CohereLabs / cohere-transcribe-03-2026

## Overview CohereLabs built cohere-transcribe-03-2026 for automatic speech recognition. It turns spoken audio into a single, readable text transcript. It uses a Conformer encoder with a Transformer decoder. The model converts audio into log-Mel features, then generates text tokens. This helps you turn recordings into searchable text for notes, analytics, and downstream automation. The model supports 14 languages: English, French, German, Italian, Spanish, Portuguese, Greek, Dutch, Polish, Chinese (Mandarin), Japanese, Korean, Vietnamese, and Arabic. ## What you can build - Meeting and interview transcripts for internal notes - Call-center QA transcripts for review and coaching - Searchable archives for podcasts, webinars, and trainings - Voice-of-customer text corpora for topic and sentiment analysis - Transcripts to feed into RAG pipelines and knowledge search - Accessibility captions that start from a raw transcript ## Inputs - An audio file for transcription. WAV and MP3 work directly. If you upload M4A, FLAC, OGG, or AAC, the platform may convert it before transcription. - A language choice using a 2-letter ISO-639-1 code. You must set the correct language. The model does not auto-detect it. - A limit on how much text the model can generate per internal audio chunk. This helps control very long outputs on long recordings. ## Outputs The model returns a speech-to-text transcript. - A single transcript string for the full recording. - Text includes the recognized words in reading order. - The output is text only. It does not include speaker labels. ## Recommended settings - For most meeting audio, keep the per-chunk text limit around 256 tokens. - Increase the per-chunk text limit for fast speakers or dense technical content. - Always set the language to match the recording. Don’t leave it on the wrong language. ## Limitations - No automatic language detection. Mixed-language audio can degrade quality. - No timestamps. You can’t align words to time without extra tooling. - No speaker diarization. Two people speaking will appear in one combined transcript. - Silence and low-volume noise can trigger hallucinated text. Add a noise gate or voice activity detection before transcription when possible. - Very noisy audio, far-field microphones, heavy overlap, or strong compression can reduce accuracy. - Long recordings are typically processed in smaller chunks and then merged. Bad cuts, music, or inconsistent audio levels can create awkward joins. - Some hosted deployments enforce an upload limit (often 25 MB). If you hit limits, compress or split the audio. ## Safety & compliance Cohere’s policies prohibit using their services for harmful or abusive content. This includes hate, sexual exploitation, and content that incites violence or self-harm. - Get consent before recording or transcribing other people. - Don’t submit audio that you don’t have rights to process. - Don’t use transcripts to enable disallowed content or targeted harassment.