25.06.26 (inclusive)

contractual

MVP

ICT tasks

Robotics

Neurotechnology and artificial Intelligence

Software/ IS

In the practical application of speech recognition and offline speech analysis technologies, a significant obstacle is the inconsistency of audio materials with the requirements for correct information processing. Dialogues between two speakers are often recorded in the same audio channel, which makes it difficult to automatically separate them for later analysis and shorthand. Existing ASR solutions for Russian and Kazakh languages do not provide stable diorization, especially in mixed speech (code-switching), which leads to a decrease in the accuracy and readability of transcriptions.

The result of the development will be a software module that provides: 1. Automatic separation of audio recordings into replicas of two speakers (diorization) with an accuracy of at least 90%; 2. Correct speech recognition in Russian and Kazakh, including mixed utterances; 3. Formation of a structured transcript with timestamps and speaker IDs (Speaker 1, Speaker 2); 4. Compatibility with existing data analysis and storage systems via API; 5. The ability to use any external or local STT service that provides the required recognition quality.

Danchenko Maxim