> ## Documentation Index > Fetch the complete documentation index at: https://docs.miraiminds.co/llms.txt > Use this file to discover all available pages before exploring further. # Transcribe recorded calls > Turn a recorded call into a transcript with speakers and timestamps, in the console or through the API, at ₹18 per hour of audio. Mira Transcribe turns a recording into text: what was said, who said it and when. You send a file or a link and get a job ID straight away. A draft is readable within seconds, and the finished transcript replaces it when it is ready. A two-minute call usually takes about 30 seconds. Base URL `https://sandbox.voice.miraiminds.co`. API requests use `Authorization: Bearer sk_live_…`, the same workspace key as the rest of the [v2 API](/v2/overview). ## When to use it | You have | Use | | :- | :- | | A recording of a call that has already happened: your team's calls, calls from another dialler, a recorded interview | Offline transcription, on this page | | A call one of your Mirai voice agents made | That call's own transcript: [`GET /v2/calls/{id}/transcript`](/v2/calls#get-the-transcript). You don't need to send its recording here. | | Live audio that you need as text while people are still talking | Streaming recognition. It runs inside every voice agent; as a standalone API it is in private preview, so ask us for access. | Turning example calls into a node-based agent has its own transcription step, priced separately. See [Draft a flow from call recordings](/v2/node-agents#draft-a-flow-from-call-recordings). ## How it works Two speech recognition passes listen to the whole recording. A language model then compares them and writes one transcript, using any context and vocabulary you sent to settle names and terms. Speaker separation listens to the voices themselves to work out who spoke when, and gives each voice its own ID. While the language model works, the job carries a draft: the stronger of the two passes, with timestamps and no speakers. In the draft, English is often written out in Devanagari. The finished transcript writes Hindi in Devanagari and English in Latin script, the way the speakers switched between them. Common English loanwords can stay in Devanagari. Nothing is translated. ```text theme={null} Draft यस टेल मी आई वॉन्टेड टू आस्क अबाउट द बी बी ए कॉर्स फ़ीस Finished yes tell me I wanted to ask about the BBA course fees ``` A job moves through `queued`, `decoding` and `merging` to `completed` or `failed`. The [reference](/v2/transcriptions#statuses) describes each status. ## Try it in the console Sign in to the [console](https://sandbox.voice.miraiminds.co), open **Speech to text** and choose **Offline**. Choose one recording or several: WAV, MP3 or M4A, up to 45 MB each. Add a line of context and any names or terms to spell right, then click **Transcribe**. Each recording gets a row with its length, a clock and its stage. Open it as soon as the draft appears. The finished transcript takes its place in the player on its own. The player shows the recording as a timeline with a lane for each speaker. The transcript scrolls with the audio, and clicking a line plays from there. You can rename, recolour and merge speakers, move a line to another speaker, fix words, and split or join lines, with undo. Exports are plain text, SRT and WebVTT subtitles, and JSON. Edits are kept in your browser, which also keeps a copy of your last few uploads for up to a week so you can play them back. **Logs** lists every recording your workspace sent in the last 30 days, from the console or the API, with what each one cost. **API** has the requests on this page ready to copy, and can create a key for you. Jobs from the console are charged to the workspace wallet in the same way as API jobs. ## Use the API Send the recording as a multipart upload: ```bash theme={null} curl -X POST https://sandbox.voice.miraiminds.co/v2/transcriptions \ -H "Authorization: Bearer $MIRAI_API_KEY" \ -H "Idempotency-Key: call-2026-10-02-0412" \ -F file=@call.wav \ -F context="A call to a university admissions desk about a course and its fees" \ -F vocabulary="Mira University, BBA, Aadhaar" ``` The answer is `202 Accepted` with the job, whose `status` is `queued`. Read it every few seconds until `status` is `completed` or `failed`: ```bash theme={null} curl https://sandbox.voice.miraiminds.co/v2/transcriptions/trn_01M3XRSFXW77RHEQ85979AJXAF \ -H "Authorization: Bearer $MIRAI_API_KEY" ``` A recording over 45 MB goes by link instead: send JSON with an `https` `url` (up to 200 MB), such as a pre-signed link to your storage. The [Transcriptions reference](/v2/transcriptions) has every field, response and error, with Python and Node.js. To build a review screen on top of this, follow the [transcript player cookbook](/cookbooks/transcript-player). ## Speakers and timestamps A finished job has one segment for each turn: ```json theme={null} { "speaker": "Customer", "speaker_id": "spk1", "start": 7.21, "end": 11.32, "text": "yes tell me I wanted to ask about the BBA course fees" } ``` `start` and `end` are seconds from the start of the recording. `speaker_id` is the voice: `spk0`, `spk1` and so on, numbered in the order the voices first speak. Group lines by it. `speaker` is a role, `Agent`, `Customer` or `Other`, worked out from what each voice says. It is a best guess and can be wrong, so show it as a first label that a person can change. It is empty when the role could not be told. `diarization.speakers` lists each voice once, with its role and how many seconds it talked. Send `words: true` for the time of every word. Word timings are added when they line up with the audio, which today means Hindi recordings; Gujarati and English recordings come back without them. `diarization.words.applied` tells you whether they were added. They need speaker separation, which is on unless you send `diarize: false`. ## Languages Mira Transcribe is built for phone calls in Hindi and Hinglish. `language` defaults to `auto`, which detects the main language of the call. You can set it to `hi`, `gu`, `en`, `mr`, `pa`, `bn` or `ur` when you know the main language and detection gets it wrong. Speech in another language inside the call is kept as it was spoken. ## Getting names and terms right `vocabulary` takes names, brands, products, places and codes, spelled the way you want them back. Send up to 200 terms of up to 100 characters each, as one string separated by commas or new lines, or as a JSON array. A term can't contain a comma, and repeats are dropped. `context` is a sentence or two about the call: who is calling whom, and why. It can be up to 2,000 characters. Both affect spelling and script. We sent the same 23-second test call twice. With an unrelated context, "Mira University" and "Aadhaar" came back as "मीरा यूनिवर्सिटी" and "आधार". With the context and vocabulary in the example above, both came back as written. Use the same context and vocabulary for every call of one kind. ## Pricing Transcription costs **₹18 per hour of audio** on every plan. Prices exclude GST. * A job is charged by the length of the recording, to the millisecond, rounded up to the paisa once. A 23-second call costs ₹0.12 and a five-minute call ₹1.50. * The charge is taken from your [wallet](/v2/wallet) once, when the job completes. It is taken whether or not you read the result. * A degraded job is free. So is a job that fails for any reason. * The rate is fixed on each job when it is accepted, and `cost` on the job says what it was charged. * Starting a job needs a wallet balance above zero, and nothing is held while it runs. With an empty wallet the request is refused with `402 insufficient_balance`. Each charge is one wallet transaction with `kind: "transcription"`, the job ID as `reference` and the billed seconds as `quantity`. The billing statement in the console shows transcription under **Charges**, with the number of recordings and minutes of audio. ### Degraded jobs When the language model step is unavailable, the job still completes with the stronger recognition pass and `degraded: true`. The words are there with their timestamps, but there are no roles and the text has had less clean-up. Speaker IDs can still be present. A degraded job is not charged. If you need the roles, send the recording again; the new job is charged when it completes in full. ## Limits | Limit | Value | | :- | :- | | Uploaded file | 45 MB | | Recording sent by link | 200 MB | | Length of a recording | 2 hours | | Unfinished jobs per workspace | 20 | | New jobs per workspace | 120 an hour | Over a limit, the request is refused with `413` or `429` and nothing is charged. A recording longer than two hours is accepted, then fails with `audio_too_long`, free. See [limits and errors](/v2/transcriptions#limits) for every code. ## Privacy and your data The API does not keep your audio. An upload passes through a temporary file that is deleted when the request ends, and the transcription service deletes the recording once it has decoded it. A recording link is fetched once and is not stored. The transcript stays with the transcription service, so that `GET /v2/transcriptions/{id}` can return it. There is no published retention period for transcripts yet, so copy each finished transcript into your own storage. If a transcript is no longer available, its job still reads `completed` with its cost, but without `text` and `segments`. The job record itself (status, file name, size, length and cost) stays with your workspace and appears in **Logs**. There is no endpoint to delete a transcript; if you need one removed, write to [help@miraiminds.co](mailto:help@miraiminds.co). Recordings and transcripts of calls are personal data under India's Digital Personal Data Protection Act, and under laws such as the GDPR when they cover people elsewhere. Tell the people on your calls that they are recorded and transcribed, and get consent where the law asks for it. Keep your API key on your server: send recordings from your backend, never from a browser or a mobile app. ## Troubleshooting | Symptom | Likely cause | Fix | | :- | :- | :- | | `402 insufficient_balance` | The wallet balance is zero or below. | Add credit in **Billing**, then send the request again. | | `413 request_too_large` | The file is over 45 MB, or the file at `url` is over 200 MB. | Send a large file by link, or compress it to a mono MP3. | | `400` with "the recording url answered HTTP 403" | The link has expired or is private. | Send a fresh pre-signed link. We fetch it as soon as the request arrives. | | `429 at_capacity` | Your workspace already has 20 unfinished jobs. | Wait for `Retry-After`, or queue uploads on your side. | | The job fails with `transcription_failed` | The file is not audio, is damaged, or has no speech. | Check that it plays. WAV and MP3 work everywhere. | | The job fails with `engine_restarted`, `job_lost`, `timed_out` or `submit_interrupted` | Something went wrong on our side. | Send the recording again. The failed job is free. | | Names and brands are misspelled | No `vocabulary` or `context` was sent. | Add the names to `vocabulary`, and a line of `context`. | | Roles are swapped, or two voices share a role | Roles are a best guess. | Group lines by `speaker_id` and let a person rename speakers. | | One person appears as two speaker IDs, or two people as one | Speaker separation can split or merge voices on poor audio, crosstalk or similar voices. | Merge or reassign speakers in your review screen. The console player can do both. | | No `words` on segments | `words` was not sent, `diarize` was `false`, or the recording is not in Hindi. | Send `words: true` with speaker separation on. | | `completed`, but no `text` | The transcript is no longer kept. | Save transcripts when they complete. | ## Related Every field, status, response and error code. Upload, draft, finished transcript, playback, edits and export in your own web app. Balance, transactions and top-ups. Transcripts of calls your voice agents made. This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.