paper-with-me

Papers

Dhvani: A Weakly-supervised Phonemic Error Detection and Personalized Feedback System for Hindi

2025-06-02 · Arnav Rustagi, Satvik Bajpai, Nimrat Kaur, Siddharth Siddharth

Computer-Assisted Pronunciation Training (CAPT) has been extensively studied for English. However, there remains a critical gap in its application to Indian languages with a base of 1.5 billion speakers. Pronunciation tools tailored to Indian languages are strikingly lacking despite the fact that millions learn them every year. With over 600 million speakers and being the fourth most-spoken language worldwide, improving Hindi pronunciation is a vital first step toward addressing this gap. This paper proposes 1) Dhvani -- a novel CAPT system for Hindi, 2) synthetic speech generation for Hindi mispronunciations, and 3) a novel methodology for providing personalized feedback to learners. While the system often interacts with learners using Devanagari graphemes, its core analysis targets phonemic distinctions, leveraging Hindi's highly phonetic orthography to analyze mispronounced speech and provide targeted feedback.

📄 PDF Abstract BibTeX arXiv:2506.02166

Code (0)

등록된 구현이 없습니다.

Methods 이 논문이 사용한 방법론

BASE 설명 없음

Similar Papers 제목 키워드 기반

Goodness-of-pronunciation without phoneme time alignment

2026-03-26 · Jeremy H. M. Wong, Nancy F. Chen arxiv

In speech evaluation, an Automatic Speech Recognition (ASR) model often computes time boundaries and phoneme posteriors for input features. However, limited data for ASR training hinders expansion of speech evaluation to…

Speech Recognition

SCaLa: Supervised Contrastive Learning for End-to-End Speech Recognition

2021-10-08 · Li Fu, Xiaoxiao Li, Runyu Wang, Lu Fan 외

End-to-end Automatic Speech Recognition (ASR) models are usually trained to optimize the loss of the whole token sequence, while neglecting explicit phonemic-granularity supervision. This could result in recognition erro…

Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Contrastive LearningRepresentation Learning+2

WeText: Scene Text Detection under Weak Supervision

2017-10-13 · ICCV 2017 10 · Shangxuan Tian, Shijian Lu, Chongshou Li

The requiring of large amounts of annotated training data has become a common constraint on various deep learning systems. In this paper, we propose a weakly supervised scene text detection method (WeText) that trains ro…

Scene Text DetectionText DetectionWeakly-supervised Learning

Sparse Coding-inspired GAN for Weakly Supervised Hyperspectral Anomaly Detection

2021-01-01 · Tao Jiang, Weiying Xie, Jie Lei, Yunsong Li 외

Anomaly detection (AD) on hyperspectral images (HSIs) is of great importance in both space exploration and earth observations. However, the challenges caused by insufficient datasets, no labels, and noise corruption subs…

Anomaly DetectionDecoderGenerative Adversarial NetworkWeakly-supervised Learning

MARTA: a model for the automatic phonemic grouping of the parkinsonian speech

2024-03-19 · techrxiv 2024 3 · Alejandro Guerrero-López, Julián D. Arias-Londoño, Stefanie Shattuck-Hufnagel, Juan I. Godino-Llorente

Parkinson's disease significantly impacts speech, particularly affecting phonemic groups like stop-plosives, fricatives, and affricates. However, its objective impact on the different phonemic groups has been briefly add…

BenchmarkingClassificationMetric Learning