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arXiv · 1707.00138

Speaker Identification in Shouted Talking Environments Based on Novel Third-Order Hidden Markov Models

Ismail Shahin
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Abstract

In this work we propose, implement, and evaluate novel models called Third-Order Hidden Markov Models (HMM3s) to enhance low performance of text-independent speaker identification in shouted talking environments. The proposed models have been tested on our collected speech database using Mel-Frequency Cepstral Coefficients (MFCCs). Our results demonstrate that HMM3s significantly improve speaker identification performance in such talking environments by 11.3% and 166.7% compared to second-order hidden Markov models (HMM2s) and first-order hidden Markov models (HMM1s), respectively. The achieved results based on the proposed models are close to those obtained in subjective assessment by human listeners.

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Ismail Shahin. 2017-07-01. Speaker Identification in Shouted Talking Environments Based on Novel Third-Order Hidden Markov Models. https://arxiv.org/abs/1707.00138

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