Peter Grosche

Learn More
Locating boundaries between coherent and/or repetitive segments of a time series is a challenging problem pervading many scientific domains. In this paper we propose an unsupervised method for boundary detection, combining three basic principles: novelty, homogeneity, and repetition. In particular, the method uses what we call structure features, a(More)
The extraction of tempo and beat information from music recordings constitutes a challenging task in particular for non-percussive music with soft note onsets and time-varying tempo. In this paper, we introduce a novel mid-level representation that captures musically meaningful local pulse information even for the case of complex music. Our main idea is to(More)
The general goal of music synchronization is to automatically align the multiple information sources such as audio recordings, MIDI files, or digitized sheet music related to a given musical work. In computing such alignments, one typically has to face a delicate tradeoff between robustness and accuracy. In this paper, we introduce novel audio features that(More)
Content-based approaches to music retrieval are of great relevance as they do not require any kind of manually generated annotations. In this paper, we introduce the concept of structure fingerprints, which are compact descriptors of the musical structure of an audio recording. Given a recorded music performance, structure fingerprints facilitate the(More)
The extraction of local tempo and beat information from audio recordings constitutes a challenging task, particularly for music that reveals significant tempo variations. Furthermore, the existence of various pulse levels such as measure, tactus, and tatum often makes the determination of absolute tempo problematic. In this paper, we present a robust(More)
Automated beat tracking and tempo estimation from music recordings become challenging tasks in the case of nonpercussive music with soft note onsets and time-varying tempo. In this paper, we introduce a novel mid-level representation which captures predominant local pulse information. To this end, we first derive a tempogram by performing a local spectral(More)
Even though there is a rapidly growing corpus of available music recordings, there is still a lack of audio contentbased retrieval systems allowing to explore large music collections without manually generated annotations. In this context, the query-by-example paradigm is commonplace: given an audio recording or a fragment of it (used as query or example),(More)
The automatic extraction of structural information from music recordings constitutes a central research topic. In this paper, we deal with a subproblem of audio structure analysis called audio thumbnailing with the goal to determine the audio segment that best represents a given music recording. Typically, such a segment has many (approximate) repetitions(More)
The computer-based harmonic analysis of music recordings with the goal to automatically extract chord labels directly from the given audio data constitutes a major task in music information retrieval. In most automated chord recognition procedures, the given music recording is first converted into a sequence of chroma-based audio features and then pattern(More)
Even though folk songs have been passed down mainly by oral tradition, most musicologists study the relation between folk songs on the basis of score-based transcriptions. Due to the complexity of audio recordings, once having the transcriptions, the original recorded tunes are often no longer studied in the actual folk song research though they still may(More)