RiverScript

MAI-Transcribe-2 is Microsoft AI’s most capable transcription model yet, designed to deliver fast, accurate speech recognition across a broad range of real-world audio. It supports speaker diarization to distinguish speakers and attribute words to the right person, along with word-level timestamps for precise alignment, search, navigation, and editing. Keyword biasing helps recognize domain-specific terminology, abbreviations, names, and other terms that can be difficult to distinguish from context alone. Developers can choose between configurable transcription styles: a verbatim setting that preserves filler words and false starts for compliance and analysis, or a clean setting that removes fillers for more readable captions, notes, and published transcripts. The model supports code-switching for conversations that naturally move between languages, including blended language pairs such as Hinglish and Spanglish, and can automatically identify the language being spoken.

ElevenLabs has introduced Scribe, an advanced Automatic Speech Recognition (ASR) model designed to deliver highly accurate transcriptions across 99 languages. Scribe is engineered to handle diverse real-world audio scenarios, providing features such as word-level timestamps, speaker diarization, and audio-event tagging. Benchmark tests, including FLEURS and Common Voice, demonstrate Scribe's superior performance over leading models like Gemini 2.0 Flash, Whisper Large V3, and Deepgram Nova-3, achieving the lowest word error rates in languages such as Italian (98.7%) and English (96.7%). Notably, Scribe also significantly reduces errors in languages that have been traditionally underserved, including Serbian, Cantonese, and Malayalam, where other models often exhibit error rates exceeding 40%. Developers can integrate Scribe through ElevenLabs' speech-to-text API, receiving structured JSON transcripts that include detailed annotations.