Detecting Extraneous Content in Podcasts

Reddy, Sravana; Yu, Yongze; Pappu, Aasish; Sivaraman, Aswin; Rezapour, Rezvaneh; Jones, Rosie

doi:10.18653/v1/2021.eacl-main.99

Cited by 14 publications

(7 citation statements)

References 15 publications

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“…2 Our participating system in TREC 2020 focuses on identifying salient segments from transcripts and using them as input to an abstractive summarizer (Song et al, 2020). Reddy et al (2021) develop classifiers to detect and eliminate extraneous marketing materials in podcasts to aid summarization. In this paper, we explore techniques that generate grounded podcast summaries where pieces of summary text are tied to short podcast clips.…”

Section: Related Workmentioning

confidence: 99%

Towards Abstractive Grounded Summarization of Podcast Transcripts

Song¹,

Li²,

Wang³

et al. 2022

Preprint

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Podcasts have shown a recent rise in popularity. Summarization of podcasts is of practical benefit to both content providers and consumers. It helps people quickly decide whether they will listen to a podcast and/or reduces the cognitive load of content providers to write summaries. Nevertheless, podcast summarization faces significant challenges including factual inconsistencies of summaries with respect to the inputs. The problem is exacerbated by speech disfluencies and recognition errors in transcripts of spoken language. In this paper, we explore a novel abstractive summarization method to alleviate these issues. Our approach learns to produce an abstractive summary while grounding summary segments in specific regions of the transcript to allow for full inspection of summary details. We conduct a series of analyses of the proposed approach on a large podcast dataset and show that the approach can achieve promising results. Grounded summaries bring clear benefits in locating the summary and transcript segments that contain inconsistent information, and hence improve summarization quality in terms of automatic and human evaluation.

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Section: Related Workmentioning

confidence: 99%

Towards Abstractive Grounded Summarization of Podcast Transcripts

Song¹,

Li²,

Wang³

et al. 2022

Preprint

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“…Figure 3 is one illustrative example of a curve from listening data on Spotify that shows the proportion of listeners at each time point over the duration of a single podcast episode. In such curves, dips tend to correspond to ads or other extraneous material [68] and there are commonly sharp drops at the beginnings and the ends of episodes. These curves in general show some distinctive characteristics depending on the nature of the podcast; for example, well-known podcasts tend to have a sharper drop at the beginning than lesser known podcasts, since they attract a diverse group of listeners who may be curious about the podcast but find that they are not interested after a few seconds.…”

Section: Podcast Consumption and Feedbackmentioning

confidence: 99%

“…These curves in general show some distinctive characteristics depending on the nature of the podcast; for example, well-known podcasts tend to have a sharper drop at the beginning than lesser known podcasts, since they attract a diverse group of listeners who may be curious about the podcast but find that they are not interested after a few seconds. Listening curves are useful for detecting extraneous content [69], assessing ad monetization, improving summarization, and devising user engagement metrics on podcast-access platforms (such as, for example, deriving thresholds on the amount of listening that counts as user satisfaction).…”

Section: Podcast Consumption and Feedbackmentioning

confidence: 99%

Current Challenges and Future Directions in Podcast Information Access

Jones¹,

Zamani

Schedl

et al. 2021

Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval

Self Cite

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Podcasts are spoken documents across a wide-range of genres and styles, with growing listenership across the world, and a rapidly lowering barrier to entry for both listeners and creators. The great strides in search and recommendation in research and industry have yet to see impact in the podcast space, where recommendations are still largely driven by word of mouth. In this perspective paper, we highlight the many differences between podcasts and other media, and discuss our perspective on challenges and future research directions in the domain of podcast information access.

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“…At the heart of the monetization ecosystem on social media are influencers (also known as content creators) [44], who engage in complex supply chains for the pursuit of revenue based on their Internet activities. As a pervasive type of Internet entrepreneurs engaged in cultural production, influencers often turn into media empires with impressive economic returns [37]. With the content creation economy booming globally and at unprecedented scale, public authorities tasked with the enforcement of existing Internet law (e.g.…”

Section: Introductionmentioning

confidence: 99%

The Case for a Legal Compliance API for the Enforcement of the EU's Digital Services Act on Social Media Platforms

Goanta¹,

Bertaglia²,

Iamnitchi³

2022

Preprint

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In the course of under a year, the European Commission has launched some of the most important regulatory proposals to date on platform governance. The Commission's goals behind cross-sectoral regulation of this sort include the protection of markets and democracies alike. While all these acts propose sophisticated rules for setting up new enforcement institutions and procedures, one aspect remains highly unclear: how digital enforcement will actually take place in practice. Focusing on the Digital Services Act (DSA), this discussion paper critically addresses issues around social media data access for the purpose of digital enforcement and proposes the use of a legal compliance application programming interface (API) as a means to facilitate compliance with the DSA and complementary European and national regulation. To contextualize this discussion, the paper pursues two scenarios that exemplify the harms arising out of content monetization affecting a particularly vulnerable category of social media users: children. The two scenarios are used to further reflect upon essential issues surrounding data access and legal compliance with the DSA and further applicable legal standards in the field of labour and consumer law.CCS Concepts: • Social and professional topics → Governmental regulations.

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Detecting Extraneous Content in Podcasts

Cited by 14 publications

References 15 publications

Towards Abstractive Grounded Summarization of Podcast Transcripts

Towards Abstractive Grounded Summarization of Podcast Transcripts

Current Challenges and Future Directions in Podcast Information Access

The Case for a Legal Compliance API for the Enforcement of the EU's Digital Services Act on Social Media Platforms

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