Speech recognition of a language is a key area in the field of pattern recognition. This paper
presents a comprehensive survey on the speech recognition techniques for non-Indian and …

This paper proposes a multilingual acoustic modeling approach for Indian languages using
a Multitask Learning (MTL) framework. Language-specific phoneme recognition is explored …

Semi-supervised training and language adversarial transfer learning are two different
techniques to improve the Automatic Speech Recognition (ASR) performance in limited …

The goal of this work is to investigate the correlation between physiological process of
articulation and emotion expressing modes via speech of Mandarin Chinese. A bimodal …

Abstract Development of Large Vocabulary Continuous Speech Recognition (LVCSR)
system is a cumbersome task, especially for low resource languages. Urdu is the national …

Background: In India, thousands of languages or dialects are in use. Most Indian dialects are
low asset dialects. A well-performing Automatic Speech Recognition (ASR) system for Indian …

In this work, the performance of Multilingual Phone Recognition System (Multi-PRS) is
improved using articulatory features (AFs). Four Indian languages–Kannada, Telugu …

Call Centers have huge amount of audio data which can be used for achieving valuable
business insights and transcription of phone calls is manually tedious task. An effective …

Bengali is a prominent language of the Indian subcontinent. However, while many state-of-
the-art acoustic models exist for prominent languages spoken in the region, research and …

The presented work aims to implement speech recognition systems for Hindi and English
using advanced deep learning. Enhancing ASR technologies is crucial for improving digital …