MODIS: an audio motif discovery software
نویسندگان
چکیده
MODIS is a free speech and audio motif discovery software developed at IRISA Rennes. Motif discovery is the task of discovering and collecting occurrences of repeating patterns in the absence of prior knowledge, or training material. MODIS is based on a generic approach to mine repeating audio sequences, with tolerance to motif variability. The algorithm implementation allows to process large audio streams at a reasonable speed where motif discovery often requires huge amount of time.
منابع مشابه
The MODIS software for word like motif discovery and its use for zero resource audio summarization
MODIS is a free audio motif discovery software developed at IRISA Rennes. Motif discovery is the task of discovering and collecting occurrences of repeating patterns in the absence of prior knowledge, or training material. In the case of speech, those motifs could be word since MODIS is tolerant to motif variability. The algorithm implementation allows to process large audio streams at a reason...
متن کاملDevelopment of an Efficient Hybrid Method for Motif Discovery in DNA Sequences
This work presents a hybrid method for motif discovery in DNA sequences. The proposed method called SPSO-Lk, borrows the concept of Chebyshev polynomials and uses the stochastic local search to improve the performance of the basic PSO algorithm as a motif finder. The Chebyshev polynomial concept encourages us to use a linear combination of previously discovered velocities beyond that proposed b...
متن کاملAudio thumbnails for spoken content without transcription based on a maximum motif coverage criterion
The paper presents a system to create audio thumbnails of spoken content, i.e., short audio summaries representative of the entire content, without resorting to a lexical representation. As an alternative to searching for relevant words and phrases in a transcript, unsupervised motif discovery is used to find short, word-like, repeating fragments at the signal level without acoustic models. The...
متن کاملGeometric Crossover for Supervised Motif Discovery
Motif discovery is a general and important problem in bioinformatics, as motifs often are used to infer biologically important sites in bio-molecular sequences. Many problems in bioinformatics are naturally cast in terms of sequences, and distance measures for sequences derived from edit distance is fundamental in bioinformatics. Geometric Crossover is a representation-independent definition of...
متن کاملGeometric Crossover for Supervised Motif Discovery
Motif discovery is a general and important problem in bioinformatics, as motifs often are used to infer biologically important sites in bio-molecular sequences. Many problems in bioinformatics are naturally cast in terms of sequences, and distance measures for sequences derived from edit distance is fundamental in bioinformatics. Geometric Crossover is a representation-independent definition of...
متن کامل