"Human, All Too Human": NOAA Weather Radio and the Emotional Impact of Synthetic Voices

Scott, Kristen M.; Ashby, Simone; Hanna, Julian

doi:10.1145/3313831.3376338

Cited by 12 publications

(7 citation statements)

References 23 publications

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“…The results reflect those of a recent qualitative study (Scott et al, 2020). It analyzed Facebook comments of weather forecasts done with synthesized voices.…”

Section: Qualitative Analysessupporting

confidence: 83%

The Human Takes It All: Humanlike Synthesized Voices Are Perceived as Less Eerie and More Likable. Evidence From a Subjective Ratings Study

2020

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Background: The increasing involvement of social robots in human lives raises the question as to how humans perceive social robots. Little is known about human perception of synthesized voices.Aim: To investigate which synthesized voice parameters predict the speaker's eeriness and voice likability; to determine if individual listener characteristics (e.g., personality, attitude toward robots, age) influence synthesized voice evaluations; and to explore which paralinguistic features subjectively distinguish humans from robots/artificial agents.Methods: 95 adults (62 females) listened to randomly presented audio-clips of three categories: synthesized (Watson, IBM), humanoid (robot Sophia, Hanson Robotics), and human voices (five clips/category). Voices were rated on intelligibility, prosody, trustworthiness, confidence, enthusiasm, pleasantness, human-likeness, likability, and naturalness. Speakers were rated on appeal, credibility, human-likeness, and eeriness. Participants' personality traits, attitudes to robots, and demographics were obtained.Results: The human voice and human speaker characteristics received reliably higher scores on all dimensions except for eeriness. Synthesized voice ratings were positively related to participants' agreeableness and neuroticism. Females rated synthesized voices more positively on most dimensions. Surprisingly, interest in social robots and attitudes toward robots played almost no role in voice evaluation. Contrary to the expectations of an uncanny valley, when the ratings of human-likeness for both the voice and the speaker characteristics were higher, they seemed less eerie to the participants. Moreover, when the speaker's voice was more humanlike, it was more liked by the participants. This latter point was only applicable to one of the synthesized voices. Finally, pleasantness and trustworthiness of the synthesized voice predicted the likability of the speaker's voice. Qualitative content analysis identified intonation, sound, emotion, and imageability/embodiment as diagnostic features.Discussion: Humans clearly prefer human voices, but manipulating diagnostic speech features might increase acceptance of synthesized voices and thereby support human-robot interaction. There is limited evidence that human-likeness of a voice is negatively linked to the perceived eeriness of the speaker.

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“…The results reflect those of a recent qualitative study (Scott et al, 2020). It analyzed Facebook comments of weather forecasts done with synthesized voices.…”

Section: Qualitative Analysessupporting

confidence: 83%

The Human Takes It All: Humanlike Synthesized Voices Are Perceived as Less Eerie and More Likable. Evidence From a Subjective Ratings Study

2020

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“…With respect to participatory radio production, recent work has explored the (semi-)automatic handling of messages shared by listeners (spanning text, photos and videos) in order to improve storytelling in live radio shows [12]. A related concept is that of community radio (i.e., radio that is produced by, and for, members of a specifc community), which has been studied in relation to, for example, civic engagement (e.g., [37,45]) and information accessibility (e.g., [51]).…”

Section: Background and Related Workmentioning

confidence: 99%

“…Finally, audio-based applications (including broadcast radio) are witnessing innovation attempts in terms of analog-to-digital conversion (e.g., [24]), location-aware content consumption (e.g., [35]), hybrid delivery models that combine the broadcast signal with a per-listener, non-linear OTT channel (e.g., the HCR approach), listener notifcation (e.g., [50]), the use of chatbots to automate textual interaction with listeners (e.g., [12]), the use of voice interaction and smart speakers (e.g., [8]), the use of synthetic voices in radio programmes (e.g., [51]), and data-driven visualisations like charts to graphically augment the audio signal (e.g., [3]).…”

Section: Background and Related Workmentioning

confidence: 99%

Stay Tuned! An Investigation of Content Substitution, the Listener as Curator and Other Innovations in Broadcast Radio

Wijnants

Geurts

Lievens

et al. 2021

ACM International Conference on Interactive Media Experiences

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This paper demystifes listeners' wishes with respect to broadcast radio innovation (with a specifc focus on radio-mediated music consumption). Our study encompasses an ideation workshop with radio experts, an exploratory survey and a mixed methods empirical evaluation. The empirical evaluation uses two concrete concepts (i.e., letting listeners on-the-fy replace radio content with preferred content and fostering participatory radio production by involving listeners as radio content curators) as a lens to zoom in on the questionable desirability of radio innovation. It is learned that a signifcant consumer group exists who will stay loyal to broadcast radio even if it does not evolve substantially, whereas others need disruptive incentives to start listening to radio (again). From our results we distill design recommendations to educate the radio production community about how best to approach radio innovation. CCS CONCEPTS• Information systems → Multimedia streaming; • Humancentered computing → Laboratory experiments; User studies.

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“…With the latest implementation of neural networks--designed as algorithms imitating how the human brain works and recognizes patterns--TTS technology is making such rapid progress in terms of human-like natural pronunciation and intonation (Cohn, Sarian, Predeck, & Zellou, 2020) that the technology has the potential to supplement regular human news reading on radio, in podcasts as well as on TV as voice-overs. Importantly, neural TTS may provide an economically sustainable way to produce audio content to audiences in remote regions that would otherwise have limited or no access to local news in audio formats on the radio or the web (Scott, Ashby, & Hanna, 2020). Also, given the growing audience demand for news podcasts (e.g.…”

Section: Introductionmentioning

confidence: 99%

Automated News Reading in the Neural Age: Audience Reception and Perceived Credibility of a News Broadcast Read By a Neural Voice

2022

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Automated journalism is rapidly developing in the news industry. Among the most recent and promising technological potentials are neural voices, i.e. text-to-speech technology powered by neural networks. Based on a reception analysis with in-depth qualitative interviews (N =12), this study explores how Danish radio listeners receive a full news broadcast read by a neural voice and perceive the credibility of the neural reader and the news content. Results show that the participants divide into two types: the perspicacious listeners who realize or suspect that the news reading is artificially synthesized and, to some degree, are annoyed by it, and the oblivious listeners who believe the news is read by a human and are predominantly positive towards it. Participants from both groups pay particular attention to voice emotionality when evaluating the appropriateness of the neural news reader. Also, they tend to attribute human characteristics to the neural news reader.The participants single out the news messages as well as the media organization behind the news broadcast, rather than the neural voice itself as critical components constituting credibility. 2Transparency is of great importance when applying a neural voice in a news broadcast, since it is a prerequisite for credibility.

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"Human, All Too Human": NOAA Weather Radio and the Emotional Impact of Synthetic Voices

Cited by 12 publications

References 23 publications

The Human Takes It All: Humanlike Synthesized Voices Are Perceived as Less Eerie and More Likable. Evidence From a Subjective Ratings Study

The Human Takes It All: Humanlike Synthesized Voices Are Perceived as Less Eerie and More Likable. Evidence From a Subjective Ratings Study

Stay Tuned! An Investigation of Content Substitution, the Listener as Curator and Other Innovations in Broadcast Radio

Automated News Reading in the Neural Age: Audience Reception and Perceived Credibility of a News Broadcast Read By a Neural Voice

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