Abstract Automatic Speech Recognition and its applications are rising in popularity across
applications with reasonable inference results. Recent state-of-the-art approaches, often …

The diverse nature of dialects presents challenges for models trained on specific linguistic
patterns, rendering them susceptible to errors when confronted with unseen or out-of …

This article examines the current state of speech recognition technologies in Bangla, which
is one of the Low Resource Languages (LRLs) spoken by a population of almost 185 million …

Byte pair encoding (BPE) emerges as an effective tokenization method for tackling the out-of-
vocabulary (OOV) challenge in various natural language and speech processing tasks …

Research on speech recognition has attracted considerable interest due to the difficult task
of segmenting uninterrupted speech. Among various languages, Bengali features distinct …

The application of several deep-learning approaches has led to remarkable improvements
in automatic speech recognition (ASR). In this paper, the authors transcribed recordings of …

The Bengali language, spoken in various regions of south-Asia and also among the Bengali
diaspora, exhibits rich diversity with regional dialects or variations that reflect the cultural …

Collection of health information from the underserved community has been a challenge.
Their health records are not digitized. The major population of the underserved community is …

This work introduces the performance comparison of two deep ASR models, Wav2Vec2 and
Whisper, in recognizing the Bengali language with complex linguistics, dialectal variations …