Evaluating the Impact of Discriminative and Generative E2E Speech Enhancement Models on Syllable Stress Preservation

RS Bharadwaj, J Mallela, SH Aluru, C Yarra - arXiv preprint arXiv …, 2024 - arxiv.org
Automatic syllable stress detection is a crucial component in Computer-Assisted Language
Learning (CALL) systems for language learners. Current stress detection models are …

[PDF][PDF] Post-Net: A linguistically inspired sequence-dependent transformed neural architecture for automatic syllable stress detection

SH Aluru, J Mallela, C Yarra - Proc. Interspeech 2024, 2024 - isca-archive.org
Automatic syllable stress detection methods typically consider syllable-level features as
independent. However, as per linguistic studies, there is a dependency among the syllables …

[PDF][PDF] A comparative analysis of sequential models that integrate syllable dependency for automatic syllable stress detection

J Mallela, SH Aluru, C Yarra - Proc. Interspeech 2024, 2024 - isca-archive.org
Automatic syllable stress detection is typically operated at syllable level with stress-related
acoustic features. The stress placed on a syllable is influenced not only by its own …

A Preliminary Analysis of Automatic Word and Syllable Prominence Detection in Non-Native Speech With Text-to-Speech Prosody Embeddings

A Mondal, RS Bharadwaj, J Mallela… - arXiv preprint arXiv …, 2024 - arxiv.org
Automatic detection of prominence at the word and syllable-levels is critical for building
computer-assisted language learning systems. It has been shown that prosody embeddings …

A Comparison of Learned Representations with Jointly Optimized VAE and DNN for Syllable Stress Detection

J Mallela, PS Boyina, C Yarra - International Conference on Speech and …, 2023 - Springer
Automatic syllable stress detection is helpful in assessing L2 learners' pronunciation. In this
work, for stress detection, we propose a representation learning framework by jointly …

An end-to-end approach for lexical stress detection based on transformer

Y Ruan, X Wang, H Liu, Z Ou, Y Gao, J Cheng… - arXiv preprint arXiv …, 2019 - arxiv.org
The dominant automatic lexical stress detection method is to split the utterance into syllable
segments using phoneme sequence and their time-aligned boundaries. Then we extract …

Exploring the Use of Self-Supervised Representations for Automatic Syllable Stress Detection

J Mallela, SH Aluru, C Yarra - 2024 National Conference on …, 2024 - ieeexplore.ieee.org
The task of automatically detecting syllable stress is a key module in computer-assisted
language learning systems. There are numerous studies proposed in the literature for …