How to Make an English-Language Neural Network Read Russian

A Habr author has published a piece on how to make English-language speech synthesis neural networks (TTS, text-to-speech) sound Russian. The article opens by acknowledging that TTS is gradually taking over part of the work of professional narrators and voice actors. It then offers a review of free models that require no credits, no subscriptions and no linked bank card, with a caveat: far from all of them support Russian at all, and those that do often show a noticeable accent.

What exactly the author tested

The core of the piece is a practical comparison. The author generates voiceovers of the same text in English and in Russian using several free neural speech synthesis models, to assess how much sound and pronunciation quality differ between the two languages. This approach answers a question that the marketing materials of model developers rarely address: how does a model trained mainly on an English corpus handle the phonetics and intonation of a language it was not originally designed for?

Russian is objectively harder for speech synthesis than most Western European languages. Its free stress can fall on different syllables in related words, its rich system of case endings affects pronunciation, and its abundance of sibilants and soft consonants demands a far more refined phonetic model than, say, English with its relatively predictable intonation. Most open TTS models are trained on English-language datasets first, simply because that is where the most openly available data is, and Russian support is often added later and less carefully.

What problems English-language models have with Russian

The key finding is the accent. The author compares the sound of some models to Arnold Schwarzenegger's pronunciation in the film Red Heat, where the actor plays a Soviet militiaman with a recognizable but clearly non-native Russian accent. The comparison captures a typical problem of TTS models trained mainly on English speech: even when a model can formally pronounce Russian words, stress, intonation contours and the softness of consonants are often rendered incorrectly. The result sounds recognizable but unnatural, like a foreigner rather than a native speaker.

Key facts:

• The piece compares free TTS models in English and Russian
• Selection criterion: no credits, no subscriptions and no linked card
• Not all of the tested models support Russian
• Some models that do support Russian have a noticeable accent, comparable to Schwarzenegger's character in Red Heat

Should you use such models for Russian voiceover?

The article's practical conclusion concerns applicability. Even if a model is free and generally impressive in English, a Russian-language project, whether a video voiceover, a podcast or a voice interface, needs a separate check of how it handles Russian phonetics, rather than relying on the general impression from English-language demos. The piece essentially gives readers a checklist for their own evaluation: test the model on your native-language text, compare the pronunciation with real Russian speech, and only then decide whether you can overlook the language limitations for the sake of zero cost, or whether the task still calls for a paid model with explicit Russian support.

For authors who create Russian-language content on their own, such as bloggers, teachers and indie game developers, comparative reviews like this are especially valuable. They save the time of testing a dozen models by hand and let you go straight to the few that sound acceptable in Russian, without spending resources on models never meant for it. For many non-professional uses, such as draft voiceovers, test versions of a product and personal projects, free English-language models may turn out to be a workable compromise. But for content aimed at a broad Russian-speaking audience, the accent the author describes will most likely prove unacceptable.