literature Review
Ospitia Medina et al. High-level libraries for emotion recognition in music: a review
Lee et al. Mood classfication from musical audio using user group-dependent models
Vale The role of artist and genre on music emotion recognition
Abeyratne et al. Classification of sinhala songs based on emotions
Pao et al. Comparison between weighted d-knn and other classifiers for music emotion recognition
Jun et al. Music retrieval and recommendation scheme based on varying mood sequences