Faster Sound Stream Segmentation In Musicians Than In Nonmusicians

The musician's brain is considered as a good model of brain plasticity as musical training is known to modify auditory perception and related cortical organization. Here, we show that music-related modifications can also extend beyond motor and auditory processing and generalize (transfer) to speech processing. Previous studies have shown that adults and newborns can segment a continuous stream of linguistic and non-linguistic stimuli based only on probabilities of occurrence between adjacent syllables, tones or timbres. The paradigm classically used in these studies consists of a passive exposure phase followed by a testing phase. By using both behavioural and electrophysiological measures, we recently showed that adult musicians and musically trained children outperform nonmusicians in the test following brief exposure to an artificial sung language. However, the behavioural test does not allow for studying the learning process per se but rather the result of the learning. In the present study, we analyze the electrophysiological learning curves that are the ongoing brain dynamics recorded as the learning is taking place. While musicians show an inverted U shaped learning curve, nonmusicians show a linear learning curve. Analyses of Event-Related Potentials (ERPs) allow for a greater understanding of how and when musical training can improve speech segmentation. These results bring evidence of enhanced neural sensitivity to statistical regularities in musicians and support the hypothesis of positive transfer of training effect from music to sound stream segmentation in general

Frequency shifting approach towards textual transcription of heartbeat sounds

Auscultation is an approach for diagnosing many cardiovascular problems. Automatic analysis of heartbeat sounds and extraction of its audio features can assist physicians towards diagnosing diseases. Textual transcription allows recording a continuous heart sound stream using a text format which can be stored in very small memory in comparison with other audio formats. In addition, a text-based data allows applying indexing and searching techniques to access to the critical events. Hence, the transcribed heartbeat sounds provides useful information to monitor the behavior of a patient for the long duration of time. This paper proposes a frequency shifting method in order to improve the performance of the transcription. The main objective of this study is to transfer the heartbeat sounds to the music domain. The proposed technique is tested with 100 samples which were recorded from different heart diseases categories. The observed results show that, the proposed shifting method significantly improves the performance of the transcription

From holism to compositionality: memes and the evolution of segmentation, syntax, and signification in music and language

Steven Mithen argues that language evolved from an antecedent he terms “Hmmmmm, [meaning it was] Holistic, manipulative, multi-modal, musical and mimetic”. Owing to certain innate and learned factors, a capacity for segmentation and cross-stream mapping in early Homo sapiens broke the continuous line of Hmmmmm, creating discrete replicated units which, with the initial support of Hmmmmm, eventually became the semantically freighted words of modern language. That which remained after what was a bifurcation of Hmmmmm arguably survived as music, existing as a sound stream segmented into discrete units, although one without the explicit and relatively fixed semantic content of language. All three types of utterance – the parent Hmmmmm, language, and music – are amenable to a memetic interpretation which applies Universal Darwinism to what are understood as language and musical memes. On the basis of Peter Carruthers’ distinction between ‘cognitivism’ and ‘communicativism’ in language, and William Calvin’s theories of cortical information encoding, a framework is hypothesized for the semantic and syntactic associations between, on the one hand, the sonic patterns of language memes (‘lexemes’) and of musical memes (‘musemes’) and, on the other hand, ‘mentalese’ conceptual structures, in Chomsky’s ‘Logical Form’ (LF)

Multisensory Congruency as a Mechanism for Attentional Control over Perceptual Selection

The neural mechanisms underlying attentional selection of competing neural signals for awareness remains an unresolved issue. We studied attentional selection, using perceptually ambiguous stimuli in a novel multisensory paradigm that combined competing auditory and competing visual stimuli. We demonstrate that the ability to select, and attentively hold, one of the competing alternatives in either sensory modality is greatly enhanced when there is a matching cross-modal stimulus. Intriguingly, this multimodal enhancement of attentional selection seems to require a conscious act of attention, as passively experiencing the multisensory stimuli did not enhance control over the stimulus. We also demonstrate that congruent auditory or tactile information, and combined auditory–tactile information, aids attentional control over competing visual stimuli and visa versa. Our data suggest a functional role for recently found neurons that combine voluntarily initiated attentional functions across sensory modalities. We argue that these units provide a mechanism for structuring multisensory inputs that are then used to selectively modulate early (unimodal) cortical processing, boosting the gain of task-relevant features for willful control over perceptual awareness

Rhythm and synchrony in animal movement and communication

Animal communication and motoric behavior develop over time. Often, this temporal dimension has communicative relevance and is organized according to structural patterns. In other words, time is a crucial dimension for rhythm and synchrony in animal movement and communication. Rhythm is defined as temporal structure at a second-millisecond time scale (Kotz et al. 2018). Synchrony is defined as precise co-occurrence of 2 behaviors in time (Ravignani 2017). Rhythm, synchrony, and other forms of temporal interaction are taking center stage in animal behavior and communication. Several critical questions include, among others: what species show which rhythmic predispositions? How does a species’ sensitivity for, or proclivity towards, rhythm arise? What are the species-specific functions of rhythm and synchrony, and are there functional trends across species? How did similar or different rhythmic behaviors evolved in different species? This Special Column aims at collecting and contrasting research from different species, perceptual modalities, and empirical methods. The focus is on timing, rhythm and synchrony in the second-millisecond range. Three main approaches are commonly adopted to study animal rhythms, with a focus on: 1) spontaneous individual rhythm production, 2) group rhythms, or 3) synchronization experiments. I concisely introduce them below (see also Kotz et al. 2018; Ravignani et al. 2018)

Action for perception : influence of handedness in visuo-auditory sensory substitution

In this preliminary study we address the question of the influence of handedness on the localization of targets perceived through a visuo-auditory substitution device. Participants hold the device in one hand in order to explore the environment and to perceive the target. They point to the estimated location of the target with the other hand. This preliminary results support our hypothesis that pointing is more accurate when the device is held in the right dominant hand. Dexterity has to be attributed to the active part of the perceptive system. This study has obviously to be completed but it shows how the concept of enaction is important and how it can be experimentaly addressed in the field of sensory substitution

Алгоритм определения высоты музыкального звука на основе подавления ложных пиков в спектре, построенном для темперированной музыкальной шкалы, и его практическое применение на примере программы музыкального секвенсора

Статья посвящена описанию алгоритма определения частоты основного тона музыкального звука, предполагающего подавление ложных пиков в спектре, построенном для темперированной музыкальной шкалы. Данный алгоритм был реализован в программе музыкального секвенсора с функцией распознавания звукового потока в реальном масштабе времени, описание которого также приводится в данной статье.Статтю присвячено опису алгоритму визначення основного тону музичного звуку, що передбачає зниження рівня хибних піків в спектрі, побудованому для темперованої музичної шкали. Даний алгоритм був реализований в програмі музичного секвенсора з функцією розпізнавання звукового потоку в реальному масштабі часу, опис якого також наведено в даній статті.The article is devoted to description of an algorithm for pitch extraction, which implies dumping of false peaks in equal-temperament-based spectra. The algorithm was employed within musical sequencer application with function for real time recognition of sound stream. The application structure is also described in this article

Long-term learning behavior in a recurrent neural network for sound recognition

In this paper, the long-term learning properties of an artificial neural network model, designed for sound recognition and computational auditory scene analysis in general, are investigated. The model is designed to run for long periods of time (weeks to months) on low-cost hardware, used in a noise monitoring network, and builds upon previous work by the same authors. It consists of three neural layers, connected to each other by feedforward and feedback excitatory connections. It is shown that the different mechanisms that drive auditory attention emerge naturally from the way in which neural activation and intra-layer inhibitory connections are implemented in the model. Training of the artificial neural network is done following the Hebb principle, dictating that "Cells that fire together, wire together", with some important modifications, compared to standard Hebbian learning. As the model is designed to be on-line for extended periods of time, also learning mechanisms need to be adapted to this. The learning needs to be strongly attention-and saliency-driven, in order not to waste available memory space for sounds that are of no interest to the human listener. The model also implements plasticity, in order to deal with new or changing input over time, without catastrophically forgetting what it already learned. On top of that, it is shown that also the implementation of shortterm memory plays an important role in the long-term learning properties of the model. The above properties are investigated and demonstrated by training on real urban sound recordings

Re-verification of a Lip Synchronization Algorithm using robust reachability

The timed automata formalism is an important model for specifying and analysing real-time systems. Robustness is the correctness of the model in the presence of small drifts on clocks or imprecision in testing guards. A symbolic algorithm for the analysis of the robustness of timed automata has been implemented. In this paper we re-analyse an industrial case lip synchronization protocol using the new robust reachability algorithm.This lip synchronization protocol is an interesting case because timing aspect are crucial for the correctness of the protocol. Several versions of the model are considered, with an ideal video stream, with anchored jitter, and with non-anchored jitter