MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202641123946 A) filed by Sns Collegeof Technology on October 16, 2026, for Ai-Based Multilingual Voice-To-Text Transcription And Intelligent Speech Understanding System For Audio And Video Content.
Inventors include Sunil. Bm; Vignesh Sanjay. C. A; Sugunthan. M; Dinesh. K; Jai Hithesh. K; Bavani. S; Sathish. M; Vishnu Priya A; Ashwini Selvakumari S; and Pranesh J.
The application for the patent was published on October 30, 2026, under issue no. 44/2026.
Abstract: The present invention relates to an Artificial Intelligence (AI)-based multilingual voice-to-text transcription and intelligent speech understanding system for converting spoken audio and video content into accurate written text. The proposed system provides an intelligent platform capable of receiving live audio, recorded audio, or video content and automatically converting spoken speech into structured textual information. The system employs Artificial Intelligence, Machine Learning, Deep Learning, Automatic Speech Recognition (ASR), Natural Language Processing (NLP), and audio signal processing techniques to identify speech, reduce background noise, detect spoken languages, and generate corresponding textual transcripts. The system is capable of processing multilingual and mixed-language speech, including English, Tamil, Hindi, and other supported languages. An intelligent language identification module automatically detects the spoken language and selects an appropriate speech recognition model. The system further identifies multiple speakers, assigns speaker labels, generates timestamps, restores punctuation, and structures the recognized text into readable sentences and paragraphs. A contextual correction module analyzes the generated transcript using Natural Language Processing to correct recognition errors, improve grammar, restore punctuation, and identify domain-specific terminology. The system may further generate summaries, important keywords, action items, and topic-wise notes from the converted speech content. The proposed invention supports both real-time speech-to-text conversion and offline processing of uploaded audio or video files. The system may generate transcripts and subtitles in multiple formats and may optionally translate the recognized text into another language. The invention reduces the manual effort required for transcription, improves accessibility for hearing-impaired individuals, enables efficient documentation of lectures, meetings, interviews, and videos, and provides an intelligent, scalable, and adaptive platform for speech-based information processing.
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