Whether the Support Region of Three-Bit Uniform Quantizer Has a Strong Impact on Post-Training Quantization for MNIST Dataset?

Driven by the need for the compression of weights in neural networks (NNs), which is especially beneficial for edge devices with a constrained resource, and by the need to utilize the simplest possible quantization model, in this paper, we study the performance of three-bit post-training uniform quantization. The goal is to put various choices of the key parameter of the quantizer in question (support region threshold) in one place and provide a detailed overview of this choice's impact on the performance of post-training quantization for the MNIST dataset. Specifically, we analyze whether it is possible to preserve the accuracy of the two NN models (MLP and CNN) to a great extent with the very simple three-bit uniform quantizer, regardless of the choice of the key parameter. Moreover, our goal is to answer the question of whether it is of the utmost importance in post-training three-bit uniform quantization, as it is in quantization, to determine the optimal support region threshold value of the quantizer to achieve some predefined accuracy of the quantized neural network (QNN). The results show that the choice of the support region threshold value of the three-bit uniform quantizer does not have such a strong impact on the accuracy of the QNNs, which is not the case with two-bit uniform post-training quantization, when applied in MLP for the same classification task. Accordingly, one can anticipate that due to this special property, the post-training quantization model in question can be greatly exploited.

Sensorimotor coupling in music and the psychology of the groove.

The urge to move in response to music, combined with the positive affect associated with the coupling of sensory and motor processes while engaging with music (referred to as sensorimotor coupling) in a seemingly effortless way, is commonly described as the feeling of being in the groove. Here, we systematically explore this compelling phenomenon in a population of young adults. We utilize multiple levels of analysis, comprising phenomenological, behavioral, and computational techniques. Specifically, we show (a) that the concept of the groove is widely appreciated and understood in terms of a pleasurable drive toward action, (b) that a broad range of musical excerpts can be appraised reliably for the degree of perceived groove, (c) that the degree of experienced groove is inversely related to experienced difficulty of bimanual sensorimotor coupling under tapping regimes with varying levels of expressive constraint, (d) that high-groove stimuli elicit spontaneous rhythmic movements, and (e) that quantifiable measures of the quality of sensorimotor coupling predict the degree of experienced groove. Our results complement traditional discourse regarding the groove, which has tended to take the psychological phenomenon for granted and has focused instead on the musical and especially the rhythmic qualities of particular genres of music that lead to the perception of groove. We conclude that groove can be treated as a psychological construct and model system that allows for experimental exploration of the relationship between sensorimotor coupling with music and emotion.

Beyond the beat: modeling metric structure in music and performance.

Current models for capturing metric structure of recordings of music are concerned primarily with the task of tempo and beat estimation. Even though these models have the potential for extracting other metric and rhythmic information, this potential has not been realized. In this paper, a model for describing the general metric structure of audio signals and behavioral data is presented. This model employs reson filters, rather than the comb filters used in earlier models. The oscillatory nature of reson filters is investigated, as they may be better suited for extracting multiple metric levels in the onset patterns of acoustic signals. The model is tested with several types of sequences of Dirac impulses as inputs, in order to investigate the model's sensitivity to timing variations and accent structure. The model's responses to natural stimuli are illustrated, both for excerpts of recorded music from a large database utilized by tempo-estimation models, and sequences of taps from a bimanual tapping task. Finally, the relationship of the model to several other beat-finding and rhythm models is discussed, and several applications and extensions for the model are suggested.

Characterization of music-evoked autobiographical memories.

Despite music's prominence in Western society and its importance to individuals in their daily lives, very little is known about the memories and emotions that are often evoked when hearing a piece of music from one's past. We examined the content of music-evoked autobiographical memories (MEAMs) using a novel approach for selecting stimuli from a large corpus of popular music, in both laboratory and online settings. A set of questionnaires probed the cognitive and affective properties of the evoked memories. On average, 30% of the song presentations evoked autobiographical memories, and the majority of songs also evoked various emotions, primarily positive, that were felt strongly. The third most common emotion was nostalgia. Analyses of written memory reports found both general and specific levels of autobiographical knowledge to be represented, and several social and situational contexts for memory formation were common across many memories. The findings indicate that excerpts of popular music serve as potent stimuli for studying the structure of autobiographical memories.

Ensemble: a web-based system for psychology survey and experiment management.

We provide a description of Ensemble, a suite of Web-integrated modules for managing and analyzing data associated with psychology experiments in a small research lab. The system delivers interfaces via a Web browser for creating and presenting simple surveys without the need to author Web pages and with little or no programming effort. The surveys may be extended by selecting and presenting auditory and/or visual stimuli with MATLAB and Flash to enable a wide range of psychophysical and cognitive experiments which do not require the recording of precise reaction times. Additionally, one is provided with the ability to administer and present experiments remotely. The software technologies employed by the various modules of Ensemble are MySQL, PHP, MATLAB, and Flash. The code for Ensemble is open source and available to the public, so that its functions can be readily extended by users. We describe the architecture of the system, the functionality of each module, and provide basic examples of the interfaces.