Deep learning-based machine learning models have shown significant results in speech
recognition and numerous vision-related tasks. The performance of the present speech-to …

Speech processing is very important research area where speaker recognition, speech
synthesis, speech codec, speech noise reduction are some of the research areas. Many of …

Automatic Speech Recognition (ASR) has gained significant progress in technology as well
as in application. There exist vast performance gap between human speech recognition …

This paper introduces a novel method for identifying Assamese dialects by analyzing the
acoustic and prosodic aspects of vowel sounds in speech signals. The distinctive …

Speech is natural vocalized and primary means of communication. Speech is easy, hand-
free, fast and do not require any technical knowledge. Communicating with computer using …

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

Automatic speech recognition (ASR) has been extensively studied during the past few
decades. Today, most of the ASR system based on statistical modelling, and HMM is the …

Punjabi, Hindi, Marathi, Gujarati, Sindhi, Bengali, Nepali, Sinhala, Oriya, Assamese, Urdu
are prominent members of the family of Indo-Aryan languages. These languages are mainly …

In this paper, one of the acoustic units of speech, the syllable, is used for the development of
a continuous Hindi speech recognition system. The syllable is a larger acoustic unit that …

Despite the continuous progress of Automatic Speech recognition (ASR) technologies, these
systems for Indian languages are still in infancy stage due to a multitude of challenges …