2015 Twenty First National Conference on Communications (NCC)最新文献_第5页

A novel breathiness feature for analysis and classification of speech under stress 一种新的呼吸特征在语音分析和分类中的应用

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084826

S. Deb, S. Dandapat

引用次数: 21

Equalization in amplify-forward full-duplex relay with direct link 直连放大前向全双工中继的均衡

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084888

Karra Chinmay Dheeraj, A. Thangaraj, R. Ganti

引用次数: 9

Widespread near-field with robust H-field using NDTC antennas in multipurpose applications 广泛的近场与鲁棒的h场使用NDTC天线在多用途应用

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084872

Ashwani Sharma, I. Zuazola, J. Batchelor, A. Perallos

引用次数: 0

On analyzing Indian cellular traffic characteristics for energy efficient network operation 分析印度蜂窝通信特性，实现高效节能网络运行

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084922

Karuna Kumar, Archit Gupta, Rushabh Shah, A. Karandikar, P. Chaporkar

引用次数: 10

On linear subspace codes closed under intersection 交点下封闭的线性子空间码

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084870

Pranab Basu, N. Kashyap

引用次数: 4

Building speech synthesis systems for Indian languages 为印度语言构建语音合成系统

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084931

Abhijit Pradhan, A. Prakash, S. Shanmugam, G. Kasthuri, R. Krishnan, H. Murthy

{"title":"Building speech synthesis systems for Indian languages","authors":"Abhijit Pradhan, A. Prakash, S. Shanmugam, G. Kasthuri, R. Krishnan, H. Murthy","doi":"10.1109/NCC.2015.7084931","DOIUrl":"https://doi.org/10.1109/NCC.2015.7084931","url":null,"abstract":"In this paper, new efforts to build text-to-speech synthesis systems (TTS) for Indian languages is presented. The synthesisers are built around both concatenative speech synthesis and statistical parametric speech synthesis frameworks. Text to speech synthesis systems require accurate segmentation. Obtaining accurate segmentation at the phone-level is a difficult task. Manual segmentation leads to human errors, while automatic segmentation using statistical approaches (hidden Markov model based approaches) leads to poor boundary information, when the amount of data used for training is small. A group delay based syllable segmentation semi-automatic tool is discussed. The tool is semi-automatic as some of the boundaries obtained are inaccurate and have to be manually corrected. Next, a segmentation algorithm that uses both HMM based segmentation and group delay based segmentation, is used to obtain accurate boundaries automatically. The boundaries obtained are used in the syllable-based synthesiser for unit selection. In the statistical phone-based synthesiser, embedded reestimation is performed at the phone level. Syllable-based and penta-phone based HMMs are used for building the synthesiser. TTS systems for 12 different Indian languages namely Tamil, Hindi, Marathi, Malayalam, Telugu, Rajasthani, Bengali, Odia, Assamese, Manipuri, Kannada and Gujarati are built using semi-automatic segmentation and synthesisers have been built for 7 Indian languages using automatic segmentation. Evaluation of the semi-automatic segmentation systems indicate that the MOS (mean opinion score) is above 3.0 for most of the languages. Pair comparison tests on semi-automatic vs. automatic segmentation show that automatic segmentation is preferred.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116964763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

An ultra-thin triple band polarization-insensitive metamaterial absorber for C-band applications 一种用于c波段应用的超薄三波段偏振不敏感超材料吸收器

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084816

Devkinandan Chaurasiya, Somak Bhattacharyya, Saptarshi Ghosh, Praneeth Munaga, K. V. Srivastava

引用次数: 5

Blind image quality evaluation using perception based features 基于感知特征的盲图像质量评价

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084843

Features Venkatanath, Praneeth, Maruthi Chandrasekhar Bh., Sumohana S. Channappayya, S. Medasani

引用次数: 381

Different aspects of source information for limited data speaker verification 不同方面的源信息对有限数据说话人进行验证

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084846

Rohan Kumar Das, D. Pati, S. Prasanna

{"title":"Different aspects of source information for limited data speaker verification","authors":"Rohan Kumar Das, D. Pati, S. Prasanna","doi":"10.1109/NCC.2015.7084846","DOIUrl":"https://doi.org/10.1109/NCC.2015.7084846","url":null,"abstract":"Limited data speaker verification has shown its significance in practical system oriented applications. The paper shows the importance of different aspects of voice source feature for limited test data scenario. A baseline speaker verification system using conventional mel frequency cepstral co-efficients (MFCC) feature is developed and performance under limited test data condition (≤10 s) is evaluated. A parallel system based on source feature mel power difference of spectrum in subband (M-PDSS) is developed in the i-vector based speaker verification framework. Both the systems were fused at the score level for the cases of short segments of test speech, which demonstrated the importance of source feature with reduction in test data duration. A comparative study of the M-PDSS feature is then made with our earlier work using discrete cosine transform of the integrated linear prediction residual (DCTILPR) feature and then fusion of two source features M-PDSS and DCTILPR along with MFCC features is carried out. An absolute improvement of 5.19% is obtained for 2 s of test data which conveys the significance of multiple source information under limited data speaker verification as it carries different aspects of source information.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132582712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

Enhancing speech intelligibility based on noise characteristics 基于噪声特性提高语音清晰度

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084905

Mayur Jagtap, P. Rao

引用次数: 1