Acoustic Analysis of the Speakers’ Variability for Regional Accent-Affected Pronunciation in Bangladeshi Bangla: A Study on Sylheti Accent

Shafkat Kibria,M Shahidur Rahman,M Zafar Iqbal,M Reza Selim

doi:10.1109/access.2020.2974799

Shafkat Kibria, M Shahidur Rahman + Show 2 more

Open Access

https://doi.org/10.1109/access.2020.2974799

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Journal: IEEE Access	Publication Date: Jan 1, 2020
Citations: 32	License type: CC BY 4.0

Affiliation: Shahjalal University of Science and Technology

Abstract

Accented pronunciation variability is one of the key elements that deteriorate the accuracy of the automatic speech recognition (ASR). This article reports the results of the acoustic analysis of the two groups of speakers’ variability caused by regional accent in Bangladeshi Bangla. The analysis considers the seven monophthongal and four diphthongal vowels of Bangla to investigate the acoustic characteristics of two groups of single-accent speakers and their correlation on the articulation of the Standard Colloquial Bangladeshi Bangla (SCBB). An accent is the speaker’s regional signature and shaped by his/her community and educational background. This study examines both male and female speakers from the Sylhet region, which has one of the extremely deviant dialects in Bangla, and comparatively less deviant speakers from different districts of North-West and Middle Part of Bangladesh. Accent-related acoustic features such as pitch slope, formant frequencies, and vowel duration have been considered to examine the prominent characteristics of the accents and to classify the accents from these features. Both gender groups are distinctly analyzed. It has been found that there are significant deviations in formant frequencies and various steepness of the rise/fall in pitch slope within accents of both gender groups. In this study, it has been observed that accent related changes in speech affect the ASR performance. This has emphasized the need for accent-specific acoustic models to handle the speakers from highly deviant dialects as well as considering the accent-affected speakers’ variability in the corpora development for robust ASR system in Bangladeshi Bangla.

Highlights

In Bengali or Bangla () language, there are many different accents among native speakers [2]
At the end of the article, we have reported the observation of the performance of two automatic speech recognition (ASR) systems on the accent groups
We have considered acoustic characteristics such as Formants frequencies (F1, F2, F3), Phone duration and rise/fall in the pitch slope for the regional accents classification using the four (4) machine learning (ML) methods

Summary

INTRODUCTION

) language, there are many different accents among native speakers [2]. Geographically, one can divide them in two major regions: people of Bangladesh and people of West Bengal (a part of India) [3]. There are no research findings on the Bangladeshi Standard Bangla, except for our own on the accent-affected acoustic features analysis of four (4) monophthongal vowels [12]. The accent analysis researches in other languages, had reported to have different accent-affected acoustic features that help us to know the regional accent effect on speech for a particular language community. These reported acoustic features are the first three formants frequencies, phone duration, intensity and pitch slope of vowel sounds [6]–[11].

ACCENT DATABASE AND EXPERIMENTAL SETUP

EXPERIMENTAL SETUP

ACCENTED FEATURES ANALYSIS

Findings

CONCLUSION