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Preliminary Study on SSCF-derived Polar Coordinate for ASR


The transition angles are defined to describe the vowel-to-vowel transitions in the acoustic space of the Spectral Subband Centroids, and the findings show that they are similar among speakers and speaking rates. In this paper, we propose to investigate the usage of polar coordinates in favor of angles to describe a speech signal by characterizing its acoustic trajectory and using them in Automatic Speech Recognition. According to the experimental results evaluated on the BRAF100 dataset, the polar coordinates achieved significantly higher accuracy than the angles in the mixed and cross-gender speech recognitions, demonstrating that these representations are superior at defining the acoustic trajectory of the speech signal. Furthermore, the accuracy was significantly improved when they were utilized with their first and second-order derivatives (∆, ∆∆), especially in cross-female recognition. However, the results showed they were not much more gender-independent than the conventional Mel-frequency Cepstral Coefficients (MFCCs).

2022 Papers

Local and Global Orientation Correction for Oriented Human (Pose) Detection

Text Recognition on the Khmer Identification Cards and Its Application in Electronic Know Your Customer (e-KYC)

Exploration of Semantic Information of Previous Sentences for Automatic Speech Recognition

Cambodia Distributed Ledger – CamDL

Job Trends Analysis Using Power BI

Students’ Sentiment and Feedback Analysis on Online Learning System during COVID-19

Temperature Forcasting in Pnhom Penh Using Time Series Models

Eveluation of Regularization based Contiual Learning Alogorithm in the Context of Human Activity Recognition

Implementation of Deep Learning for Smart City Application: Lessons Learned

Intelligent Control in SDN/NFV-Empowered IoT System for Smart City Application

ENI-ETSI Meets the Proactive Network Solutions for Multi-tier Networking


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