{"id":1679,"date":"2026-03-12T22:00:00","date_gmt":"2026-03-12T13:00:00","guid":{"rendered":"https:\/\/datalab.flitto.com\/en\/company\/blog\/?p=1679"},"modified":"2026-03-11T10:12:34","modified_gmt":"2026-03-11T01:12:34","slug":"ai-training-data-speech-multimodal-data","status":"publish","type":"post","link":"https:\/\/datalab.flitto.com\/en\/company\/blog\/ai-training-data-speech-multimodal-data\/","title":{"rendered":"[Data Deep Dive #5] How Speech and Multimodal Data Power AI Training"},"content":{"rendered":"\n
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One of the apps that has become essential when traveling abroad is an automatic translation app. In the past, people often communicated in broken English depending on the language environment, or pointed to pictures of dishes on restaurant menus to place orders. However, after automatic translation apps such as Google Translate appeared, even simple travel conversations became much easier.<\/p>\n\n\n\n

At that time, however, users still had to type their language in order to translate it. In that sense, it was somewhat inconvenient, similar to how officials from Korea used to communicate with envoys from China or Japan through written Chinese characters.<\/p>\n\n\n\n

As AI technology continued to develop, translation became much more convenient. Today, simply pointing a camera at street signs or restaurant menus allows the text to be translated instantly. In addition, translation apps can recognize speech directly and translate it without the need for manual typing.<\/p>\n\n\n\n

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AI models can understand text in images and human speech because they are trained not only on text but also on multimodal <\/mark>data, including images, speech, and video<\/strong>. Flitto also develops speech recognition and translation AI models and provides a Live Translation service<\/a><\/mark> that enables real-time interpretation<\/strong>. As overseas clients in regions such as the United States, Japan, China, and the Middle East continue to increase, Flitto\u2019s Live Translation service was used at 442 conferences across 13 countries in 2025.<\/strong><\/p>\n\n\n\n

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Recently, speech recognition performance for major languages such as English, Chinese, Spanish, and French has improved significantly. As a result, demand for speech data<\/mark> from minority languages and regional dialects has also increased.<\/strong> In the case of Korean, companies building speech recognition models initially trained their systems mostly using standard Korean spoken in the Seoul metropolitan area. Over time, additional speech data from regional dialects such as those spoken in Gyeongsang, Jeolla, and Jeju regions were added. Similarly, speech data is now being expanded to include English spoken outside the United States and the United Kingdom, Spanish spoken in Latin America, and various regional dialects of Arabic rather than only standard Arabic.<\/p>\n\n\n\n

There are countless languages around the world, and speech differs significantly from parallel corpora used in machine translation. Even when the same sentence is spoken, the way it is pronounced can vary depending on region, gender, age, and other factors. For this reason, it is necessary to collect as much speech data as possible.<\/strong><\/p>\n\n\n\n

Companies that build speech recognition models often face limitations in collecting large amounts of speech data on their own. To address this demand, Flitto has focused on collecting speech data along with parallel corpora since the early stages of the company.<\/p>\n\n\n\n

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Collecting Speech Using Text<\/h2>\n\n\n\n
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One of the simplest ways to collect speech data is to provide sentences and ask participants to read them aloud. Flitto has built a data warehouse <\/mark><\/strong>using text data collected over the years, which includes not only written sentences but also many conversational expressions. By extracting sentences from the data warehouse and opening speech collection events on the Arcade platform<\/mark><\/strong>, users can participate and record their voices by reading the provided sentences.<\/p>\n\n\n\n

Unlike parallel corpus tasks that require foreign language skills, speech data collection only requires participants to read sentences in their native language. This makes it possible for people of all ages and backgrounds to participate, allowing speech data to be collected quickly.<\/p>\n\n\n\n

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Korean sentence:
\u201cThe weather suddenly became cold today, so it feels like winter again.\u201d<\/p>\n\n\n\n