Television Discourse Decoded: Comprehensive Multimodal Analytics at Scale-Reference-Cited by-同舟云学术

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Television Discourse Decoded: Comprehensive Multimodal Analytics at Scale

Published:2024-08-24 Issue: Volume:13 Page:4752-4763
ISSN:
Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Agarwal Anmol¹^ORCID,Priyadarshi Pratyush¹^ORCID,Sinha Shiven¹^ORCID,Gupta Shrey¹^ORCID,Jangra Hitkul²^ORCID,Kumaraguru Ponnurangam¹^ORCID,Garimella Kiran³^ORCID

Affiliation:

1. International Institute of Information Technology, Hyderabad, India

2. Indraprastha Institute of Information Technology, Delhi, India

3. Rutgers University, New Brunswick, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671532

Reference43 articles.

1. Shikha Baghel, Mrinmoy Bhattacharjee, SR Mahadeva Prasanna, and Prithwijit Guha. 2021. Automatic Detection of Shouted Speech Segments in Indian News Debates.. In Interspeech. 4179--4183.

2. Doug Beeferman, William Brannon, and Deb Roy. 2019. Radiotalk: A large-scale corpus of talk radio transcripts. arXiv preprint arXiv:1907.07073 (2019).

3. Expanding public debate? Examining the impact of India’s top English language political talk shows

4. Jay G Blumler. 1970. The political effects of television. The political effects of television (1970), 68--104.

5. Hervé Bredin and Antoine Laurent. 2021. End-to-end speaker segmentation for overlap-aware resegmentation. In Interspeech 2021.

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