A Corpus-based Study Of Rhythm Patterns

We present a corpus-based study of musical rhythm, based on a collection of 4.8 million bar-length drum patterns extracted from 48,176 pieces of symbolic music. Approaches to the analysis of rhythm in music information retrieval to date have focussed on low-level features for retrieval or on the detection of tempo, beats and drums in audio recordings. Musicological approaches are usually concerned with the description or implementation of manmade music theories. In this paper, we present a quantitative bottom-up approach to the study of rhythm that relies upon well-understood statistical methods from natural language processing. We adapt these methods to our corpus of music, based on the realisation that—unlike words—barlength drum patterns can be systematically decomposed into sub-patterns both in time and by instrument. We show that, in some respects, our rhythm corpus behaves like natural language corpora, particularly in the sparsity of vocabulary. The same methods that detect word collocations allow us to quantify and rank idiomatic combinations of drum patterns. In other respects, our corpus has properties absent from language corpora, in particular, the high amount of repetition and strong mutual information rates between drum instruments. Our findings may be of direct interest to musicians and musicologists, and can inform the design of ground truth corpora and computational models of musical rhythm. 1

How jazz musicians improvise: The central role of auditory and motor patterns

It is well known that jazz improvisations include repeated rhythmic and melodic patterns. What is less understood is how those patterns come to be. One theory posits that entire motor patterns are stored in procedural memory and inserted into an ongoing improvisation. An alternative view is that improvisers use procedures based on the rules of tonal jazz to create an improvised output. This output may contain patterns but these patterns are accidental and not stored in procedural memory for later use. The current study used a novel computer-based technique to analyze a large corpus of 48 improvised solos by the jazz great Charlie Parker. To be able to compare melodic patterns independent of absolute pitch, all pitches were converted to directional intervals listed in half steps. Results showed that 82.6% of the notes played begin a four-interval pattern and 57.6% begin interval and rhythm patterns. The mean number of times the four-interval pattern on each note position is repeated in the solos analyzed was 26.3 and patterns up to 49 intervals in length were identified. The sheer ubiquity of patterns and the pairing of pitch and rhythm patterns support the theory that pre-formed structures are inserted during improvisation. The patterns may be encoded both during deliberate practice and through an incidental learning processes. These results align well with related processes in both language acquisition and motor learning

Acoustic correlates of linguistic rhythm: Perspectives

The empirical grounding of a typology of languages' rhythm is again a hot issue. The currently popular approach is based on the durations of vocalic and intervocalic intervals and their variability. Despite some successes, many questions remain. The main findings still need to be generalised to much larger corpora including many more languages. But a straightforward continuation of the current work faces many difficulties. Perspectives are outlined for future work, including proposals for the cross-linguistic control of speech rate, improvements on the statistical analyses, and prospects raised by automatic speech processing

Speaker Identification for Swiss German with Spectral and Rhythm Features

We present results of speech rhythm analysis for automatic speaker identification. We expand previous experiments using similar methods for language identification. Features describing the rhythmic properties of salient changes in signal components are extracted and used in an speaker identification task to determine to which extent they are descriptive of speaker variability. We also test the performance of state-of-the-art but simple-to-extract frame-based features. The paper focus is the evaluation on one corpus (swiss german, TEVOID) using support vector machines. Results suggest that the general spectral features can provide very good performance on this dataset, whereas the rhythm features are not as successful in the task, indicating either the lack of suitability for this task or the dataset specificity

Impact of Metrical Prosody on Performances

This thesis is about testing Frederick Turner and Ernst Pöppel's claim that suggestmetrical poem tends to measure three seconds in terms of psychological limitwhen it is performed aloud. The objective of the study is to present metricalpoems as the new data to test their claim by using corpus analysis. Hereby, theresearcher uses publicly available 28 read-aloud poems from poetryoutloud.orgby using Praat to find the duration of each metrical line. The findings indicate thatthere are 18 English metrical poems with 314 lines in total, supported by metricaltree analysis, meanwhile there are 10 poems which are free verse and found that1) most lines have iamb feet, 2) 10 of the metrical pattern of the poems are iambicpentameter, whereas others are in diverse meter, 3) there is no psychological limiton the duration of metrical lines in performance as the researcher only founds62.73% that fit to the 3 seconds of temporal window based on the analysis in thecorpus of 314 metrical lines. This study has shown what Frederick Turner andErnst Pöppel claim is not methodologically proven

Impact of Metrical Prosody on Performances

This thesis is about testing Frederick Turner and Ernst Pöppel\u27s claim that suggestmetrical poem tends to measure three seconds in terms of psychological limitwhen it is performed aloud. The objective of the study is to present metricalpoems as the new data to test their claim by using corpus analysis. Hereby, theresearcher uses publicly available 28 read-aloud poems from poetryoutloud.orgby using Praat to find the duration of each metrical line. The findings indicate thatthere are 18 English metrical poems with 314 lines in total, supported by metricaltree analysis, meanwhile there are 10 poems which are free verse and found that1) most lines have iamb feet, 2) 10 of the metrical pattern of the poems are iambicpentameter, whereas others are in diverse meter, 3) there is no psychological limiton the duration of metrical lines in performance as the researcher only founds62.73% that fit to the 3 seconds of temporal window based on the analysis in thecorpus of 314 metrical lines. This study has shown what Frederick Turner andErnst Pöppel claim is not methodologically proven

Speech and music discrimination: Human detection of differences between music and speech based on rhythm

Rhythm in speech and singing forms one of its basic acoustic components. Therefore, it is interesting to investigate the capability of subjects to distinguish between speech and singing when only the rhythm remains as an acoustic cue. For this study we developed a method to eliminate all linguistic components but rhythm from the speech and singing signals. The study was conducted online and participants could listen to the stimuli via loudspeakers or headphones. The analysis of the survey shows that people are able to significantly discriminate between speech and singing after they have been altered. Furthermore, our results reveal specific features, which supported participants in their decision, such as differences in regularity and tempo between singing and speech samples. The hypothesis that music trained people perform more successfully on the task was not proved. The results of the study are important for the understanding of the structure of and differences between speech and singing, for the use in further studies and for future application in the field of speech recognition