# Exploring Dynamic Parameters for Vietnamese Gender-Independent ASR

arXiv: https://arxiv.org/abs/2507.22964 · HTML: https://mlsanity.com/paper/2507.22964/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 26 references that are in the map.
- First posted on arXiv 30 Jul 2025.

## Builds on (most cited first, 4 of 4)

- [End-to-End Speech Recognition: A Survey](https://mlsanity.com/paper/2303.03329/) (2023)
- [How to Learn a New Language? An Efficient Solution for Self-Supervised Learning Models Unseen Languages Adaption in Low-Resource Scenario](https://mlsanity.com/paper/2411.18217/) (2024)
- [Articulatory information and Multiview Features for Large Vocabulary Continuous Speech Recognition](https://mlsanity.com/paper/1802.05853/) (2018)
- [Preliminary Study on SSCF-derived Polar Coordinate for ASR](https://mlsanity.com/paper/2212.01245/) (2022)

## Abstract (arXiv)

The dynamic characteristics of speech signal provides temporal information and play an important role in enhancing Automatic Speech Recognition (ASR). In this work, we characterized the acoustic transitions in a ratio plane of Spectral Subband Centroid Frequencies (SSCFs) using polar parameters to capture the dynamic characteristics of the speech and minimize spectral variation. These dynamic parameters were combined with Mel-Frequency Cepstral Coefficients (MFCCs) in Vietnamese ASR to capture more detailed spectral information. The SSCF0 was used as a pseudo-feature for the fundamental frequency (F0) to describe the tonal information robustly. The findings showed that the proposed parameters significantly reduce word error rates and exhibit greater gender independence than the baseline MFCCs.