AIMC Topic: Phonetics

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Brain-to-text decoding with context-aware neural representations and large language models.

Journal of neural engineering
. Decoding attempted speech from neural activity offers a promising avenue for restoring communication abilities in individuals with speech impairments. Previous studies have focused on mapping neural activity to text using phonemes as the intermedia...

Wordsworth: A generative word dataset for comparison of speech representations in humans and neural networks.

Scientific data
Speech perception is fundamental for human communication, but its neural basis is not well understood. Furthermore, while modern neural networks (NNs) can accurately recognize speech, whether they effectively model human speech processing remains unc...

Research on optimal deep learning modeling in HaiNan dialect recognition.

Scientific reports
The speech recognition task of the HaiNan dialect faces significant differences in phonology, intonation, and grammatical structure among dialects, which in turn show significant regionalization characteristics, which makes the task of dialect-to-Man...

A dataset for recognition of Arabic accents from spoken L2 English speech (ArL2Eng).

Scientific data
This paper introduces the ArL2Eng dataset, a speech corpus of L2 English produced by native speakers of Arabic, and highlights its potential in supporting research into automated language assessment. ArL2Eng comprises audio sequences from speakers of...

Evaluating Mandarin tone pronunciation accuracy for second language learners using a ResNet-based Siamese network.

Scientific reports
Evaluating tone pronunciation is essential for helping second-language (L2) learners master the intricate nuances of Mandarin tones. This article introduces an innovative automatic evaluation method for Mandarin tone pronunciation that employs a Siam...

A study on phonemes recognition method for Mandarin pronunciation based on improved Zipformer-RNN-T(Pruned) modeling.

PloS one
In recent years, empowered by artificial intelligence technologies, computer-assisted language learning systems have gradually become a hot topic of research. Currently, the mainstream pronunciation assessment models rely on advanced speech recogniti...

Does Musical Experience Facilitate Phonetic Accommodation During Human-Robot Interaction?

Journal of speech, language, and hearing research : JSLHR
PURPOSE: This study investigated the effect of musical training on phonetic accommodation in a second language (L2) after interacting with a social robot, exploring the motivations and reasons behind their accommodation strategies.

A Tunable Forced Alignment System Based on Deep Learning: Applications to Child Speech.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Phonetic forced alignment has a multitude of applications in automated analysis of speech, particularly in studying nonstandard speech such as children's speech. Manual alignment is tedious but serves as the gold standard for clinical-grade ...

Effective Phoneme Decoding With Hyperbolic Neural Networks for High-Performance Speech BCIs.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
OBJECTIVE: Speech brain-computer interfaces (speech BCIs), which convert brain signals into spoken words or sentences, have demonstrated great potential for high-performance BCI communication. Phonemes are the basic pronunciation units. For monosylla...

The Mason-Alberta Phonetic Segmenter: a forced alignment system based on deep neural networks and interpolation.

Phonetica
Given an orthographic transcription, forced alignment systems automatically determine boundaries between segments in speech, facilitating the use of large corpora. In the present paper, we introduce a neural network-based forced alignment system, the...