Azure Speech to Text
Quickly and accurately transcribe audio to text in more than 85 languages and variants. Customize models to enhance accuracy for domain-specific terminology. Get more value from spoken audio by enabling search or analytics on transcribed text or facilitating action, all in your preferred programming language. Get accurate audio to text transcriptions with state-of-the-art speech recognition. Add specific words to your base vocabulary or build your own speech-to-text models. Run Speech to Text anywhere, in the cloud or at the edge in containers. Access the same robust technology that powers speech recognition across Microsoft products. Convert audio to text from a range of sources, including microphones, audio files, and blob storage. Use speaker diarisation to determine who said what and when. Get readable transcripts with automatic formatting and punctuation. Tailor your speech models to understand organization- and industry-specific terminology.
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Subanana
Subanana is an AI speech-to-text web app that turns audio and video into subtitles, transcripts, and meeting summaries in 80+ languages, with standout accuracy on Asian and mixed-language speech (Cantonese, Mandarin, Japanese, Korean, and code-switching) that English-first tools handle poorly.
Subtitles: import a file or a YouTube/Instagram/Facebook link, edit with a glossary and AI auto-correct, and export SRT, VTT, TXT, DOCX, bilingual subtitles, or burned-in video.
Transcripts: speaker labels, filler-word removal, automatic punctuation and paragraphs.
Meeting summaries: templates, decisions and action items, plus a Google Meet and Microsoft Teams recording bot that processes the meeting after it ends.
Live captions: real-time captioning with translation for events.
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MAI-Transcribe-1.5
MAI-Transcribe-1.5 is Microsoft AI’s production-ready speech-to-text model for turning noisy audio into highly accurate, domain-aware transcripts across 43 languages. It delivers consistent, high-accuracy transcription across languages, accents, speaking styles, and challenging audio conditions, with automatic language detection included. The model is designed for real-world audio where speech often comes through conference rooms, phone lines, busy streets, low-quality recordings, background noise, and overlapping speakers. MAI-Transcribe-1.5 adapts transcription to domain-specific terminology, making it ready for captions, call analysis, accessibility, meeting transcription, doctor’s notes, pharma customer calls, content workflows, and other enterprise speech use cases out of the box. It uses contextual biasing to improve recognition of specialized vocabulary, names, industry language, and terms that generic transcription systems may miss.
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Ecango
Ecango is an AI-powered audio and video transcription tool that converts spoken content into accurate, searchable text in seconds. Users can upload or drag and drop audio or video files, let Ecango generate the transcript, then edit it directly in the browser and export it in popular formats including DOCX, ODT, PDF, SRT, and TXT. It supports transcription, subtitles, and translation across more than 90 languages, dialects, and accents, using advanced speech recognition to deliver up to 99.8% accuracy. Speaker identification and diarization detect different people speaking within the same recording and organize their dialogue into an easy-to-read transcript. Ecango supports popular audio and video formats and automatically handles video files without requiring users to separate the audio first. Its AI can also filter background noise to improve transcription and translation results when recordings are less than ideal.
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