Focusing on the limited pronunciation dictionary in Russian speech synthesis and speech recognition system, a Russian grapheme-to-phoneme algorithm based on Long Short-Term Memory (LSTM) sequence-to-sequence model was proposed, as well as a phonetic transcription system. Firstly, a new Russian phoneme set based on Speech Assessment Methods Phonetic Alphabet (SAMPA) was designed, making transcription results can reflect the stress position and vowel reduction of Russian words, and a 20 000-word Russian pronunciation dictionary was constructed according to the new phoneme set. Then, the proposed algorithm was implemented by using the TensorFlow framework, in which the Russian word was converted into a fixed-length vector by encoding LSTM, and then the vector was converted into the target pronunciation sequence by decoding LSTM. Finally, the Russian phonetic transcription system was designed and implemented. The experimental results on out-of-vocabulary test set show that the word correct rate reaches 74.8%, and the phoneme correct rate reaches 94.5%, which are higher than those of Phonetisaurus method. The system can effectively support the construction of the Russian pronunciation dictionary.