Speech recognition models turn calls, meetings and voice messages into searchable, analyzable text. Local deployment matters when call recordings must stay in-house. Check accuracy in your languages and with background noise, speaker separation, the license and speed on your hardware.
Fast NVIDIA speech recognition models, including streaming ones for real-time use. Parakeet TDT v3 and Nemotron 3.5 ASR understand Russian. The new Nemotron 3.5 Transcribe (34B, 4.3B active, OpenMDW 1.1) transcribes recordings of up to an hour in 40 languages, translates speech, splits it by speaker, puts word timestamps and answers questions about the content (questions in English only); all tasks are available for Russian. Ready files only, live streaming is not supported. The figures are the authors: 5.33% word errors on English in the open Hugging Face leaderboard.
One model for developers: reads documents and tables, transcribes speech with speaker labels, finds objects in an image and answers strictly by a JSON schema you supply. Inside is a reasoning core and a set of narrow specialist models.
parsing documents and tables with text coordinates
transcribing recordings with speaker labels
extracting data from documents into a given JSON schema
Sizes
a model that needs 80 GB of video memory (the core is based on Qwen3.8-27B)
Speech recognition in a single 16.9 MB file: runs on a phone, watch, robot and CPU without a graphics card. Languages: English, German, French, Spanish, Italian, Dutch, Polish. Gives word timestamps.
Mistral's speech models: they understand audio, transcribe and answer questions about a recording. The Realtime version recognizes speech live and supports Russian; speech synthesis and a separate version for Arabic dialects are also available.
Streaming recognition of Chinese and English speech with a 240-560 ms delay. It can listen indefinitely without memory growth and tells a thinking pause from the end of a turn.
A very compact English speech recognition model: 164 MB, close in accuracy to its large Parakeet base. Transcribes an hour of audio in about 20 seconds on a laptop.
Xiaomi models for reasoning and agents: from the compact MiMo-7B to MiMo-V2.6-Pro with 1.02 trillion parameters. The larger versions understand text, images, video and audio, with a 1M token context. Languages: English and Chinese.
Microsoft speech models: long multi-voice dialogue synthesis, fast synthesis for live conversation, and recognition of long recordings split by speaker, including in Russian.
Very small and fast speech recognition models for phones, tablets and embedded devices. Version 2 streams, producing text while the person is still speaking.
Aigiz Kunafin (AigizK), member of the SLONE community · Russia
Years of work by one enthusiast around the Bashkir Common Voice project: Whisper, wav2vec2, w2v-BERT and GigaAM fine-tuned for Bashkir, Tatar and Mari. Quality differs between models, so test them on your own recordings.
Transcribing calls and meetings in Bashkir and Tatar
Sber's models for Russian speech recognition, among the most accurate for Russian. Includes emotion recognition, v3 with punctuation, and a multilingual version (Russian, Kazakh, Kyrgyz, Uzbek).
Cohere's speech recognition model for 14 languages (Russian is not on the list), with a separate version for Arabic. Built for accurate transcription of business recordings.
Expressive speech and dialogue synthesis with voice cloning, plus recognition models. Version 3 of the synthesis supports about 100 languages, including Russian, but is non-commercial.
Streaming speech recognition and synthesis models from the makers of Moshi: they start speaking and transcribing without waiting for the end of a phrase. Pocket TTS (100M) runs on a CPU. English, French and a few other European languages, no Russian.
Streaming speech transcription for voice bots
Voicing replies with minimal delay
Speech synthesis on a server without a GPU (Pocket TTS)
Speech recognition for 1,600+ languages, including Russian and rare languages no system supported before. A new language can be added from a few examples.
Russian-language fine-tunes of open models (Mistral, Qwen, Llama) by the independent Vikhr team, with compact versions for a regular PC. Borealis is an audio model for recognizing and understanding Russian speech.
Russian-language assistant on your own PC or server
About two dozen Whisper, wav2vec2 and WavLM fine-tunes for Karelian, including recordings where the speaker switches from Karelian to Russian. The model cards are empty, so quality must be checked on your own recordings.
Transcribing field and archive recordings in Karelian
The most widely used open tool for splitting a recording by speaker: who spoke and when. Usually paired with speech recognition. Weights are issued after a short form on HF.
Tagging calls: which part is the agent, which is the customer
Meeting minutes with speaker labels
Preparing recordings for transcription and analysis
Offline Russian speech recognition that runs even on a Raspberry Pi or a phone, without internet. Streaming models for live audio and simple Russian speech synthesis, Vosk TTS, are available.
Transcribing Russian calls and recordings without the cloud
A general-purpose audio model: speech recognition, answering questions about sounds, detecting emotions and voice dialogue. Trained on 13 million hours of audio; languages are English and Chinese.
Speech recognition in 99 languages, including Russian. The de facto standard for transcribing calls and meetings. Hugging Face's faster Distil-Whisper is English only.
Speech and text translation across roughly a hundred languages, including Russian: speech to text, speech to speech, and streaming translation that keeps intonation.
Meta speech models covering more than a thousand languages. The supported list includes Bashkir, Tatar, Chuvash, Sakha, Ossetian, Chechen, Avar, Udmurt, Mari, Erzya, Moksha, Kalmyk and Karelian. Quality varies a lot by language, so test it on your own recordings.
