Will AI replace our news anchors? The Business Standard

For example, Janse and Adank (2012) report that both measures of selective attention and vocabulary predicted adaptation in a group of older adults. Moreover, while some indices of executive function can predict adaptation, they might not be the same in younger and older adults (Jesse and Janse, 2012). This is clearly a promising avenue of research, which could inform our understanding of the variety of mechanisms that are involved in both accent perception and adaptation. Children are remarkably good at spotting accents, although they may be better with some accents than others (e.g., Floccia et al., 2009).

The second test trial was more cognitively demanding, since a new label was provided, and toddlers were expected to infer that the correct referent was the competitor. In this demanding task, 30-month-olds were able to recognize a newly learned word across Spanish-accented and native English pronunciations, regardless of which variety was used in training and test. This order of presentation effect suggested that even short exposures to the accent could suffice in easing children into the unfamiliar accent, a possibility that was investigated in a study reported in the next section. Cross-accent segmentation studies ask whether infants can recognize and segment a familiarized word across the native variety and an accented variety.

Preference paradigms skip the familiarization phase to tap infants’ early preferences for one variety over another, simply measuring infants’ attention while they hear utterances in their own or an unfamiliar variety. In this paradigm, preference is dependent on age (younger infants show stronger preferences than younger ones), and experience (infants with some exposure to the non-native variety lose their preferences earlier; Kitamura et al., 2006). A decrease of preference for the native over the non-native variety has been taken as evidence that infants learn to interpret the unfamiliar accents as a variant of the native accent.

21, 1903–1909. Furthermore, there have been reports of virtual avatars being exploited to spread fake news and propaganda in countries like Venezuela. While the threat of job losses to AI is not entirely trivial, it remains a valid concern. To explore the capabilities of AI in reporting, Tom Clarke, editor of the science and technology department at SkyNews, experimented using Python programming. The survey conducted by the World Association of News Publishers shed light on the perceived risks of using generative AI in journalism.

Adaptation to novel accents by toddlers. 14, 372–384. Sumner, M., and Samuel, A. The effect of experience on the perception and representation of dialect variants.

As the business landscape increasingly prioritizes flexibility, rapid implementation, and resource efficiency, the growth of cloud-based deployment in the market reflects its ability to meet these evolving demands and drive widespread adoption. Services holds the largest share in the Text-to-Speech market offering category due to the heightened demand for cloud-based TTS solutions and the shift toward service-oriented models. The versatility and scalability of TTS services enable businesses to access advanced voice synthesis capabilities without the need for substantial infrastructure investments. Cloud-based offerings, in particular, provide a cost-effective and efficient way for organizations to integrate TTS into their applications and products.

While some suggest that learners extract prelexical patterns, others favor lexical storage as the way in which learners capture their newly gained accent knowledge. We have reviewed evidence that 19-month-olds exposed to an artificial accent did not accept any sound change in untrained items, but only mispronunciations along the lines of the experienced sound change (White and Aslin, 2011). However, this may not indicate that phonemic remapping is already perfect at this young age. For example, van Linden and Vroomen (2008) suggest that additional experience helps learners become more informed listeners, allowing them to integrate multimodal information.

Jesse, A., and Janse, E. Audiovisual benefit for recognition of speech presented with single-talker noise in older listeners. Process. 27, 1167–1191. Janse, E., and Adank, P. (2012).

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These results could suggest that 8-month-olds can already accommodate for within-language varieties, in a way that does not extend to an unfamiliar language. However, we believe this interpretation is too strong in view of the following two sets of results. Further, American English-learning 9-month-olds are able to segment words in Dutch, a language unfamiliar to them (Houston et al., 2000).

In McQueen et al. (2012), 6- and 12-year-olds learned to map an ambiguous sound between /f/ and /s/ onto one of these endpoints after hearing them in the context of unambiguous lexical items (such as platypus and giraffe). Other work suggests that there may be some developmental differences in the ability to integrate multiple cues in order to perform such remapping. Van Linden and ChatGPT App Vroomen (2008) presented 5- and 8-year-olds with videos where talkers said /aba/ (or /ada/) when the paired audio was an ambiguous sound between /b/ and /d/, and videos of /ada/ (or /aba/) with an unambiguous audio. As adults had in a previous study (Bertelson et al., 2003), 8-year-olds clearly learned to interpret the ambiguous sound in terms of the visually presented category.

Regional dialect variation in the vowel systems of typically developing children. Res. 54, 448–470. Girard, F., Floccia, C., and Goslin, J. Perception and awareness of accents in young children. 26, 409–433. Gass, S., and Varonis, E.

The most appropriate immediate parent market size has been used to implement the top-down approach to calculate the market size of specific segments. The top-down approach has been implemented for the regional accents present challenges for natural language processing. data extracted from the secondary research to validate the market size obtained. Each company’s market share has been estimated to verify the revenue shares used earlier in the top-down approach.

You can foun additiona information about ai customer service and artificial intelligence and NLP. For example, Nazzi et al. (2012) propose that irrelevant prosodic cues (e.g., the quality or degree of the infant-directed speech and hence its likability) could shape infants’ performance when not explicitly and carefully controlled. In most of the world, people have regular exposure to multiple accents. Therefore, learning to quickly process accented speech is a prerequisite to successful communication. In this paper, we examine work on the perception of accented speech across the lifespan, from early infancy to late adulthood. Unfamiliar accents initially impair linguistic processing by infants, children, younger adults, and older adults, but listeners of all ages come to adapt to accented speech.

Data Triangulation

By 2021, more AI presenters appeared in four newsrooms in China and South Korea in a similar fashion. South Korea-based company DeepBrain AI was involved in all of this. According to a survey by the World Association of News Publishers published last May, more than half of newsrooms around the world use generative AI tools like ChatGPT. Exclusive indicates content/data unique to MarketsandMarkets and not available with any competitors. Kendall, T., and Fridland, V. (2012). Variation in perception and production of mid front vowels in the U.S.

For example, Maye et al. (2008) created an accent where all vowels were shifted down in the vowel space (i.e., “wetch” became an acceptable pronunciation of the word “witch”). After mere minutes of hearing the story of the Wizard of Oz spoken in this “accent,” participants gave more “word” responses on a subsequent lexical decision task to items that were plausible implementations of real words in that accent. Interestingly, several top-down factors have been shown to modulate the processing cost involved in perceiving accented speech, suggesting that, to a certain extent, a different processing profile may not be due only to differences in the acoustic signal.

Magnuson, J. S., and Nusbaum, H. C. Acoustic differences, listener expectations, and the perceptual accommodation of talker variability. 33, 391–409. Kinzler, K. D., Shutts, K., DeJesus, J., and Spelke, E. S. Accent trumps race in guiding children’s social preferences.

It’s the remarkable synergy of NLP and NLU, two dynamic subfields of AI that facilitates it. NLP assists with grammar and spelling checks, translation,  sentence completion, and data analytics. Whereas NLU broadly focuses on intent recognition, detects sentiment and sarcasm, and focuses on the semantics of the sentence. The AI reporter demonstrated competence in generating logical and informative story ideas, offering excellent advice on scriptwriting and suitable footage.

Listening to speech by multiple talkers as compared to one talker results in slower reaction times and disrupted accuracy on many tasks, a phenomenon that has been called the talker interference effect (Creel and Bregman, 2011). Likewise, when given a set of utterances, listeners are slower and less accurate at naming a word spoken in noise if the utterances are spoken by a mix of talkers instead of one talker (e.g., Creelman, 1957; Mullennix et al., 1989; Sommers et al., 1994). Finally, listeners recall fewer words from a list spoken by multiple talkers as compared to a list spoken by one talker (Martin et al., 1989, but see Goldinger et al., 1991 and Nygaard et al., 1994 for evidence that inter-stimulus-interval modulates this effect). To a certain extent, the talker interference effect is due to top-down biases, since it emerges when the listeners expect to hear two voices, even if the signal from “both voices” is acoustically identical (Magnuson and Nusbaum, 2007, using synthetic speech). This question has been approached using regional variation in French.

Intelligibility of foreign-accented speech for older adults with and without hearing loss. 21, 153–162. Additionally, AI can facilitate the seamless translation of content into various languages. This capability enables news organisations to deliver the same news to a global audience rapidly and efficiently. The primary hurdles in this domain are data adequacy and high-performance computing.

The varieties spoken in France have either lost or are in the process of merging /e/ and /ε/, a contrast that has not merged in the varieties spoken in Switzerland. Current results indicate that long-term exposure to a variety where a given contrast is merged (i.e., French as spoken in France) could actually result in loss of discrimination in one’s own unmerged variety (affecting Swiss listeners; Brunellière et al., 2009, 2011). In fact, some research suggests that delays when processing speech in an accent that is not one’s own could actually indicate that different mechanisms are recruited, or that they are relied upon to a different extent when processing accented and unaccented speech. These differences are sometimes evident when processing is rendered difficult.

Based on verticals, the education sector in Text-to-Speech market accounts for highest CAGR

Initially developed to aid the visually impaired, TTS systems find application in various scenarios, assisting those who read slowly, face concentration challenges, need writing feedback, experience visual stress, and more. Over time, technological progress has expanded the use of TTS across diverse applications, including providing directions on navigation devices, facilitating public announcements, and serving as voices for virtual assistants. The Text-to-Speech market is driven by increasing demand for AI-based tools and natural language processing, widespread adoption of advanced electronic devices, and growing applications across industries. The rising need for accessibility features, particularly for differently-abled individuals, fuels market growth. Technological advancements, such as enhanced pronunciation and voice modification capabilities, contribute to the expanding use of Text-to-Speech solutions.

• At an empirical level, it is not rare to find two “languages” that are closer to each other (in terms of mutual intelligibility and ease of processing) than two “dialects” of the same language.
• Computer vision allows machines to accurately identify emotions from visual cues such as facial expressions and body language, thereby improving human-machine interaction.
• Accent trumps race in guiding children’s social preferences.
• Kinzler, K. D., Dupoux, E., and Spelke, E. S.
• Although the parallels between processing talker and accent variation are remarkable, further work is needed before concluding that this stems from their involving the same mechanisms.

Goldinger, S. D., Pisoni, D. B., and Logan, J. S. On the nature of talker variability effects on recall of spoken word lists. 17, 152–162.

Some effects of talker variability on spoken word recognition. 85, 365–378. However, since the amount of data processed here is small, the new language has some linguistic complexities, so facial abnormalities, very slow speech or slurred speech will remain to some extent.

In the Introduction, we merely stated that we would use “linguistic variety” as an umbrella term. We viewed this umbrella as necessary for both conceptual and empirical reasons. At a conceptual level, it is impossible to draw stable, non-arbitrary boundaries between (1) different languages; (2) different dialects of the same language; and (3) non-native, dialectal, sociolectal accents. For example, among linguists, it is often said that “a language is a dialect with an army and a navy” (Magner, 1974).

DeKeyser, R. The robustness of critical period effects in second language acquisition. Second Lang. Acquisition 22, 499–533. Clopper, C. G., and Pisoni, D. B. (2004b).

Text-to-Speech Market Size, Share and Growth Analysis

This study has determined and confirmed the overall parent market and individual market sizes by the data triangulation method and data validation through primaries. The data triangulation method in this study is explained in the next section. In the complete market engineering process, both top-down and bottom-up approaches have been used, along with several data triangulation methods, to perform market estimation and forecasting for the overall market segments and subsegments listed in this report. Key players in the market have been identified through secondary research, and their market shares in the respective regions have been determined through primary and secondary research.

Following this exposure phase was another sentence transcription task serving as a test. Participants who heard one Chinese-accented speaker in training and a different Chinese-accented speaker at test did not perform any better than participants who heard unaccented speakers in training. In contrast, exposure to multiple Chinese-accented talkers resulted in adaptation to a novel Chinese-accented talker, at a level equivalent to being trained with the test talker. Thus, it seems that exposure to multiple talkers of the target foreign accent can be an effective means of achieving talker-independent adaptation in adults. Interestingly, this adaptation was accent-dependent rather than accent-general since training on Chinese-accented English (whether with one or five talkers of the accent) did not result in adaptation to another unfamiliar accent (Slovakian-accented English).

In this article, we review evidence bearing on how we perceive speech in the face of accent variation, both as our linguistic system develops and after we have become efficient language processors. To our knowledge, this is the first review that aims to assemble findings on infant, child, and adult accent perception. Examining accent perception across the lifespan allows us to underline points of convergence and divergence, as well as gaps that remain for future work. The question of how to draw lines between linguistic varieties is relevant for another line of research. It has been repeatedly reported that bilingual speakers develop more flexible cognitive and linguistic systems (Kovacs and Mehler, 2009; Bialystok, 2010; Sebastián-Gallés, 2010). If the line between accents, dialects, and languages is difficult to draw, does this mean that bi-accentual/bi-dialectal children will also experience similar cognitive gains?

• The structural organization of the mental lexicon and its contribution to age-related declines in spoken-word recognition.
• Each company’s market share has been estimated to verify the revenue shares used earlier in the top-down approach.
• 26, 708–715.
• (2010b).

Jusczyk, P. W., and Aslin, R. N. Infants’ detection of the sound patterns of words ChatGPT in fluent speech. 29, 1–23. Jacewicz, E., Allen Fox, R., and Salmons, J.

With its extensive list of benefits, conversational AI also faces some technical challenges such as recognizing regional accents and dialects, and ethical concerns like data privacy and security. To address these, employing advanced machine learning algorithms and diverse training datasets, among other sophisticated technologies is essential. Voice assistants like Alexa and Google Assistant bridge the gap between humans and technology through accurate speech recognition and natural language generation.

Bürki-Cohen, J., Miller, J. L., and Eimas, P. D. Perceiving non-native speech. Speech 44, 149–169. Bresnahan, M., Ohashi, R., Nebashi, R., Liu, W., and Shearman, S. Attitudinal and affective response toward accented English.

Speech 51, 175–198. Bradlow, A. R., and Bent, T. Perceptual adaptation to non-native speech. Cognition 106, 707–729. Adank, P., Hagoort, P., and Bekkering, H. Imitation improves language comprehension.

Naturally, SSB adults will have a harder time understanding a Dutch speaker than a fellow Glaswegian, given the smaller lexical overlap with the former variety. In other words, it is not always the case that dialects are closer to each other than languages. Moreover, the degree to which processing an unfamiliar within-language accent resembles processing an unfamiliar foreign accent at any given age is an empirical matter and probably depends on the dimension of focus. As argued above, diverse results could be explained by sampling from a variable population. Janse and colleagues have begun investigating whether individual variation in accented speech comprehension and adaptation correlates with individual variation along cognitive and linguistic dimensions.

Percept. Perform. 31, 1315–1330. AI news presenters like ‘Aparajita’ only convert text to audio. But generative AI is much more complex. To replace a human news presenter, AI needs the understanding and processing of natural language to rearrange questions and answers coherently and humanly, making it more challenging compared to current AI avatars.

Some acoustic cues for the perceptual categorization of American English regional dialects. 32, 111–140. Clarke, C. M., and Garrett, M. F. Rapid adaptation to foreign-accented English. J. Acoust. 116, 3647–3658.