Evaluating an analysis-by-synthesis model for Jazz improvisation

This paper pursues two goals. First, we present a generative model for (monophonic) jazz improvisation whose main purpose is testing hypotheses on creative processes during jazz improvisation. It uses a hierarchical Markov model based on mid-level units and the Weimar Bebop Alphabet, with statistics taken from the Weimar Jazz Database. A further ingredient is chord-scale theory to select pitches. Second, as there are several issues with Turing-like evaluation processes for generative models of jazz improvisation, we decided to conduct an exploratory online study to gain further insight while testing our algorithm in the context of a variety of human generated solos by eminent masters, jazz students, and non-professionals in various performance renditions. Results show that jazz experts (64.4% accuracy) but not non-experts (41.7% accuracy) are able to distinguish the computer-generated solos amongst a set of real solos, but with a large margin of error. The type of rendition is crucial when assessing artificial jazz solos because expressive and performative aspects (timbre, articulation, micro-timing and band-soloist interaction) seem to be equally if not more important than the syntactical (tone) content. Furthermore, the level of expertise of the solo performer does matter, as solos by non-professional humans were on average rated worse than the algorithmic ones. Accordingly, we found indications that assessments of origin of a solo are partly driven by aesthetic judgments. We propose three possible strategies to install a reliable evaluation process to mitigate some of the inherent problems

Consistent increase in Indian monsoon rainfall and its variability across CMIP-5 models

The possibility of an impact of global warming on the Indian monsoon is of critical importance for the large population of this region. Future projections within the Coupled Model Intercomparison Project Phase 3 (CMIP-3) showed a wide range of trends with varying magnitude and sign across models. Here the Indian summer monsoon rainfall is evaluated in 20 CMIP-5 models for the period 1850 to 2100. In the new generation of climate models, a consistent increase in seasonal mean rainfall during the summer monsoon periods arises. All models simulate stronger seasonal mean rainfall in the future compared to the historic period under the strongest warming scenario RCP-8.5. Increase in seasonal mean rainfall is the largest for the RCP-8.5 scenario compared to other RCPs. Most of the models show a northward shift in monsoon circulation by the end of the 21st century compared to the historic period under the RCP-8.5 scenario. The interannual variability of the Indian monsoon rainfall also shows a consistent positive trend under unabated global warming. Since both the long-term increase in monsoon rainfall as well as the increase in interannual variability in the future is robust across a wide range of models, some confidence can be attributed to these projected trends

A trend-preserving bias correction – The ISI-MIP approach

Statistical bias correction is commonly applied within climate impact modelling to correct climate model data for systematic deviations of the simulated historical data from observations. Methods are based on transfer functions generated to map the distribution of the simulated historical data to that of the observations. Those are subsequently applied to correct the future projections. Here, we present the bias correction method that was developed within ISI-MIP, the first Inter-Sectoral Impact Model Intercomparison Project. ISI-MIP is designed to synthesise impact projections in the agriculture, water, biome, health, and infrastructure sectors at different levels of global warming. Bias-corrected climate data that are used as input for the impact simulations could be only provided over land areas. To ensure consistency with the global (land + ocean) temperature information the bias correction method has to preserve the warming signal. Here we present the applied method that preserves the absolute changes in monthly temperature, and relative changes in monthly values of precipitation and the other variables needed for ISI-MIP. The proposed methodology represents a modification of the transfer function approach applied in the Water Model Intercomparison Project (Water-MIP). Correction of the monthly mean is followed by correction of the daily variability about the monthly mean. Besides the general idea and technical details of the ISI-MIP method, we show and discuss the potential and limitations of the applied bias correction. In particular, while the trend and the long-term mean are well represented, limitations with regards to the adjustment of the variability persist which may affect, e.g. small scale features or extremes

Emulating Atlantic overturning strength for low emission scenarios: Consequences for sea-level rise along the North American east coast

In order to provide probabilistic projections of the future evolution of the Atlantic Meridional Overturning Circulation (AMOC), we calibrated a simple Stommeltype box model to emulate the output of fully coupled threedimensional atmosphere-ocean general circulation models (AOGCMs) of the Coupled Model Intercomparison Project (CMIP). Based on this calibration to idealised global warming scenarios with and without interactive atmosphere-ocean fluxes and freshwater perturbation simulations, we project the future evolution of the AMOC mean strength within the covered calibration range for the lower two Representative Concentration Pathways (RCPs) until 2100 obtained from the reduced complexity carbon cycle-climate model MAGICC 6. For RCP3-PD with a global mean temperature median below 1.0 C warming relative to the year 2000, we project an ensemble median weakening of up to 11% compared to 22% under RCP4.5 with a warming median up to 1.9 C over the 21st century. Additional Greenland meltwater of 10 and 20 cm of global sea-level rise equivalent further weakens the AMOC by about 4.5 and 10 %, respectively. By combining our outcome with a multi-model sea-level rise study we project a dynamic sea-level rise along the New York City coastline of 4 cm for the RCP3-PD and of 8 cm for the RCP4.5 scenario over the 21st century. We estimate the total steric and dynamic sea-level rise for New York City to be about 24 cm until 2100 for the RCP3-PD scenario, which can hold as a lower bound for sea-level rise projections in this region, as it does not include ice sheet and mountain glacier contributions

Musical sophistication and speech auditory-motor coupling: Easy tests for quick answers

Musical training enhances auditory-motor cortex coupling, which in turn facilitates music and speech perception. How tightly the temporal processing of music and speech are intertwined is a topic of current research. We investigated the relationship between musical sophistication (Goldsmiths Musical Sophistication index, Gold-MSI) and spontaneous speech-to-speech synchronization behavior as an indirect measure of speech auditory-motor cortex coupling strength. In a group of participants (n = 196), we tested whether the outcome of the spontaneous speech-to-speech synchronization test (SSS-test) can be inferred from self-reported musical sophistication. Participants were classified as high (HIGHs) or low (LOWs) synchronizers according to the SSS-test. HIGHs scored higher than LOWs on all Gold-MSI subscales (General Score, Active Engagement, Musical Perception, Musical Training, Singing Skills), but the Emotional Attachment scale. More specifically, compared to a previously reported German-speaking sample, HIGHs overall scored higher and LOWs lower. Compared to an estimated distribution of the English-speaking general population, our sample overall scored lower, with the scores of LOWs significantly differing from the normal distribution, with scores in the ∼30th percentile. While HIGHs more often reported musical training compared to LOWs, the distribution of training instruments did not vary across groups. Importantly, even after the highly correlated subscores of the Gold-MSI were decorrelated, particularly the subscales Musical Perception and Musical Training allowed to infer the speech-to-speech synchronization behavior. The differential effects of musical perception and training were observed, with training predicting audio-motor synchronization in both groups, but perception only in the HIGHs. Our findings suggest that speech auditory-motor cortex coupling strength can be inferred from training and perceptual aspects of musical sophistication, suggesting shared mechanisms involved in speech and music perception

Symbolic Melodic Similarity: State of the Art and Future Challenges

Fostered by the introduction of the Music Information Retrieval Evaluation eXchange (MIREX) competition, the number of systems which calculate Symbolic Melodic Similarity has recently increased considerably. In order to understand the state of the art, we provide a comparative analysis of existing algorithms. The analysis is based on eight criteria that help characterising the systems, and highlighting strengths and weaknesses. We also propose a taxonomy which classifies algorithms based on their approach. Both taxonomy and criteria are fruitfully exploited for providing input for new forthcoming research in the area