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Voice search queries account for one-third of searches in India, says Google executive

Approximately one-third of search queries originating from India are spoken, highlighting the cultural preference of Indians to use voice rather than text for searching, according to a senior vice president of Google, Prabhakar Raghavan.

Raghavan stated in an interaction with ET that in contrast to the United States, where only around 3% to 4% of search queries are spoken, India has witnessed a tenfold increase in spoken search queries due to the comfort people have in using their phones to speak to search engines.

Raghavan further emphasized that India will experience a diversification in search queries across various modalities, including text, voice, and image.

Recognizing India’s rapid growth, Raghavan predicted that the next major startup success in the country could be one that caters specifically to the needs of Indian users.

Google has developed several India-focused products, such as Google Pay and specific features in Google Maps tailored to the Indian market, including offline maps, flood forecast warnings, and directions for two-wheelers. These products have not only gained popularity in India but have also found use cases in other countries.

Raghavan highlighted the significance of building better Indic language models, including dialects like Hinglish, which is a blend of pure and written languages. Training mixed language models alongside pure language models is essential to comprehend the evolving search queries from India, as they now involve combinations of voice, image, or both.

Regarding generative AI, Raghavan opposed calls for a pause in its development, stating that regulations should be based on a deep understanding of the subject. He emphasized the need to balance innovation and the potential of AI to uplift economies like India. Google considers India one of its two priority markets.

As the preference for voice-based search continues to rise in India, Google is actively working on enhancing its language models and developing better resources to support diverse search queries in the country.

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