3 accepted papers
Pre-trained transformer-based models have significantly advanced automatic speech recognition (ASR), yet they remain sensitive to accent and dialectal variations, resulting in elevated word error rates (WER) in linguistically diverse languages such as English and Persian. To address this challenge,…
Text-to-Speech (TTS) systems have made significant strides, enabling the generation of speech from grapheme sequences. However, for low-resource languages, these models still struggle to produce natural and intelligible speech. Grapheme-to-Phoneme conversion (G2P) addresses this challenge by enhanci…
I-vectors have proved to be the most effective features for text-independent speaker verification in recent researches. In this article a new scheme is proposed to utilize i-vectors in text-prompted speaker verification in a simple while effective manner. In order to examine this scheme empirically,…