The South Asian Association for Regional Cooperation (SAARC) is deploying speech recognition support to clients who are keen on purchasing speech recognition software for commercial purposes. Speech recognition software are in high demand amidst the COVID-19 (coronavirus) pandemic in order to provide remote services to users in the real4ms of banking and financial services and the retail shopping sector. Thus, companies in the intelligent virtual assistant market should capitalize on the demand for speech recognition software, especially to help individuals with mobility impairments, visual impairments, and senior citizens amidst the ongoing COVID-19 pandemic.
Speech recognition products are expected to register a sudden spike during the coronavirus era, since voice-to-text solutions have become the need of the hour. Speech to text converting software are improving internal efficiencies in healthcare organizations. Speech recognition tools are reducing unnecessary overheads for the healthcare industry and is being highly preferred by hospitals with budget-strapped resources.
These factors are expected to drive the intelligent virtual assistant market during the forecast period.
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Intelligent Virtual Assistant Vendors Achieve Wide Distribution of TTS in Wireless Devices
Popular products such as Google’s Alexa and Siri in iOS phones are set to create lucrative growth opportunities for companies in the intelligent virtual assistant market. Text-to-speech (TTS) use is growing in network applications such as in synthetic voice reading of email messages and textual content of websites. Intelligent virtual assistant vendors are focusing on niche applications for TTS such as developing limited vocabularies in order to deliver quality in specific applications. These factors are helping the intelligent virtual assistant market to mature from an estimated value position of US$ 2.9 Bn in 2024 to US$ 50.9 Bn by the end of 2030.
TTS is achieving wide distribution in the market for intelligent virtual assistant for content from up-to-the minute information services. Vendors are broadening their revenue streams in motor vehicles, wireless devices, games, and toys.
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ML and Big Data Help Improve Speech Accuracy Rates in Devices
Innovative uses of speech recognition such as in smartwatches, computers, and cars are some of the key drivers that are bolstering growth for the intelligent virtual assistant market. These factors are slated to register an astonishing CAGR of 33% for the market during the forecast period. The ever-increasing mobile phone usage is another key driver, which is establishing stable revenue streams for intelligent virtual assistant vendors. Apart from electronics, companies are tapping into incremental opportunities in the realms of finance, marketing, human resource (HR), and even public transportation.
Companies in the intelligent virtual assistant market are aiming to bring down business costs associated with the integration of speech recognition systems, whilst simplifying outdates processes and increasing overall efficiency. Backed by proficiency in machine learning (ML), Big Data, and cloud processing, companies are improving speech accuracy rates.
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High-quality TTS Acquires Prominence in Network Applications for Reading Names to Customers
New innovations in the text-to-speech technology are bringing about a significant change in the intelligent virtual assistant market. However, several TTS systems tend to offer unnatural and unpleasant speech to uses. Hence, companies in the intelligent virtual assistant market should increase efforts to acquire large databases of speech recordings. They should increase their R&D activities to incorporate carefully designed responses and specific emotions to resonate with the users. Likewise, speech recognition technologies are also found to achieve higher accuracy when tailored to specific applications.
The ultimate goal for intelligent virtual assistant vendors is to produce TTS synthesis with a speech that is indistinguishable from human speech. As such, high-quality TTS is being used in network applications such as for reading names and addresses back to customers. On the other hand, low-quality TTS is acquiring prominence in automotive systems and mobile devices, since it requires less memory storage.
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