• Gladia samples Github repository for different coding languages

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Overview

The Gladia Audio Transcription WebSocket API allows developers to connect to a streaming audio transcription endpoint and receive real-time transcription results. This documentation provides the necessary information and guidelines for establishing a WebSocket connection and sending audio data for transcription.

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WebSocket Endpoint

The WebSocket endpoint for Gladia Audio Transcription API is:

wss://api.gladia.io/audio/text/audio-transcription

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Establishing a WebSocket Connection

To connect to the Gladia Audio Transcription WebSocket API, follow the steps below:

1. Create a WebSocket connection to the Gladia Audio Transcription endpoint: wss://api.gladia.io/audio/text/audio-transcription.
2. After establishing the connection, send an initial configuration message as a JSON object. This message specifies the transcription options and settings.

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Initial Configuration Message

The initial configuration message should be sent as a JSON object and include the following options:

• x_gladia_key (mandatory, string): Your API key obtained from app.gladia.io.
• encoding (optional, string): Specifies the audio encoding format. Valid values are “WAV”, “WAV/PCM”, “WAV/ALAW”, “WAV/ULAW”, “AMB”, “MP3”, “FLAC”, “OGG/VORBIS”, “OPUS”, “SPHERE” and “AMR-NB”. Default value is “WAV.”
• bit_depth(optional, integer): Specifies the bit depth of the audio submitted for transcription. The bit depth represents the number of bits of information stored for each sample of audio. Available options are 8, 16, 24, 32, and 64. If not specified, the default value is 16.
• sample_rate (optional, integer): Specifies the sample rate of the audio in Hz. Valid values are 8000, 16000, 32000, 44100, and 48000. default value is 16000
• language_behaviour (optional, enum): - Defines how the transcription model detects the audio language. Default value is automatic single language.

• language (optional, string): e.g. “english” - Required when language_behaviour = manual. Defines the language to use for the transcription.
• transcription_hint (optional, string): Provides a custom vocabulary to the model to improve accuracy of transcribing context specific words, technical terms, names, etc. If empty, this argument is ignored.
  ⚠️ Warning ⚠️: Please be aware that the transcription_hint field has a character limit of 600. If you provide a transcription_hint longer than 600 characters, it will be automatically truncated to meet this limit.
• endpointing (optional, integer): Specifies the endpointing duration in milliseconds. i.e. the duration of silence which will cause the utterance to be considered finished and a result of type ‘final’ to be sent. For more info see Transcription Results below. Default value is 300 ms.
• model_type (optional, string): Specifics which transcription model to use. possible values are “accurate” and “fast”. Default value is “fast”.
  The fast model will return less accurate ‘partial’ frames during an utterance with 400-500ms latency, and a more accurate ‘final’ frame at the end of each utterance with 700-800 ms latency.
  The accurate model will only return final frames at the end of each utterance, with very high accuracy and a latency of 1000-1100ms.
• frames_format (optional, string): Specifies how formated the frames will be. Possible values are “base64” and “bytes”. Default value is “base64”.
• prosody (optional, boolean): If prosody is true, you will get a transcription that can contain prosodies i.e. (laugh) (giggles) (malefic laugh) (toss) (music)… Default value is false.
• audio_enhancer (optional, boolean): If true, audio will be pre-processed to improve accuracy but latency will increase. Default value is false.
• reinject_context [experimental] (optional, boolean or string): Enables or disables reinjecting the last 10 sentences to guide the transcription. Depending on the use case and context, turning this on may increase accuracy or degrade it. Default value is false.
  Note: Do not enable if code switching is required. If language_behaviour is set to automatic multiple languages, enabling reinject_context will override the behaviour to automatic single language
• word_timestamps (optional, boolean): It enables word timestamps. Default value isfalse.
• maximum_audio_duration (optional, int): When audio duration since last final is longer than maximum_audio_duration, a final will be triggered with stable utterances. Default value is30 seconds.

Here’s an example initial configuration message:

{
    "x_gladia_key": "your_gladia_key",
    "sample_rate": 16000,
    "encoding": "mp3"
}

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Sending Audio Data for Transcription

Once the WebSocket connection is established and the initial configuration message is sent, you can start sending audio data for transcription.

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Using base64 encoded frames

Send JSON objects as messages to the WebSocket with the following structure:

{
    "frames": "base64"
}

• frames (string): Contains the audio data in base64-encoded format.

To send audio data, convert your audio to base64-encoded bytes and include them in the frames field of the JSON object.

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Using raw frames (bytes)

In case you specified in the configuration message frames_format to be bytes, you need to forward the binary frames as it without any formatting nor wrapping.

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Transcription Results

The Gladia Audio Transcription API will send back transcription results as JSON objects in real-time.
There are 3 types of results, identified by the event parameter:

Each result object with "event": "transcript"contains the following information:

• type (string): Specifies the type of transcription result. It can have two values: “final” or “partial.” If the type is “final,” it means there are more than endpointing milliseconds of silence or maximum_audio_duration has been reached; otherwise, it is considered partial.
• transcription (string): Contains the full transcription text since the last ‘final’ result.
• language (string): Represents the detected language for the transcription.
• time_begin (number): Timestamp in seconds of the beginning of this transcription
• time_end (number): Timestamp in seconds of the end of this transcription
• duration (number): Total duration in seconds of the audio
• words (array): Contains the words within the transcription. Only present if you enabled word_timestamps.
• utterances (array): Contains the detected utterances
  • id (number): Unique identifier across partial and final message of this utterance
  • stable (boolean): If true, the utterance is “stable”, meaning its transcription won’t change and you can safely use it even if returned in a partial transcript
  • transcription (string): Contains the transcription of this utterance
  • language (string): Represents the detected language for this utterance.
  • time_begin (number): Timestamp in seconds of the beginning of this utterance
  • time_end (number): Timestamp in seconds of the end of this utterance
  • words (array): Contains the words within the utterance. Only present if you enabled word_timestamps.

With word timestamps enabled, the result can be the following:

{
    "event": "transcript",
    "type": "final",
    "transcription": "Dall'associazione",
    "language": "it",
    "time_begin": 0.08019,
    "time_end": 0.58137,
    "duration": 0.623,
    "utterances": [
      {
        "id": 0,
        "stable": true,
        "transcription": "Dall'associazione",
        "language": "it",
        "time_begin": 0.08019,
        "time_end": 0.58137,
        "words": [
          {
            "word": "Dall'associazione",
            "time_begin": 0.08019,
            "time_end": 0.58137,
            "confidence": 0.77
          }
        ]
      }
    ],
    "words": [
        {
            "word": "Dall'associazione",
            "time_begin": 0.08019,
            "time_end": 0.58137,
            "confidence": 0.77
        }
    ]
}

Please note that multiple result objects may be received during the transcription process, depending on the audio duration and WebSocket connection.

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End a live transcription session

When you have send your last audio chunk, instead of closing yourself the WebSocket connection, you should send the following JSON message:

{
    "event": "terminate"
}

If there is any pending audio chunk, you’ll receive a transcript event with a final transcription result. The WebSocket connection will then be closed with a code 1000.

If you close the WebSocket connection without sending this event, you may miss the last final transcription.

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Recovering from WebSocket disconnects

The WebSocket connection may disconnect for any number of reasons. It is important to implement a recovery mechanism on the client side to reopen the connection and continue the live transcription.
On the close event, you should reconnect to the WebSocket unless :

• code = 1000: you should only receive that code if you send the terminate event or you closed the connection yourself. In this case, you should not attempt a reconnection
• code >= 4400 and < 4500: we send code in this range when there is an issue with something you sent. In this case, you should look at the reason and fix the issue.

For any other code, you should reconnect to the WebSocket.

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Example Workflow

1. Establish a WebSocket connection to wss://api.gladia.io/audio/text/audio-transcription.
2. Send the initial configuration message as a JSON object to specify the transcription options.

{
    "x_gladia_key": "your_gladia_key",
    "sample_rate": 16000,
    "encoding": "mp3"
}

1. Start sending audio data for transcription by converting the audio to base64-encoded bytes and including them in the frames field of a JSON object.

{
    "frames": "base64"
}

1. Receive real-time transcription results in JSON format. Each result object will include the type, transcription, language, and words fields.

{
    "type": "partial",
    "transcription": "Hello world.",
    "language": "en",
}

1. Continue sending audio data and receiving transcription results until the audio stream is complete.
2. Send the finalize event once your session is complete

{
    "event": "terminate"
}

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Limitations

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Chunk Size Limitation

Our streaming service is designed to handle data in smaller, manageable chunks. While we aim to provide flexibility in the content you can stream, we have established a maximum chunk duration of 120 seconds for the following reasons:

• Optimal Streaming Performance: Smaller chunks allow for better real-time processing and distribution, reducing the risk of buffering or delays in playback.
• Resource Management: Longer chunks could potentially strain our server resources and impact the overall performance of the service for all users.
• Reliability: Shorter chunks improve the reliability of the streaming service by minimizing the likelihood of errors or data loss during transmission.

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Thirty Seconds Behavior

If endpointing fails to be activated and the audio that is being buffered is greater than 30s, we force the following behavior:

• force a final utterance is forced
• the buffer state is reinitialised

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Conclusion

Congratulations! You have successfully learned how to connect to the Gladia Audio Transcription WebSocket API and send audio data for real-time transcription. Make sure to handle WebSocket connection errors, manage audio streaming, and process the received transcription results according to your application’s needs.

For further assistance or inquiries, please refer to the Gladia documentation or contact our support team at support@gladia.io.

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WebSocket close codes

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Code samples

import asyncio
import websockets
import json
import base64

ERROR_KEY = 'error'
TYPE_KEY = 'type'
TRANSCRIPTION_KEY = 'transcription'
LANGUAGE_KEY = 'language'

# retrieve gladia key
gladiaKey = ''  # replace with your gladia key
if not gladiaKey:
    print('You must provide a gladia key. Go to app.gladia.io')
    exit(1)
else:
    print('using the gladia key : ' + gladiaKey)

# connect to api websocket
gladiaUrl = "wss://api.gladia.io/audio/text/audio-transcription"

async def send_audio(socket):

    # Configure stream with a configuration message
    configuration = {
        "x_gladia_key": gladiaKey,
        # "model_type":"accurate" <- Less faster but more accurate model_type, useful if you need precise addresses for example.
    }
    await socket.send(json.dumps(configuration))

    # Once the initial message is sent, send audio data
    file = '../../../data/anna-and-sasha-16000.wav'
    with open(file, 'rb') as f:
        fileSync = f.read()
    base64Frames = base64.b64encode(fileSync).decode('utf-8')
    partSize = 20000  # The size of each part
    numberOfParts = -(-len(base64Frames) // partSize)  # equivalent of math.ceil

    # Split the audio data into parts and send them sequentially
    for i in range(numberOfParts):
        start = i * partSize
        end = min((i + 1) * partSize, len(base64Frames))
        part = base64Frames[start:end]

        # Delay between sending parts (500 mseconds in this case)
        await asyncio.sleep(0.5)
        message = {
            'frames': part
        }
        await socket.send(json.dumps(message))

    await asyncio.sleep(2)
    print("final closing")


# get ready to receive transcriptions
async def receive_transcription(socket):
    while True:
        response = await socket.recv()
        utterance = json.loads(response)
        if utterance:
            if ERROR_KEY in utterance:
                print(f"{utterance[ERROR_KEY]}")
                break
            else:
                print(f"{utterance[TYPE_KEY]}: ({utterance[LANGUAGE_KEY]}) {utterance[TRANSCRIPTION_KEY]}")
        else:
            print('empty,waiting for next utterance...')


# run both tasks concurrently
async def main():
    async with websockets.connect(gladiaUrl) as socket:
        send_task = asyncio.create_task(send_audio(socket))
        receive_task = asyncio.create_task(receive_transcription(socket))
        await asyncio.gather(send_task, receive_task)

asyncio.run(main())

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Working with Typescript

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Streaming a file

import WebSocket from "ws";
import fs from "fs";
import { resolve } from "path";
import { exit } from "process";

const ERROR_KEY = "error";
const TYPE_KEY = "type";
const TRANSCRIPTION_KEY = "transcription";
const LANGUAGE_KEY = "language";

const sleep = (delay: number): Promise<void> =>
  new Promise((f) => setTimeout(f, delay));

// retrieve gladia key
const gladiaKey = process.argv[2];
if (!gladiaKey) {
  console.error("You must provide a gladia key. Go to app.gladia.io");
  exit(1);
} else {
  console.log("using the gladia key : " + gladiaKey);
}

// connect to api websocket
const gladiaUrl = "wss://api.gladia.io/audio/text/audio-transcription";
const socket = new WebSocket(gladiaUrl);

// get ready to receive transcriptions
socket.on("message", (event: any) => {
  if (event) {
    const utterance = JSON.parse(event.toString());
    if (Object.keys(utterance).length !== 0) {
      if (ERROR_KEY in utterance) {
        console.error(`${utterance[ERROR_KEY]}`);
        socket.close();
      } else {
        console.log(
          `${utterance[TYPE_KEY]}: (${utterance[LANGUAGE_KEY]}) ${utterance[TRANSCRIPTION_KEY]}`
        );
      }
    }
  } else {
    console.log("empty ...");
  }
});

socket.on("error", (error: WebSocket.ErrorEvent) => {
  console.log(error.message);
});

socket.on("open", async () => {
  // Configure stream with a configuration message
  const configuration = {
    x_gladia_key: gladiaKey,
    // "model_type":"accurate"
  };
  socket.send(JSON.stringify(configuration));

  // Once the initial message is sent, send audio data
  const file = resolve("../data/anna-and-sasha-16000.wav");
  const fileSync = fs.readFileSync(file);
  const newBuffers = Buffer.from(fileSync)
  const segment = newBuffers.slice(44, newBuffers.byteLength);
  const base64Frames = segment.toString("base64");
  const partSize = 20000; // The size of each part
  const numberOfParts = Math.ceil(base64Frames.length / partSize);

  // Split the audio data into parts and send them sequentially
  for (let i = 0; i < numberOfParts; i++) {
    const start = i * partSize;
    const end = Math.min((i + 1) * partSize, base64Frames.length);
    const part = base64Frames.substring(start, end);

    // Delay between sending parts (500 mseconds in this case)
    await sleep(500);
    const message = {
      frames: part,
    };
    // console.log(part)
    socket.send(JSON.stringify(message));
  }

  socket.send(JSON.stringify({event: 'terminate'}));
});

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Streaming a microphone

import { exit } from "process";
import WebSocket from "ws";
import mic from "mic";

const ERROR_KEY = "error";
const TYPE_KEY = "type";
const TRANSCRIPTION_KEY = "transcription";
const LANGUAGE_KEY = "language";
const SAMPLE_RATE = 16_000

// retrieve gladia key
const gladiaKey = process.argv[2];
if (!gladiaKey) {
  console.error("You must provide a gladia key. Go to app.gladia.io");
  exit(1);
} else {
  console.log("using the gladia key : " + gladiaKey);
}

// connect to api websocket
const gladiaUrl = "wss://api.gladia.io/audio/text/audio-transcription";
const socket = new WebSocket(gladiaUrl);

// get ready to receive transcriptions
socket.on("message", (event: any) => {
  if (event) {
    const utterance = JSON.parse(event.toString());
    if (Object.keys(utterance).length !== 0) {
      if (ERROR_KEY in utterance) {
        console.error(`${utterance[ERROR_KEY]}`);
        socket.close();
      } else {
        console.log(
          `${utterance[TYPE_KEY]}: (${utterance[LANGUAGE_KEY]}) ${utterance[TRANSCRIPTION_KEY]}`
        );
      }
    }
  } else {
    console.log("empty ...");
  }
});

socket.on("error", (error: WebSocket.ErrorEvent) => {
  console.log(error.message);
});

socket.on("open", async () => {
  // Configure stream with a configuration message
  const configuration = {
    x_gladia_key: gladiaKey,
    sample_rate: SAMPLE_RATE
    // "model_type":"accurate"
  };
  socket.send(JSON.stringify(configuration));

  // create micrphone instance
  const micophoneInstance = mic({
    rate: SAMPLE_RATE,
    channels: '1',
  });

  const microphoneInputStream = micophoneInstance.getAudioStream();
  microphoneInputStream.on('data', function (data: any) {
    const base64 = data.toString('base64')
    socket.send(JSON.stringify({ frames: base64 }));
  });

  microphoneInputStream.on('error', function (err: any) {
    console.log("Error in Input Stream: " + err);
  });

  micophoneInstance.start();
})