Real-time Streaming Transcription with Deepgram

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Implements real-time streaming transcription using Deepgram's WebSocket API. Use when building live transcription, voice interfaces, or real-time audio processing applications. Handles WebSocket connections, interim results, and audio data streaming.

Sby Skills Guide Bot
Data & AIIntermediate
6/2/2026
Claude CodeCursorWindsurfCopilotCodex
#deepgram#real-time-transcription#live-audio#streaming-speech#web-sockets

Recommended for

Automated summary

Implements real-time streaming transcription using Deepgram's WebSocket API for live audio processing.

Strengths

  • Full TypeScript implementation with event handlers
  • Includes browser microphone integration
  • Handles errors with auto-reconnect
  • Supports model and language configuration

Limitations

  • Requires a Deepgram API key and network connectivity
  • Latency can vary based on audio quality
  • Not suitable for pre-recorded audio
When to use it

Use for building live transcription, voice interfaces, or real-time audio processing applications.

When not to use it

Do not use for non-real-time batch transcription or when offline speech recognition is needed.

Security analysis

Safe
Quality score85/100

The skill provides guidance and code examples for using Deepgram's WebSocket API. It does not contain any destructive or exfiltrating commands, and the allowed Bash tools are for standard package installation.

No concerns found

How this analysis is made

Examples

Real-time streaming setup
Set up a real-time streaming transcription service with Deepgram using the WebSocket API.
Live microphone transcription
Implement a live transcription client that captures microphone audio and displays interim results.
Streaming pipeline with error handling
Create a Deepgram streaming pipeline with auto-reconnect and error handling.

name: deepgram-core-workflow-b description: | Implement real-time streaming transcription with Deepgram. Use when building live transcription, voice interfaces, or real-time audio processing applications. Trigger with phrases like "deepgram streaming", "real-time transcription", "live transcription", "websocket transcription", "voice streaming". allowed-tools: Read, Write, Edit, Bash(npm:), Bash(pip:), Grep version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io

Deepgram Core Workflow B: Real-time Streaming

Overview

Implement real-time streaming transcription using Deepgram's WebSocket API for live audio processing.

Prerequisites

  • Completed deepgram-install-auth setup
  • Understanding of WebSocket patterns
  • Audio input source (microphone or stream)

Instructions

Step 1: Set Up WebSocket Connection

Initialize a live transcription connection with Deepgram.

Step 2: Configure Stream Options

Set up interim results, endpointing, and language options.

Step 3: Handle Events

Implement handlers for transcript events and connection lifecycle.

Step 4: Stream Audio Data

Send audio chunks to the WebSocket connection.

Output

  • Live transcription WebSocket client
  • Event handlers for real-time results
  • Audio streaming pipeline
  • Graceful connection management

Error Handling

| Error | Cause | Solution | |-------|-------|----------| | Connection Closed | Network interruption | Implement auto-reconnect | | Buffer Overflow | Too much audio data | Reduce sample rate or chunk size | | No Transcripts | Silent audio | Check audio levels and format | | High Latency | Network/processing delay | Use interim results |

Examples

TypeScript WebSocket Client

// services/live-transcription.ts
import { createClient, LiveTranscriptionEvents } from '@deepgram/sdk';

export interface LiveTranscriptionOptions {
  model?: 'nova-2' | 'nova' | 'enhanced' | 'base';
  language?: string;
  punctuate?: boolean;
  interimResults?: boolean;
  endpointing?: number;
  vadEvents?: boolean;
}

export class LiveTranscriptionService {
  private client;
  private connection: any = null;

  constructor(apiKey: string) {
    this.client = createClient(apiKey);
  }

  async start(
    options: LiveTranscriptionOptions = {},
    handlers: {
      onTranscript?: (transcript: string, isFinal: boolean) => void;
      onError?: (error: Error) => void;
      onClose?: () => void;
    } = {}
  ): Promise<void> {
    this.connection = this.client.listen.live({
      model: options.model || 'nova-2',
      language: options.language || 'en',
      punctuate: options.punctuate ?? true,
      interim_results: options.interimResults ?? true,
      endpointing: options.endpointing ?? 300,
      vad_events: options.vadEvents ?? true,
    });

    this.connection.on(LiveTranscriptionEvents.Open, () => {
      console.log('Deepgram connection opened');
    });

    this.connection.on(LiveTranscriptionEvents.Transcript, (data: any) => {
      const transcript = data.channel.alternatives[0].transcript;
      const isFinal = data.is_final;

      if (transcript && handlers.onTranscript) {
        handlers.onTranscript(transcript, isFinal);
      }
    });

    this.connection.on(LiveTranscriptionEvents.Error, (error: Error) => {
      console.error('Deepgram error:', error);
      handlers.onError?.(error);
    });

    this.connection.on(LiveTranscriptionEvents.Close, () => {
      console.log('Deepgram connection closed');
      handlers.onClose?.();
    });
  }

  send(audioData: Buffer): void {
    if (this.connection) {
      this.connection.send(audioData);
    }
  }

  async stop(): Promise<void> {
    if (this.connection) {
      this.connection.finish();
      this.connection = null;
    }
  }
}

Browser Microphone Integration

// services/microphone.ts
import { LiveTranscriptionService } from './live-transcription';

export async function startMicrophoneTranscription(
  onTranscript: (text: string, isFinal: boolean) => void
): Promise<{ stop: () => void }> {
  const service = new LiveTranscriptionService(process.env.DEEPGRAM_API_KEY!);

  // Get microphone access
  const stream = await navigator.mediaDevices.getUserMedia({ audio: true });

  // Create audio context and processor
  const audioContext = new AudioContext({ sampleRate: 16000 });
  const source = audioContext.createMediaStreamSource(stream);
  const processor = audioContext.createScriptProcessor(4096, 1, 1);

  // Start transcription
  await service.start({
    model: 'nova-2',
    interimResults: true,
    punctuate: true,
  }, {
    onTranscript,
    onError: console.error,
  });

  // Process audio
  processor.onaudioprocess = (event) => {
    const inputData = event.inputBuffer.getChannelData(0);
    const pcmData = new Int16Array(inputData.length);

    for (let i = 0; i < inputData.length; i++) {
      pcmData[i] = Math.max(-32768, Math.min(32767, inputData[i] * 32768));
    }

    service.send(Buffer.from(pcmData.buffer));
  };

  source.connect(processor);
  processor.connect(audioContext.destination);

  return {
    stop: () => {
      processor.disconnect();
      source.disconnect();
      stream.getTracks().forEach(track => track.stop());
      service.stop();
    }
  };
}

Node.js with Audio File Streaming

// stream-file.ts
import { createReadStream } from 'fs';
import { LiveTranscriptionService } from './services/live-transcription';

async function streamAudioFile(filePath: string) {
  const service = new LiveTranscriptionService(process.env.DEEPGRAM_API_KEY!);

  const finalTranscripts: string[] = [];

  await service.start({
    model: 'nova-2',
    punctuate: true,
    interimResults: false,
  }, {
    onTranscript: (transcript, isFinal) => {
      if (isFinal) {
        finalTranscripts.push(transcript);
        console.log('Final:', transcript);
      }
    },
    onClose: () => {
      console.log('Complete transcript:', finalTranscripts.join(' '));
    },
  });

  // Stream file in chunks
  const stream = createReadStream(filePath, { highWaterMark: 4096 });

  for await (const chunk of stream) {
    service.send(chunk);
    // Pace the streaming to match real-time
    await new Promise(resolve => setTimeout(resolve, 100));
  }

  await service.stop();
}

Python Streaming Example

# services/live_transcription.py
from deepgram import DeepgramClient, LiveTranscriptionEvents, LiveOptions
import asyncio

class LiveTranscriptionService:
    def __init__(self, api_key: str):
        self.client = DeepgramClient(api_key)
        self.connection = None
        self.transcripts = []

    async def start(self, on_transcript=None):
        self.connection = self.client.listen.asynclive.v("1")

        async def on_message(self, result, **kwargs):
            transcript = result.channel.alternatives[0].transcript
            if transcript and on_transcript:
                on_transcript(transcript, result.is_final)

        async def on_error(self, error, **kwargs):
            print(f"Error: {error}")

        self.connection.on(LiveTranscriptionEvents.Transcript, on_message)
        self.connection.on(LiveTranscriptionEvents.Error, on_error)

        options = LiveOptions(
            model="nova-2",
            language="en",
            punctuate=True,
            interim_results=True,
        )

        await self.connection.start(options)

    def send(self, audio_data: bytes):
        if self.connection:
            self.connection.send(audio_data)

    async def stop(self):
        if self.connection:
            await self.connection.finish()

Auto-Reconnect Pattern

// services/resilient-live.ts
export class ResilientLiveTranscription {
  private service: LiveTranscriptionService;
  private reconnectAttempts = 0;
  private maxReconnectAttempts = 5;

  async connect(options: LiveTranscriptionOptions) {
    try {
      await this.service.start(options, {
        onClose: () => this.handleDisconnect(options),
        onError: (err) => console.error('Stream error:', err),
      });
      this.reconnectAttempts = 0;
    } catch (error) {
      await this.handleDisconnect(options);
    }
  }

  private async handleDisconnect(options: LiveTranscriptionOptions) {
    if (this.reconnectAttempts < this.maxReconnectAttempts) {
      this.reconnectAttempts++;
      const delay = Math.pow(2, this.reconnectAttempts) * 1000;
      console.log(`Reconnecting in ${delay}ms...`);
      await new Promise(r => setTimeout(r, delay));
      await this.connect(options);
    }
  }
}

Resources

Next Steps

Proceed to deepgram-common-errors for error handling patterns.

From the file to a first result

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View the source and supporting files

This download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.

1. Download the file

Download SKILL.md

From the root of a test project, save the file as .skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.

mkdir -p '.skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/real-time-streaming-transcription-with-deepgram-mmlj2oyz/download' --output '.skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz/SKILL.md.part' && mv '.skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz/SKILL.md.part' '.skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz/SKILL.md'

2. Check prerequisites

Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

Tools declared by the author (check availability in your agent): Read, Write, Edit, Bash(npm:*), Bash(pip:*), Grep

Original excerpt: Prerequisites
  • Completed deepgram-install-auth setup
  • Understanding of WebSocket patterns
  • Audio input source (microphone or stream)

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.

Claude Code
test -f '.skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz/SKILL.md' && test -s '.skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/deepgram-core-workflow-b' && cp -R '.skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz' '.claude/skills/deepgram-core-workflow-b'

Cursor
test -f '.skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz/SKILL.md' && test -s '.skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz/SKILL.md' && mkdir -p '.cursor/skills' && test ! -e '.cursor/skills/deepgram-core-workflow-b' && cp -R '.skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz' '.cursor/skills/deepgram-core-workflow-b'

Codex
test -f '.skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz/SKILL.md' && test -s '.skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz/SKILL.md' && mkdir -p '.agents/skills' && test ! -e '.agents/skills/deepgram-core-workflow-b' && cp -R '.skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz' '.agents/skills/deepgram-core-workflow-b'

OpenSkills

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Official OpenSkills installation
openskills install './.skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz'

openskills read 'real-time-streaming-transcription-with-deepgram-mmlj2oyz'

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For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.

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4. Try a first task

Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:

Read .skill-downloads/real-time-streaming-transcription-with-deepgram-mmlj2oyz/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

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