Pitch Sequences Research Articles

Effect of stimulus type and pitch salience on pitch-sequence processing.

Using a same-different discrimination task, it has been shown that discrimination performance for sequences of complex tones varying just detectably in pitch is less dependent on sequence length (1, 2, or 4 elements) when the tones contain resolved harmonics than when they do not [Cousineau, Demany, and Pessnitzer (2009). J. Acoust. Soc. Am. 126, 3179-3187]. This effect had been attributed to the activation of automatic frequency-shift detectors (FSDs) by the shifts in resolved harmonics. The present study provides evidence against this hypothesis by showing that the sequence-processing advantage found for complex tones with resolved harmonics is not found for pure tones or other sounds supposed to activate FSDs (narrow bands of noise and wide-band noises eliciting pitch sensations due to interaural phase shifts). The present results also indicate that for pitch sequences, processing performance is largely unrelated to pitch salience per se: for a fixed level of discriminability between sequence elements, sequences of elements with salient pitches are not necessarily better processed than sequences of elements with less salient pitches. An ideal-observer model for the same-different binary-sequence discrimination task is also developed in the present study. The model allows the computation of d' for this task using numerical methods.

Neural Integration of Stimulus History Underlies Prediction for Naturalistically Evolving Sequences.

Forming valid predictions about the environment is crucial to survival. However, whether humans are able to form valid predictions about natural stimuli based on their temporal statistical regularities remains unknown. Here, we presented subjects with tone sequences with pitch fluctuations that, over time, capture long-range temporal dependence structures prevalent in natural stimuli. We found that subjects were able to exploit such naturalistic statistical regularities to make valid predictions about upcoming items in a sequence. Magnetoencephalography (MEG) recordings revealed that slow, arrhythmic cortical dynamics tracked the evolving pitch sequence over time such that neural activity at a given moment was influenced by the pitch of up to seven previous tones. Importantly, such history integration contained in neural activity predicted the expected pitch of the upcoming tone, providing a concrete computational mechanism for prediction. These results establish humans' ability to make valid predictions based on temporal regularities inherent in naturalistic stimuli and further reveal the neural mechanisms underlying such predictive computation.SIGNIFICANCE STATEMENT A fundamental question in neuroscience is how the brain predicts upcoming events in the environment. To date, this question has primarily been addressed in experiments using relatively simple stimulus sequences. Here, we studied predictive processing in the human brain using auditory tone sequences that exhibit temporal statistical regularities similar to those found in natural stimuli. We observed that humans are able to form valid predictions based on such complex temporal statistical regularities. We further show that neural response to a given tone in the sequence reflects integration over the preceding tone sequence and that this history dependence forms the foundation for prediction. These findings deepen our understanding of how humans form predictions in an ecologically valid environment.

Trajectory Planning and Control of a Quadrotor Choreography for Real-Time Artist-in-the-Loop Performances

This paper proposes a systematic methodology for the guidance, control, and navigation of a quadrotor to perform a choreographed dance in real-time as a function of, and interacting with, the music performed by an artist-in-the-loop. This methodology allows for a real-time interaction with improvized music by an artist based on the pitch of the acoustic signal being played without prior knowledge of the music. The four main components of a human choreography (namely, the notions of space, shape, time and structure) are analyzed and mathematically formulated for a robotic performance. A new approach for mapping music features to trajectory parameters is proposed, as well as the design of a trajectory shaping filter based on two coefficients that are set in real-time by an artist through a MIDI foot-pedal board. The proposed approach maps motion parameters and the music to trajectory motifs that are then switched in harmony with the chord structure. The overall system is validated in a hardware-in-the-loop simulation where the hardware will consist of the musical instrument and the foot pedals. In the simulation, the trajectory generator system is inverted to generate a sequence of music pitches from the actual trajectory of the quadrotor. The music generated by the quadrotor is then played back to the musician allowing for real-time interaction. The simulation results show that the proposed methodology yields an effective performance for a quadrotor choreography based on the real-time interaction with a musician. The proposed system was successfully used by an artist as can be seen in a video link to the work described in this paper and listed in the conclusions.

Cross-range scaling of inverse synthetic aperture radar images with complex moving targets based on parameter estimation

To solve the problem of ISAR imaging cross-range scaling of complex motion of target, this paper analyzes kinetic mechanism of complex motion of the target. The motion forms will produce different Doppler frequency if the target is different. For 2D rotation target, the proportion of azimuth angle and pitch angle keeps constant, and the synthetic rotation vector is polynomial function of time. This paper takes “Matching Fourier Transform Algorithm” as the processing method to estimate the motion parameters of target. Additionally, the simulated result indicates the effectiveness of algorithm. For 3D rotation target, the paper adopts “Target Observation Matrix Decomposition method” to obtain European calibrated viewing angle vector matrix, and further get azimuth angle as well as pitch angle sequences of the target. Moreover, LS method is used for parameter estimation and the result is effective.

Audio-Based Melody Categorization: Exploring Signal Representations and Evaluation Strategies

AbstractMelody categorization refers to the task of grouping a set of melodies into categories of similar items that originate from the same melodic contour. From a computational perspective, automatic melody categorization is of crucial importance for the automatic organization of databases, as well as for large-scale musicological studies—in particular, in the context of folk music and non-Western music traditions. We investigate methods starting from the raw audio file. For each recording contained in a collection, we extract a pitch sequence representing the main melodic line. We then estimate pairwise similarities and evaluate the discriminative power of the resulting similarity matrix with respect to ground-truth annotations. We propose novel evaluation methodologies, compare melody representations, and explore the potential of our approach in the context of two applications: interstyle and intrastyle categorization of flamenco music and tune-family recognition of folk-song recordings.

Wa Language Syllables Classification by Support Vector Machine Based on Genetic Algorithm

In this paper, propose the method to classify Wa syllables by support vector machine (SVM) based on genetic algorithm (GA). Firstly, select all the Wa syllables from the speech corpus recorded. Secondly, extract pitch and formant frequencies by vowel main body extension method and linear predictive coding method respectively. Thirdly, describe every syllable with a 12-dimensional feature vector composed of its mean values, minima and maxima, belonging to its pitch frequency sequence and its first three formant frequency sequences respectively. Fourthly, divide the obtained data set into training set and test set, the former use to train SVM, and the latter test SVM. Fifthly, normalize data set into [0,1], and select the radial basis function as kernel function. Finally, use the K crossover validation method (K-CV) based on genetic algorithm (GA) to get the best parameter values train SVM. As a result, the predictive accuracy of Wa syllables classification by test set arrives at 84.83%, which has shown that the proposed method is effective and feasible on Wa syllables classification.

Shared structuring resources across domains: double task effects from linguistic processing on the structural integration of pitch sequences.

Many studies have reported evidence suggesting that resources involved in linguistic structural processing might be domain-general by demonstrating interference from simultaneously presented non-linguistic stimuli on the processing of sentences (Slevc, Rosenberg, & Patel, 2009 ). However, the complexity of the analysed linguistic processes often precludes the interpretation of such interference as being based on structural-rather than more general-processing resources (Perruchet & Poulin-Charronnat, 2013 ). We therefore used linguistic structure as a source of interference for another structural processing task, by asking participants to read sentences while processing experimentally manipulated pitch sequences. Half of the sentences contained a segment with either an "out-of-context" sentential violation or a "garden path" unexpectancy. Furthermore, the pitch sequences contained a cluster shift, which did or did not align with the sentential unexpectancies. A two-tone recognition task followed each pitch sequence, providing an index of the strength with which this structural boundary was processed. When a "garden path" unexpectancy (requiring structural reintegration) accompanied the cluster shift, the structural boundary induced by this shift was processed more shallowly. No such effect occurred with non-reintegratable "out-of-context" sentential violations. Furthermore, the discussed interference effect can be isolated from general pitch recognition performance, supporting the interpretation of such interference as being based on overlapping structural processing resources (Kljajevic, 2010 ; Patel, 2003 ).

A predictive model for analysing the starting pitchers’ performance using time series classification methods

Pitcher’s performance is a key factor for winning or losing baseball games. Predicting when a starting pitcher will enter into an unfortunate pitching sequence is one of the most difficult decision-making problems for baseball managers. Since 2007, vast amounts of pitch-by-pitch records are available for free via the PITCHf/x system, but obtaining useful knowledge from this huge amount of data is a complex task. In this paper, we propose a novel model for analysing the performance of starting pitchers, determining when they should be removed from the game and replaced by a reliever. Our approach represents pitch-by-pitch sequences as time series data using baseball’s linear runs and builds an instance-based model that learns from past experience using the k-Nearest Neighbours classification method. In order to compare time series of pitcher’s performance, Dynamic Time Warping is used as the dissimilarity measure in conjunction with the Keogh’s lower bound technique. We validate the proposed model using real data from 20 Major League Baseball starting pitchers during the 2009 regular season. The experimental results show a good performance of the predictive model for all pitchers; with values of Precision, Recall and F1 near to 0.9 when the outcomes of their last 10 throws are unknown.

Using PITCHf/x to model the dependence of strikeout rate on the predictability of pitch sequences

Using PITCHf/x to model the dependence of strikeout rate on the predictability of pitch sequences

An Automatic Synthesis of Musical Phrases from Multi-Pitch Samples

Abstract Sound synthesizers are a natural element of a musician’s toolset. In music arrangement, samplers can often produce satisfactory results, but it requires a combination of manual and automatic methods that may be arduous at times. Concatenative Sound Synthesis reproduces many of natural performance- and expression-related nuances but at a cost of high demand for processing power. Here, another method of musical phrase synthesis aimed at music arrangement is presented that addresses these and other related issues. Contrary to common practice, we propose to record and utilize sound samples containing not one,but short sequences of pitches. In effect, natural pitch transitions are preserved and phrases appear to be much smoother, despite using very limited set of performance rules. The proof-of-concept implementation of the proposed method is discussed in detail along with attempts at optimizing the final sound effects, based on auditory tests. The limitations and future applications of the synthesizer are also discussed.

Functional neuroanatomy of speech signal decoding in primary progressive aphasias

The pathophysiology of primary progressive aphasias remains poorly understood. Here, we addressed this issue using activation fMRI in a cohort of 27 patients with primary progressive aphasia (nonfluent, semantic, and logopenic variants) versus 15 healthy controls. Participants listened passively to sequences of spoken syllables in which we manipulated 3-key auditory speech signal characteristics: temporal regularity, phonemic spectral structure, and pitch sequence entropy. Relative to healthy controls, nonfluent variant patients showed reduced activation of medial Heschl's gyrus in response to any auditory stimulation and reduced activation of anterior cingulate to temporal irregularity. Semantic variant patients had relatively reduced activation of caudate and anterior cingulate in response to increased entropy. Logopenic variant patients showed reduced activation of posterior superior temporal cortex to phonemic spectral structure. Taken together, our findings suggest that impaired processing of core speech signal attributes may drive particular progressive aphasia syndromes and could index a generic physiological mechanism of reduced computational efficiency relevant to all these syndromes, with implications for development of new biomarkers and therapeutic interventions.

A Dynamical Model of Pitch Memory Provides an Improved Basis for Implied Harmony Estimation.

Tonal melody can imply vertical harmony through a sequence of tones. Current methods for automatic chord estimation commonly use chroma-based features extracted from audio signals. However, the implied harmony of unaccompanied melodies can be difficult to estimate on the basis of chroma content in the presence of frequent nonchord tones. Here we present a novel approach to automatic chord estimation based on the human perception of pitch sequences. We use cohesion and inhibition between pitches in auditory short-term memory to differentiate chord tones and nonchord tones in tonal melodies. We model short-term pitch memory as a gradient frequency neural network, which is a biologically realistic model of auditory neural processing. The model is a dynamical system consisting of a network of tonotopically tuned nonlinear oscillators driven by audio signals. The oscillators interact with each other through nonlinear resonance and lateral inhibition, and the pattern of oscillatory traces emerging from the interactions is taken as a measure of pitch salience. We test the model with a collection of unaccompanied tonal melodies to evaluate it as a feature extractor for chord estimation. We show that chord tones are selectively enhanced in the response of the model, thereby increasing the accuracy of implied harmony estimation. We also find that, like other existing features for chord estimation, the performance of the model can be improved by using segmented input signals. We discuss possible ways to expand the present model into a full chord estimation system within the dynamical systems framework.

New Hybrid Genetic Algorithm for Pitch Sequence Optimization of CVT Variator Chain

New Hybrid Genetic Algorithm for Pitch Sequence Optimization of CVT Variator Chain

Melody extraction from music using modified group delay functions

Modified group delay based algorithms for estimation of melodic pitch sequences from heterphonic/polyphonic music are discussed in this paper. Two different variants of the modified group delay function are proposed, namely, (a) system based--MODGD (Direct) and (b) source based--MODGD (Source). In (a) the standard modified group delay function (MODGDF) is used to estimate prominent melodic pitch ($$f_0$$f0), which appears like a low frequency formant in the MODGDF spectrum. In (b), the power spectrum of the signal is first flattened to emphasise the source. The flattened power spectrum behaves like a sinusoid in noise, the frequency of the sinusoid being related to the pitch frequency. The modified group delay function of this signal produces peaks at $$T_0$$T0, $$2T_0, \ldots ,$$2T0,ź, where $$T_0=\frac{1}{f_0}$$T0=1f0. Continuity constraints in a dynamic programming framework are imposed across frames to reduce octave errors. Sudden changes in pitch are accommodated by changing the frame size dynamically using a multi-resolution framework. The performance of the proposed systems was evaluated on four datasets: ADC-2004, LabROSA, MIREX-2008 and Carnatic music dataset. The performance of the proposed approaches demonstrate the potential of the group delay based methods for melody extraction.

Interference in memory for pitch-only and rhythm-only sequences

In human memory, the ability to recognize a previously encountered stimulus often undergoes cumulative interference when the number of intervening items between its first and second presentation increases. Although this is a common effect in many domains, melodies composed in tuning systems familiar to participants (e.g., Western tonal music) do not seem to suffer such cumulative decrements in recognition performance. Interestingly, melodies in unfamiliar tuning systems do show cumulative decrements. This finding has been predicted by a novel Regenerative Multiple Representations (RMR) conjecture. The present study further explores this phenomenon and the conjecture by investigating pitch-only (isochronous rhythm) and rhythm-only (monotone pitch) sequences of melodies in an unfamiliar tuning system that previously showed cumulative disruptive effects. Experiment 1 replicated previous studies reporting significant interference effects from the number of intervening items when melodies use uncommon rhythms and are composed in an unfamiliar tuning system. Furthermore, as predicted by the RMR conjecture, when rhythmic information was neutralized (Experiment 2), the cumulative interference related to the number of intervening items was retained. This was also the case when the original pitch information of each melody was neutralized, leaving variation only in the rhythmic information (Experiment 3). Results are discussed in the context of the RMR conjecture: given converse results, the conjecture would have been falsified. However, it currently remains plausible and appears to be a useful tool for precise predictions about the link between prior experience, perception, and formation of new memories.

Algorithmically-generated Corpora that use Serial Compositional Principles Can Contribute to the Modeling of Sequential Pitch Structure in Non-tonal Music

We investigate whether pitch sequences in non-tonal music can be modeled by an information-theoretic approach using algorithmically-generated melodic sequences, made according to 12-tone serial principles, as the training corpus. This is potentially useful, because symbolic corpora of non-tonal music are not readily available. A non-tonal corpus of serially-composed melodies was constructed algorithmically using classic principles of 12-tone music, including prime, inversion, retrograde and retrograde inversion transforms. A similar algorithm generated a tonal melodic corpus of tonal transformations, in each case based on a novel tonal melody and expressed in alternating major keys. A cognitive model of auditory expectation (IDyOM) was used first to analyze the sequential pitch structure of the corpora, in some cases with pre-training on established tonal folk-song corpora (Essen, Schaffrath, 1995). The two algorithmic corpora can be distinguished in terms of their information content, and they were quite different from random corpora and from the folk-song corpus. We then demonstrate that the algorithmic serial corpora can assist modeling of canonical non-tonal compositions by Webern and Schoenberg, and also non-tonal segments of improvisations by skilled musicians. Separately, we developed the process of algorithmic melody composition into a software system (the Serial Collaborator) capable of generating multi-stranded serial keyboard music. Corpora of such keyboard compositions based either on the non-tonal or the tonal melodic corpora were generated and assessed for their information-theoretic modeling properties.

Neural correlates of auditory scale illusion

The auditory illusory perception “scale illusion” occurs when ascending and descending musical scale tones are delivered in a dichotic manner, such that the higher or lower tone at each instant is presented alternately to the right and left ears. Resulting tone sequences have a zigzag pitch in one ear and the reversed (zagzig) pitch in the other ear. Most listeners hear illusory smooth pitch sequences of up-down and down-up streams in the two ears separated in higher and lower halves of the scale. Although many behavioral studies have been conducted, how and where in the brain the illusory percept is formed have not been elucidated. In this study, we conducted functional magnetic resonance imaging using sequential tones that induced scale illusion (ILL) and those that mimicked the percept of scale illusion (PCP), and we compared the activation responses evoked by those stimuli by region-of-interest analysis. We examined the effects of adaptation, i.e., the attenuation of response that occurs when close-frequency sounds are repeated, which might interfere with the changes in activation by the illusion process. Results of the activation difference of the two stimuli, measured at varied tempi of tone presentation, in the superior temporal auditory cortex were not explained by adaptation. Instead, excess activation of the ILL stimulus from the PCP stimulus at moderate tempi (83 and 126 bpm) was significant in the posterior auditory cortex with rightward superiority, while significant prefrontal activation was dominant at the highest tempo (245 bpm). We suggest that the area of the planum temporale posterior to the primary auditory cortex is mainly involved in the illusion formation, and that the illusion-related process is strongly dependent on the rate of tone presentation.

The Influence of Contextual Cues on Cultural Bias in Music Memory

We have ample evidence of cultural bias influencing music cognition in a variety of ways including memory. The purpose of this study was to explore the influence of various musical elements on Western-born listeners’ cross-cultural recognition memory performance. Specifically, we were interested in whether the enculturation effect found in previous studies would be observed when tuning, timbre, texture, and rhythm were equalized in the presentation of music from two different cultures. In addition we wanted to explore the possible influence of music preference on recognition memory performance. Listeners were randomly assigned to hear Western and Turkish music in one of three musical context conditions (full, monophonic, isochronous) and subsequently tested on their recognition memory. Results indicated that memory performance was superior for in-culture music regardless of contextual condition, with no significant correlation between preference and memory performance. This points to the statistical properties of pitch sequences as a possible source of culturally biased responses in music listening.

Evaluation and combination of pitch estimation methods for melody extraction in symphonic classical music

The extraction of pitch information is arguably one of the most important tasks in automatic music description systems. However, previous research and evaluation datasets dealing with pitch estimation focused on relatively limited kinds of musical data. This work aims to broaden this scope by addressing symphonic western classical music recordings, focusing on pitch estimation for melody extraction. This material is characterized by a high number of overlapping sources, and by the fact that the melody may be played by different instrumental sections, often alternating within an excerpt. We evaluate the performance of eleven state-of-the-art pitch salience functions, multipitch estimation and melody extraction algorithms when determining the sequence of pitches corresponding to the main melody in a varied set of pieces. An important contribution of the present study is the proposed evaluation framework, including the annotation methodology, generated dataset and evaluation metrics. The results show that the assumptions made by certain methods hold better than others when dealing with this type of music signal, leading to a better performance. Additionally, we propose a simple method for combining the output of several algorithms, with promising results.

Relationship of working memory to the effect of listener training on pitch and rhythm perception

Experience and training can affect discrimination of tonal sequences. Recent work has demonstrated differences in processing multidimensional tonal sequences defined both by pitch contour and sequence rhythm. With groups defined by skill level on a pattern reconstruction task, a significant interaction between group and sequence-task condition suggested a difference in the manner of integration of pitch and rhythm information, with the poorer performing group showing greater integration across dimensions. Current work investigated the effect of training over sessions on pitch and rhythm processing of four-tone sequences by trained musicians and audio-arts students experienced in critical listening. Sequence tones either had a fixed duration (212 ms) with frequency randomly selected from a logarithmically scaled distribution (400–1750 Hz), a fixed frequency (837 Hz) with a randomly selected logarithmically scaled duration (75–600 ms), or a random frequency and duration. In initial conditions, the task was to assemble sequence elements to recreate the target sequence, whereas the later conditions required subjects to ignore extraneous changes in one dimension while reconstructing the target dimension. Trends suggest that training improves performance. Ongoing work is examining the relationship between performance on a number-letter sequencing task and integration of the pitch and rhythm information in tonal sequences.