[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Ragano et al., 2023 - Google Patents

Audio quality assessment of vinyl music collections using self-supervised learning

Ragano et al., 2023

View PDF
Document ID
112275164920238014
Author
Ragano A
Benetos E
Hines A
Publication year
Publication venue
ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

External Links

Snippet

Metadata such as mean opinion score (MOS) quality ratings are critical to improve the usability and accessibility of music archive collections. Developing a non-intrusive objective quality metric that predicts MOS of archive music collections is challenging, since it requires …
Continue reading at qmro.qmul.ac.uk (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use
    • G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use for comparison or discrimination
    • G10L25/66—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use for comparison or discrimination for extracting parameters related to health condition
    • 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
    • G06F17/30017—Multimedia data retrieval; Retrieval of more than one type of audiovisual media
    • 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
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • 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
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • 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
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/08—Speech classification or search
    • 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
    • G—PHYSICS
    • G11—INFORMATION STORAGE
    • G11B—INFORMATION STORAGE BASED ON RELATIVE MOVEMENT BETWEEN RECORD CARRIER AND TRANSDUCER
    • G11B27/00—Editing; Indexing; Addressing; Timing or synchronising; Monitoring; Measuring tape travel

Similar Documents

Publication Publication Date Title
JP7617569B2 (en) Methods for training neural networks to reflect emotional perception, and related systems and methods for classifying and discovering associated content and associated digital media files with embedded multi-dimensional property vectors - Patents.com
Hasib et al. Bmnet-5: A novel approach of neural network to classify the genre of bengali music based on audio features
US20210012200A1 (en) Method of training a neural network and related system and method for categorizing and recommending associated content
KR20230079186A (en) System and method for recommending semantically related content
KR101057919B1 (en) How to recommend customized music through analyzing playlists of users
Niyazov et al. Content-based music recommendation system
GB2533654A (en) Analysing audio data
US20220238087A1 (en) Methods and systems for determining compact semantic representations of digital audio signals
Fan et al. Automatic recognition of eventfulness and pleasantness of soundscape
Kirchhoff et al. Evaluation of features for audio-to-audio alignment
Ragano et al. More for less: Non-intrusive speech quality assessment with limited annotations
Thorogood et al. Soundscape audio signal classification and segmentation using listeners perception of background and foreground sound
Ragano et al. Audio quality assessment of vinyl music collections using self-supervised learning
EP4196916A1 (en) Method of training a neural network and related system and method for categorizing and recommending associated content
WO2016102738A1 (en) Similarity determination and selection of music
EP3096242A1 (en) Media content selection
Morrison et al. Voting ensembles for spoken affect classification
Rao et al. Automatic music genre classification based on linguistic frequencies using machine learning
Zhang et al. Differentiated harmonic feature analysis on music information retrieval for instrument recognition.
De Mooij et al. Learning preferences for music playlists
Wang et al. Novel music genre classification system using transfer learning on a small dataset
Williamson Automatic Music Similarity Assessment and Recommendation
KR102623459B1 (en) Method, apparatus and system for providing audition event service based on user's vocal evaluation
US11134315B1 (en) Method of selecting a suitable content for subjective preference judgement
Venkatesh Deep learning for audio segmentation and intelligent remixing