A fundamental challenge for current research on speech science and technology is
understanding and modeling individual variation in spoken language. Individuals have their …

Automatic Dialect Identification has attracted researchers in the field of speech signal
processing. Dialect can be defined as the language characteristics of a specific community …

In the domain of speech recognition many methods have been proposed over time like
Gaussian mixture models (GMM), GMM with universal background model (GMM-UBM …

Abstract i-Vector based recognition is a well-established technique in state-of-the-art
speaker and language recognition but its use in dialect and accent classification has …

In this paper, investigation of the significance of spectral and prosodic behaviors of speech
signal has been carried out for dialect identification. Spectral features such as cepstral …

We propose a unified approach to automatic foreign accent recognition. It takes advantage
of recent technology advances in both linguistics and acoustics based modeling techniques …

The Algerian linguistic situation is very intricate due to the ethnic, geographical and colonial
occupation influences which have lead to a complex sociolinguistic environment. As a result …

In this paper, an automatic dialect identification (ADI) system is proposed by extracting
spectral and prosodic features for Kannada language. A new dialect dataset is collected …

We describe a new approach to automatic dialect and accent recognition which exceeds
state-of-the-art performance in three recognition tasks. This approach improves the accuracy …

In this work, we propose a framework that automatically discovers dialect-specific phonetic
rules. These rules characterize when certain phonetic or acoustic transformations occur …