Objective assessment of communication speech interference effect based on feature fusion
In view of the objective assessment problem of the effect of communication speech interference, methods based on multi-measurements and multimodal fusion were proposed.First, the interfered speech was preprocessed by the endpoint detection algorithm and time warping algorithm.Then, the content of sp...
Saved in:
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | zho |
Published: |
Editorial Department of Journal on Communications
2023-03-01
|
Series: | Tongxin xuebao |
Subjects: | |
Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023043/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
_version_ | 1841540035903488000 |
---|---|
author | Yun LIN Huaitao XU Sen WANG Sicheng ZHANG Long ZHUANG |
author_facet | Yun LIN Huaitao XU Sen WANG Sicheng ZHANG Long ZHUANG |
author_sort | Yun LIN |
collection | DOAJ |
description | In view of the objective assessment problem of the effect of communication speech interference, methods based on multi-measurements and multimodal fusion were proposed.First, the interfered speech was preprocessed by the endpoint detection algorithm and time warping algorithm.Then, the content of speech was extracted and performed measurement calculated with the standard speech to obtain five kinds of measure.After the fusion of five measures, random forest model was used to assessed the quality level.Finally, a neural network model based on residual structure was designed combined multimodal fusion technique, which fused the graph domain and measure domain features of the interfered speech data and performed quality level assessment.Experimental results show that the accuracy of two methods have reached more than 90%.Among them, the multimodal assessment method improves the accuracy by about 3.269% compared with the existing research methods, which proves that it has a better performance. |
format | Article |
id | doaj-art-42b174413c7a43dca6a82fea93fc617b |
institution | Kabale University |
issn | 1000-436X |
language | zho |
publishDate | 2023-03-01 |
publisher | Editorial Department of Journal on Communications |
record_format | Article |
series | Tongxin xuebao |
spelling | doaj-art-42b174413c7a43dca6a82fea93fc617b2025-01-14T06:23:19ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2023-03-014410511659387706Objective assessment of communication speech interference effect based on feature fusionYun LINHuaitao XUSen WANGSicheng ZHANGLong ZHUANGIn view of the objective assessment problem of the effect of communication speech interference, methods based on multi-measurements and multimodal fusion were proposed.First, the interfered speech was preprocessed by the endpoint detection algorithm and time warping algorithm.Then, the content of speech was extracted and performed measurement calculated with the standard speech to obtain five kinds of measure.After the fusion of five measures, random forest model was used to assessed the quality level.Finally, a neural network model based on residual structure was designed combined multimodal fusion technique, which fused the graph domain and measure domain features of the interfered speech data and performed quality level assessment.Experimental results show that the accuracy of two methods have reached more than 90%.Among them, the multimodal assessment method improves the accuracy by about 3.269% compared with the existing research methods, which proves that it has a better performance.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023043/speech quality assessmentspeech signal processingmultimodal fusiondeep neural network |
spellingShingle | Yun LIN Huaitao XU Sen WANG Sicheng ZHANG Long ZHUANG Objective assessment of communication speech interference effect based on feature fusion Tongxin xuebao speech quality assessment speech signal processing multimodal fusion deep neural network |
title | Objective assessment of communication speech interference effect based on feature fusion |
title_full | Objective assessment of communication speech interference effect based on feature fusion |
title_fullStr | Objective assessment of communication speech interference effect based on feature fusion |
title_full_unstemmed | Objective assessment of communication speech interference effect based on feature fusion |
title_short | Objective assessment of communication speech interference effect based on feature fusion |
title_sort | objective assessment of communication speech interference effect based on feature fusion |
topic | speech quality assessment speech signal processing multimodal fusion deep neural network |
url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023043/ |
work_keys_str_mv | AT yunlin objectiveassessmentofcommunicationspeechinterferenceeffectbasedonfeaturefusion AT huaitaoxu objectiveassessmentofcommunicationspeechinterferenceeffectbasedonfeaturefusion AT senwang objectiveassessmentofcommunicationspeechinterferenceeffectbasedonfeaturefusion AT sichengzhang objectiveassessmentofcommunicationspeechinterferenceeffectbasedonfeaturefusion AT longzhuang objectiveassessmentofcommunicationspeechinterferenceeffectbasedonfeaturefusion |