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Scheduled sampling is an effective method to alleviate the exposure bias problem of neural machine translation. It simulates the inference scene by randomly replacing ground-truth target input tokens with predicted ones during training.…

Computation and Language · Computer Science 2021-07-23 Yijin Liu , Fandong Meng , Yufeng Chen , Jinan Xu , Jie Zhou

Neural Language Models of Code, or Neural Code Models (NCMs), are rapidly progressing from research prototypes to commercial developer tools. As such, understanding the capabilities and limitations of such models is becoming critical.…

Software Engineering · Computer Science 2024-03-29 David N. Palacio , Alejandro Velasco , Nathan Cooper , Alvaro Rodriguez , Kevin Moran , Denys Poshyvanyk

Modern automatic speech recognition (ASR) systems have been observed to function better for certain speaker groups (SGs) than others, despite recent gains in overall performance. One potential impediment to progress towards fairer ASR is a…

Computation and Language · Computer Science 2026-04-27 Felix Herron , Solange Rossato , Alexandre Allauzen , François Portet

A population of firing neurons is expected to carry information not only by mean firing rate but also by fluctuation and synchrony among neurons. In order to examine this possibility, we have studied responses of neuronal ensembles to three…

Neurons and Cognition · Quantitative Biology 2009-11-13 Hideo Hasegawa

The goal of universal audio representation learning is to obtain foundational models that can be used for a variety of downstream tasks involving speech, music and environmental sounds. To approach this problem, methods inspired by works on…

Sound · Computer Science 2024-05-22 Leonardo Pepino , Pablo Riera , Luciana Ferrer

fMRI semantic category understanding using linguistic encoding models attempt to learn a forward mapping that relates stimuli to the corresponding brain activation. Classical encoding models use linear multi-variate methods to predict the…

Machine Learning · Computer Science 2018-12-04 Subba Reddy Oota , Adithya Avvaru , Naresh Manwani , Raju S. Bapi

Acoustic word embeddings (AWEs) aims to map a variable-length speech segment into a fixed-dimensional representation. High-quality AWEs should be invariant to variations, such as duration, pitch and speaker. In this paper, we introduce a…

Audio and Speech Processing · Electrical Eng. & Systems 2023-07-20 Jingru Lin , Xianghu Yue , Junyi Ao , Haizhou Li

Incoming sound is in cochlea and auditory nerve encoded into spike trains. At the third neuron of the auditory pathway, spike trains of the left and right sides are processed in brainstem nuclei to yield sound localization information. Two…

Neurons and Cognition · Quantitative Biology 2020-07-02 Petr Marsalek , Pavel Sanda , Zbynek Bures

Predictive processing has become an influential framework in cognitive sciences. This framework turns the traditional view of perception upside down, claiming that the main flow of information processing is realized in a top-down…

Robotics · Computer Science 2021-01-25 Alejandra Ciria , Guido Schillaci , Giovanni Pezzulo , Verena V. Hafner , Bruno Lara

Rhythm is a fundamental aspect of human behaviour, present from infancy and deeply embedded in cultural practices. Rhythm anticipation is a spontaneous cognitive process that typically occurs before the onset of actual beats. While most…

Neurons and Cognition · Quantitative Biology 2025-03-18 Zhongju Yuan , Geraint Wiggins , Dick Botteldooren

The Frequency Following Response (FFR) reflects the brain's neural encoding of auditory stimuli including speech. Because the fundamental frequency (F0), a physical correlate of pitch, is one of the essential features of speech, there has…

Machine learning algorithms have achieved superhuman performance in specific complex domains. However, learning online from few examples and compositional learning for efficient generalization across domains remain elusive. In humans, such…

Neurons and Cognition · Quantitative Biology 2024-11-11 V. A. Aksyuk

In this paper, we investigate the output token probability information in the output embedding of language models. We find an approximate common log-linear encoding of output token probabilities within the output embedding vectors and…

Computation and Language · Computer Science 2024-12-12 Hakaze Cho , Yoshihiro Sakai , Kenshiro Tanaka , Mariko Kato , Naoya Inoue

Neural network models using predictive coding are interesting from the viewpoint of computational modelling of human language acquisition, where the objective is to understand how linguistic units could be learned from speech without any…

Computation and Language · Computer Science 2020-07-09 María Andrea Cruz Blandón , Okko Räsänen

Encoding models provide a powerful framework for linking continuous stimulus features to neural activity; however, traditional voxelwise approaches are limited by measurement noise, inter-subject variability, and redundancy arising from…

Computation and Language · Computer Science 2026-04-29 Kamya Hari , Taha Binhuraib , Jin Li , Cory Shain , Anna A. Ivanova

Previous work has established that a person's demographics and speech style affect how well speech processing models perform for them. But where does this bias come from? In this work, we present the Speech Embedding Association Test…

Computation and Language · Computer Science 2023-10-31 Isaac Slaughter , Craig Greenberg , Reva Schwartz , Aylin Caliskan

This paper introduces the Procedural (audio) Variational autoEncoder (ProVE) framework as a general approach to learning Procedural Audio PA models of environmental sounds with an improvement to the realism of the synthesis while…

Sound · Computer Science 2023-03-07 Danzel Serrano , Mark Cartwright

Anticipated synchronization (AS) is a counter intuitive behavior that has been observed in several systems. When AS establishes in a sender-receiver configuration, the latter can predict the future dynamics of the former for certain…

Neurons and Cognition · Quantitative Biology 2017-05-31 Fernanda S. Matias , Pedro V. Carelli , Claudio R. Mirasso , Mauro Copelli

Building upon advancements in Large Language Models (LLMs), the field of audio processing has seen increased interest in training audio generation tasks with discrete audio token sequences. However, directly discretizing audio by neural…

Audio and Speech Processing · Electrical Eng. & Systems 2024-10-08 Wenrui Liu , Zhifang Guo , Jin Xu , Yuanjun Lv , Yunfei Chu , Zhou Zhao , Junyang Lin

Minimization of cortical prediction errors has been considered a key computational goal of the cerebral cortex underlying perception, action and learning. However, it is still unclear how the cortex should form and use information about…

Neurons and Cognition · Quantitative Biology 2025-04-07 Arno Granier , Mihai A. Petrovici , Walter Senn , Katharina A. Wilmes
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