Recognition of Heavily Accented and Emotional Speech of English and Czech Holocaust Survivors Using Various DNN Architectures
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-87802-3_50
Reference29 articles.
1. Abdel-Hamid, O., Mohamed, A., Jiang, H., Deng, L., Penn, G., Yu, D.: Convolutional neural networks for speech recognition. IEEE/ACM Trans. Audio Speech Lang. Process. 22(10), 1533–1545 (2014). https://doi.org/10.1109/TASLP.2014.2339736
2. Byrne, W., et al.: Automatic recognition of spontaneous speech for access to multilingual oral history archives. IEEE Trans. Speech Audio Process. 12(4), 420–435 (2004). https://doi.org/10.1109/TSA.2004.828702
3. Dehak, N., Kenny, P.J., Dehak, R., Dumouchel, P., Ouellet, P.: Front-end factor analysis for speaker verification. IEEE Trans. Audio Speech Lang. Process. 19(4), 788–798 (2011). https://doi.org/10.1109/TASL.2010.2064307
4. Ghahremani, P., Manohar, V., Povey, D., Khudanpur, S.: Acoustic modelling from the signal domain using CNNs. In: Interspeech 2016, pp. 3434–3438 (2016). https://doi.org/10.21437/Interspeech.2016-1495
5. Hadian, H., Sameti, H., Povey, D., Khudanpur, S.: Flat-start single-stage discriminatively trained HMM-based models for ASR. IEEE ACM Trans. Audio Speech Lang. Process. 26(11), 1949–1961 (2018). https://doi.org/10.1109/TASLP.2018.2848701
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Transformer-based Speech Recognition Models for Oral History Archives in English, German, and Czech;INTERSPEECH 2023;2023-08-20
2. Developing a Question Answering System on the Material of Holocaust Survivors’ Testimonies in Russian;Speech and Computer;2023
3. Emotional Speech Recognition of Holocaust Survivors with Deep Neural Network Models for Russian Language;Speech and Computer;2023
4. Exploring Capabilities of Monolingual Audio Transformers using Large Datasets in Automatic Speech Recognition of Czech;Interspeech 2022;2022-09-18
5. Transformer-Based Automatic Speech Recognition of Formal and Colloquial Czech in MALACH Project;Text, Speech, and Dialogue;2022
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3