Russia Has Taught AI to Understand the Nuances of Russian Speech
A new Russian speech‑recognition system demonstrates a leap forward in linguistic sensitivity, capturing meaning more accurately while remaining resilient to challenging acoustic conditions.
A Russian‑Adapted Dialogue Model
Scientists at Novosibirsk State University have introduced an upgraded dialogue model based on OpenAI’s Whisper, deeply adapted to the specifics of the Russian language.
Typical speech‑recognition tools transcribe text entirely in lowercase, without capitalizing sentences, marking proper nouns, or structuring phrasing clearly. The new system formats text correctly, interprets meaning more precisely, and produces more accurate formulations that match the speaker’s intent.
Cross‑Training Neural Networks
Developers from the Laboratory of Applied Digital Technologies trained the model on more than 500 hours of conversational audio. To broaden linguistic diversity and communication styles, part of the training dataset was synthesized using neural networks. In effect, some AI models generated training samples for others, expanding vocabulary coverage and improving robustness in complex acoustic environments.
Testing on Public Speeches
The system was tested on recordings of speeches by academics and public figures, including Alexey Savvateyev, Andrei Lankov, and Vladimir Zhirinovsky. According to the researchers, the AI confidently handles live speech, while the greatest difficulty arises in content rich with specialized terminology, such as mathematical lectures.
The Challenge of Translation
Beyond recognition, the model also accurately translates Russian speech into English. At present, processing a voice request takes about 40 seconds, but NSU researchers plan to reduce this time to five.
Russian scientists continue strengthening their position in speech‑technology development, making voice‑driven services more intuitive and accessible for users.
