Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

The Application of Probabilistic Neural Network in Speech Recognition Based on Partition Clustering

Domain:

natural language processing

Record type:

paper
Creator:
XinMinLi Zhe
Publisher:
Tra
Host:
A probabilistic neural network (PNN) speech recognition model based on the partition clustering algorithm is proposed in this paper. The most important advantage of PNN is that training is easy and instantaneous. Therefore, PNN is capable of dealing with real time speech recognition. Besides, in order to increase the performance of PNN, the selection of data set is one of the most important issues. In this paper, using the partition clustering algorithm to select data is proposed. The proposed model is tested on two data sets from the field of spoken Arabic numbers, with promising results. The performance of the proposed model is compared to single back propagation neural network and integrated back propagation neural network. The final comparison result shows that the proposed model performs better than the other two neural networks, and has an accuracy rate of 92.41%.

Visit

doi.org

Tasks

automatic speech recognitionspeech processing

Licenses

https://www.scientific.net/PolicyAndEthics/PublishingPolicieshttps://www.scientific.net/license/TDM_Licenser.pdf

Similar

Neural Network Based Hausa Language Speech RecognitionNEURAL NETWORK BASED ARCHITECTURE FOR AUTOMATIC SPEECH RECOGNITION IN YORUBASpeech recognition system based on deep neural network acoustic modeling for low resourced language-AmharicApplication of Artificial Neural Network on South African Sign Language Recognition SystemAdvanced Convolutional Neural Network-Based Hybrid Acoustic Models for Low-Resource Speech RecognitionBridgeNets: Student-Teacher Transfer Learning Based on Recursive Neural Networks and its Application to Distant Speech Recognition

Neural Network Based Hausa Language Speech Recognition

NEURAL NETWORK BASED ARCHITECTURE FOR AUTOMATIC SPEECH RECOGNITION IN YORUBA

Speech recognition system based on deep neural network acoustic modeling for low resourced language-Amharic

Application of Artificial Neural Network on South African Sign Language Recognition System

Advanced Convolutional Neural Network-Based Hybrid Acoustic Models for Low-Resource Speech Recognition

Deep neural networks (DNNs) have shown a great achievement in acoustic modeling for speech recogniti

BridgeNets: Student-Teacher Transfer Learning Based on Recursive Neural Networks and its Application to Distant Speech Recognition

Despite the remarkable progress achieved on automatic speech recognition, recognizing far-field spee