deepgram-js-speech-to-text

Q: How do I install deepgram-js-speech-to-text?

Run npx skills add https://github.com/deepgram/deepgram-js-sdk --skill deepgram-js-speech-to-text in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/deepgram-js-speech-to-text/ (personal) or .claude/skills/deepgram-js-speech-to-text/ (project).

by deepgram OfficialMedia & Creative

Use when writing or reviewing JavaScript/TypeScript in this repo that calls Deepgram Speech-to-Text v1 (/v1/listen) for prerecorded or live audio transcription. Covers client.listen.v1.media.transcribeUrl / transcribeFile (REST) plus client.listen.v1.createConnection() / connect() (WebSocket). Use deepgram-js-audio-intelligence for summarize/sentiment/topics/diarize overlays, deepgram-js-conversational-stt for Flux turn-taking on /v2/listen, and deepgram-js-voice-agent for full-duplex assistants. Triggers include "transcribe", "speech to text", "STT", "listen.v1", "nova-3", "live transcription", and "websocket transcription".

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/deepgram/deepgram-js-sdk --skill deepgram-js-speech-to-text

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads deepgram-js-speech-to-text automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Using Deepgram Speech-to-Text (JavaScript / TypeScript SDK)

Basic transcription for prerecorded audio (REST) or live audio (WebSocket) via /v1/listen.

When to use this product

REST (client.listen.v1.media.transcribeUrl / transcribeFile) — one-shot transcription of a finished URL or file. Good for batch jobs, caption generation, offline processing.
WebSocket (client.listen.v1.createConnection() / connect()) — continuous streaming transcription. Good for live captions, microphone audio, telephony streams, browser or Node realtime apps.

Use a different skill when:

You also want summaries, topics, intents, sentiment, language detection, or redaction guidance on the same /v1/listen call → deepgram-js-audio-intelligence.
You need Flux turn-taking and end-of-turn events on /v2/listen → deepgram-js-conversational-stt.
You need a full interactive assistant with STT + LLM + TTS over one socket → deepgram-js-voice-agent.

Authentication

require("dotenv").config();

const { DeepgramClient } = require("@deepgram/sdk");

const deepgramClient = new DeepgramClient({
  apiKey: process.env.DEEPGRAM_API_KEY,
});

Use the exported DeepgramClient from src/CustomClient.ts, not DefaultDeepgramClient. The wrapper adds the required Token auth prefix, session headers, and patched WebSocket behavior.

Quick start — REST (prerecorded URL)

From examples/04-transcription-prerecorded-url.ts:

const data = await deepgramClient.listen.v1.media.transcribeUrl({
  url: "https://dpgr.am/spacewalk.wav",
  model: "nova-3",
  language: "en",
  punctuate: true,
  paragraphs: true,
  utterances: true,
});

console.log(
  "Transcription:",
  data.results?.channels?.[0]?.alternatives?.[0]?.transcript,
);

Quick start — REST (prerecorded file)

From examples/05-transcription-prerecorded-file.ts:

const { createReadStream } = require("fs");

const data = await deepgramClient.listen.v1.media.transcribeFile(
  createReadStream("./examples/spacewalk.wav"),
  {
    model: "nova-3",
    language: "en",
    punctuate: true,
    paragraphs: true,
    utterances: true,
    smart_format: true,
  }
);

transcribeFile(...) accepts multiple upload shapes in this SDK: fs.ReadStream, Buffer, ReadableStream, Blob, File, ArrayBuffer, and Uint8Array (see examples/23-file-upload-types.ts).

Quick start — WebSocket (live streaming)

From examples/07-transcription-live-websocket.ts:

const deepgramConnection = await deepgramClient.listen.v1.createConnection({
  model: "nova-3",
  language: "en",
  punctuate: "true",
  interim_results: "true",
});

deepgramConnection.on("message", (data) => {
  if (data.type === "Results") {
    console.log("Transcript:", data);
  }
});

deepgramConnection.connect();
await deepgramConnection.waitForOpen();

// Swap this for a mic capture (e.g. `node-microphone` / `MediaRecorder`)
// in real apps; the repo examples use `createReadStream` over a sample WAV.
const { createReadStream } = require("node:fs");
const audioStream = createReadStream("samples/spacewalk.wav");

audioStream.on("data", (chunk) => {
  deepgramConnection.sendMedia(chunk);
});

audioStream.on("end", () => {
  deepgramConnection.sendFinalize({ type: "Finalize" });
});

The repo examples use the two-step socket flow: createConnection() → register handlers → connect() → waitForOpen().

Key parameters / API surface

REST: model, language, punctuate, smart_format, paragraphs, utterances, multichannel, numerals, search, keyterm, keywords, encoding, sample_rate, callback, tag.
WSS connect args (src/api/resources/listen/resources/v1/client/Client.ts): model is required; common realtime flags include language, interim_results, endpointing, utterance_end_ms, vad_events, encoding, sample_rate, multichannel, punctuate, smart_format.
WSS client messages (src/api/resources/listen/resources/v1/client/Socket.ts): sendMedia(...), sendFinalize(...), sendCloseStream(...), sendKeepAlive(...).
WSS server events: Results, Metadata, UtteranceEnd, SpeechStarted.

API reference (layered)

In-repo reference: reference.md → Listen V1 Media for REST; WSS behavior lives in src/CustomClient.ts and src/api/resources/listen/resources/v1/client/{Client,Socket}.ts.
Canonical OpenAPI (REST): https://developers.deepgram.com/openapi.yaml
Canonical AsyncAPI (WSS): https://developers.deepgram.com/asyncapi.yaml
Context7: library ID /llmstxt/developers_deepgram_llms_txt
Product docs:
- https://developers.deepgram.com/reference/speech-to-text/listen-pre-recorded
- https://developers.deepgram.com/reference/speech-to-text/listen-streaming

Gotchas

Use DeepgramClient, not DefaultDeepgramClient. The custom wrapper adds Token auth, session IDs, browser WS auth protocols, and patched sockets.
Repo examples are two-stage for WSS. createConnection() does not open the socket; call connect() and usually waitForOpen().
Finalize before closing v1 streams. sendFinalize({ type: "Finalize" }) flushes the final partial.
Keep idle streams alive. Use audio or sendKeepAlive({ type: "KeepAlive" }) on long pauses.
Raw audio metadata must match reality. If you send PCM, encoding and sample_rate must match the bytes.
Browser auth differs from Node auth. In browsers, the wrapper moves auth/session info into WebSocket subprotocols because custom headers are unavailable.
Use /v2/listen only for Flux. If you need turn-aware conversational STT, switch skills instead of forcing v1.

Example files in this repo

examples/04-transcription-prerecorded-url.ts
examples/05-transcription-prerecorded-file.ts
examples/06-transcription-prerecorded-callback.ts
examples/07-transcription-live-websocket.ts
examples/08-transcription-captions.ts
examples/23-file-upload-types.ts
examples/27-deepgram-session-header.ts

Central product skills

For cross-language Deepgram product knowledge — the consolidated API reference, documentation finder, focused runnable recipes, third-party integration examples, and MCP setup — install the central skills:

npx skills add deepgram/skills

This SDK ships language-idiomatic code skills; deepgram/skills ships cross-language product knowledge (see api, docs, recipes, examples, starters, setup-mcp).

FAQ

What does the deepgram-js-speech-to-text skill do?

How do I install deepgram-js-speech-to-text?

Run npx skills add https://github.com/deepgram/deepgram-js-sdk --skill deepgram-js-speech-to-text in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/deepgram-js-speech-to-text/ (personal) or .claude/skills/deepgram-js-speech-to-text/ (project).

Which AI agents can use deepgram-js-speech-to-text?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is deepgram-js-speech-to-text safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains deepgram-js-speech-to-text?

It is published by deepgram in deepgram/deepgram-js-sdk, and it is an official skill from the maker of the technology it covers. It has 81 recorded installs.

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deepgram-js-speech-to-text

Install

Install

Describe the task

Review the result

SKILL.md

Using Deepgram Speech-to-Text (JavaScript / TypeScript SDK)

When to use this product

Authentication

Quick start — REST (prerecorded URL)

Quick start — REST (prerecorded file)

Quick start — WebSocket (live streaming)

Key parameters / API surface

API reference (layered)

Gotchas

Example files in this repo

Central product skills

FAQ

More from deepgram/deepgram-js-sdk

Popular media & creative skills