Editing Anil Kumar Vuppala

{{Infobox Professor
| education = Ph.D
| occupation = Professor
| Institute = IIIT-H
| specialization = Emotion and pathological speech recognition
}}

==Anil Kumar Vuppala ==
'''Dr. Anil Kumar Vuppala''' has joined as an [[Associate Professor]] at [[IIIT-H]]. Anil Kumar Vuppula was born on 1st November in 1984 at Nagayalanka in Krishna district, Andhra Pradesh State, [[India]].<ref>{{Cite web |title=Faculty profile IIITH |url=https://www.iiit.ac.in/faculty/anil-kumar-vuppala/}}</ref> 

== Education ==
Prof Anil Kumar Received [[B.Tech]] degree in [[Electronics & Communication Engineering]] from the Jawaharlal  Nehru Technological University (JNTU), Andhra Pradesh, India, in 2005 and  [[M.Tech]] degree in Electronics & Communication Engineering from the [[NIT Kurukshetra]], Haryana, India, in 2007, and [[Ph.D]] in [[speech processing]] from [[IIT Kharagpur]] in 2012.<ref>{{Cite web |title=Educational details google |url=https://sites.google.com/view/welcome-to-anils-world/Home}}</ref> 

==Research & Publications==
His research interests are Speech, speaker, language, emotion and pathological speech recognition.

# Novel feature representation using single frequency filtering and nonlinear energy operator for speech emotion recognition in 2022.<ref>{{Cite web |title=Novel feature representation using single frequency filtering and nonlinear energy operator for speech emotion recognition |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=VEx1PN4AAAAJ&cstart=20&pagesize=80&citation_for_view=VEx1PN4AAAAJ:TlpoogIpr_IC}}</ref>
# Analytic phase features for dysarthric speech detection and intelligibility assessment in 2020.<ref>{{Cite web |title=Analytic phase features for dysarthric speech detection and intelligibility assessment |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=VEx1PN4AAAAJ&cstart=20&pagesize=80&citation_for_view=VEx1PN4AAAAJ:FiDNX6EVdGUC}}</ref>
# IIIT-H Spoofing Countermeasures for Automatic Speaker Verification Spoofing and Countermeasures Challenge 2019.<ref>{{Cite web |title=IIIT-H Spoofing Countermeasures for Automatic Speaker Verification Spoofing and Countermeasures Challenge 2019. |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=VEx1PN4AAAAJ&cstart=20&pagesize=80&citation_for_view=VEx1PN4AAAAJ:O0nohqN1r9EC}}</ref>
# Application of emotion recognition and modification for emotional Telugu speech recognition in 2019.<ref>{{Cite web |title=Application of emotion recognition and modification for emotional Telugu speech recognition |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=VEx1PN4AAAAJ&cstart=20&pagesize=80&citation_for_view=VEx1PN4AAAAJ:yFnVuubrUp4C}}</ref>
# An Exploration towards Joint Acoustic Modeling for Indian Languages: IIIT-H Submission for Low Resource Speech Recognition Challenge for Indian Languages, INTERSPEECH 2018.<ref>{{Cite web |title=An Exploration towards Joint Acoustic Modeling for Indian Languages: IIIT-H Submission for Low Resource Speech Recognition Challenge for Indian Languages, INTERSPEECH 2018. |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=VEx1PN4AAAAJ&cstart=20&pagesize=80&citation_for_view=VEx1PN4AAAAJ:3htObqc8RwsC}}</ref>
# IIITH-ILSC Speech Database for Indain Language Identification in 2018.<ref>{{Cite web |title=IIITH-ILSC Speech Database for Indain Language Identification. |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=VEx1PN4AAAAJ&cstart=20&pagesize=80&citation_for_view=VEx1PN4AAAAJ:_OXeSy2IsFwC}}</ref>
# Residual neural networks for speech recognition in 2017.<ref>{{Cite web |title=Residual neural networks for speech recognition |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=VEx1PN4AAAAJ&cstart=20&pagesize=80&citation_for_view=VEx1PN4AAAAJ:OTTXONDVkokC}}</ref>
# Significance of neural phonotactic models for large-scale spoken language identification in 2017.<ref>{{Cite web |title=Significance of neural phonotactic models for large-scale spoken language identification |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=VEx1PN4AAAAJ&cstart=20&pagesize=80&citation_for_view=VEx1PN4AAAAJ:u_35RYKgDlwC}}</ref>
# Improved emotion recognition using GMM-UBMs in 2015.<ref>{{Cite web |title=Improved emotion recognition using GMM-UBMs |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=VEx1PN4AAAAJ&cstart=20&pagesize=80&citation_for_view=VEx1PN4AAAAJ:aqlVkmm33-oC}}</ref>
# Significance of automatic detection of vowel regions for automatic shout detection in continuous speech in 2016.<ref>{{Cite web |title=Significance of automatic detection of vowel regions for automatic shout detection in continuous speech |url=https://scholar.google.com/citations?view_op=view_citation&hl=en&user=VEx1PN4AAAAJ&cstart=20&pagesize=80&citation_for_view=VEx1PN4AAAAJ:ldfaerwXgEUC}}</ref>

== References ==

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