Fundamentals of speech recognition
Fundamentals of speech recognition
Visualizing music and audio using self-similarity
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition
Structural analysis of musical signals for indexing and thumbnailing
Proceedings of the 3rd ACM/IEEE-CS joint conference on Digital libraries
Repeating pattern discovery and structure analysis from acoustic music data
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Tonal Description of Polyphonic Audio for Music Content Processing
INFORMS Journal on Computing
Music structure analysis using a probabilistic fitness measure and a greedy search algorithm
IEEE Transactions on Audio, Speech, and Language Processing
Music information retrieval using social tags and audio
IEEE Transactions on Multimedia - Special section on communities and media computing
Detection of similar sequences in EEG maps series using correlation coefficients matrix
Machine Graphics & Vision International Journal
Using quadratic programming to estimate feature relevance in structural analyses of music
Proceedings of the 21st ACM international conference on Multimedia
| Hi-index | 0.00 |
The structure analysis of pop and rock songs from audio signals is conducted via similarity matrix processing in this work. The similarity matrix offers pairwise similarity between any two short intervals of fixed length in a song. We use two similarity matrices to show their diverse characteristics. The characteristics are explained by musical chord successions. Then, several similarity matrix processing techniques are developed for music structure analysis. First, an algorithm is proposed to check the boundaries and periods of repetitive chord successions with short periods. Second, the Viterbi algorithm is applied to detect straight segments in sub-diagonal lines of the similarity matrix. Periods of repeating chord successions are used to refine the state space to enhance the detection performance. Furthermore, a post-processing technique is used to map detected segments into sections in a song. Experimental results from test musical audio data are given to demonstrate the performance of the proposed method.