Výsledky vyhledávání - "Madhu R. Kamble"

Amplitude and Frequency Modulation-based features for detection of replay Spoof Speech

Autor: Hemlata Tak, Madhu R. Kamble, Hemant A. Patil

Publikováno v: Speech Communication. 125:114-127

Replay attack poses a great threat to the Automatic Speaker Verification (ASV) system. This paper introduces Amplitude Modulation and Frequency Modulation-based features for replay Spoof Speech Detection (SSD) task. In this context, we propose Instan

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ab79ff46ce12acb0e6686e44ebd2b7f0
https://doi.org/10.1016/j.specom.2020.10.003

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Combination of Amplitude and Frequency Modulation Features for Presentation Attack Detection

Autor: Madhu R. Kamble, Hemant A. Patil

Publikováno v: Journal of Signal Processing Systems. 92:777-791

In this paper, we propose the combination of Amplitude Modulation and Frequency Modulation (AM-FM) features for replay Spoof Speech Detection (SSD) task. The AM components are known to be affected by noise (in this case, due to replay mechanism). In

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::17947d2278788ff5d3538c16f9e2c9f6
https://doi.org/10.1007/s11265-020-01532-3

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PANACEA Cough Sound-Based Diagnosis of COVID-19 for the DiCOVA 2021 Challenge

Autor: Massimiliano Todisco, Alejandro Gomez-Alanis, Yiqing Huang, Maria A. Zuluaga, Angel M. Gomez, Madhu R. Kamble, Juan M. Espin, Jose A. Gonzalez-Lopez, Lorenzo Cascioli, Teresa Grau, Jose Patino, Nicholas Evans, Roberto Font, Antonio M. Peinado

Publikováno v: Interspeech 2021.

The COVID-19 pandemic has led to the saturation of public health services worldwide. In this scenario, the early diagnosis of SARS-Cov-2 infections can help to stop or slow the spread of the virus and to manage the demand upon health services. This i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36e9d3a60233e50d3b0d293efa01804b
https://doi.org/10.21437/interspeech.2021-1062

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End-to-End Spectro-Temporal Graph Attention Networks for Speaker Verification Anti-Spoofing and Speech Deepfake Detection

Autor: Massimiliano Todisco, Madhu R. Kamble, Jose Patino, Nicholas Evans, Jee-weon Jung, Hemlata Tak

Artefacts that serve to distinguish bona fide speech from spoofed or deepfake speech are known to reside in specific subbands and temporal segments. Various approaches can be used to capture and model such artefacts, however, none works well across a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c808d4c71d6ec6ef207fcba4e44b7a6
http://arxiv.org/abs/2107.12710

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Energy Separation Based Features for Replay Spoof Detection for Voice Assistant

Autor: Madhu R. Kamble, Hemant A. Patil, Gauri P. Prajapati

Publikováno v: EUSIPCO

Voice Assistant (VA) now-a-days plays a very important role for the smart home applications. However, the VA along with ease also brings security issue too, such as possibility of being attacked by replay, hidden voice commands, etc. This paper prese

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a8201b33b3bf160a150aec1978d632de
https://doi.org/10.23919/eusipco47968.2020.9287577

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Teager Energy Cepstral Coefficients for Classification of Normal vs. Whisper Speech

Autor: Madhu R. Kamble, Kuldeep Khoria, Hemant A. Patil

Publikováno v: EUSIPCO

The whispered speech is quite different from natural speech in the context of nature, acoustic characteristics, and generation mechanism. In order to improve the robustness of Automatic Speech Recognition (ASR) system, it is very important to analyze

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::729eb8c0e7d11d7f0dcf45ca2bf72642
https://doi.org/10.23919/eusipco47968.2020.9287634

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