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Quickstart: Recognize and convert speech to text

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Reference documentation | Package (NuGet) | Additional Samples on GitHub

In this quickstart, you create and run an application to recognize and transcribe speech to text in real-time.

Tip

You can try real-time speech to text in Speech Studio without signing up or writing any code.

To instead transcribe audio files asynchronously, see Batch transcription. If you're not sure which speech to text solution is right for you, see the speech to text overview documentation.

Prerequisites

Set up the environment

The Speech SDK is available as a NuGet package and implements .NET Standard 2.0. You install the Speech SDK later in this guide, but first check the SDK installation guide for any more requirements.

Set environment variables

Your application must be authenticated to access Cognitive Services resources. For production, use a secure way of storing and accessing your credentials. For example, after you get a key for your Speech resource, write it to a new environment variable on the local machine running the application.

Tip

Don't include the key directly in your code, and never post it publicly. See the Cognitive Services security article for more authentication options like Azure Key Vault.

To set the environment variable for your Speech resource key, open a console window, and follow the instructions for your operating system and development environment.

  • To set the SPEECH_KEY environment variable, replace your-key with one of the keys for your resource.
  • To set the SPEECH_REGION environment variable, replace your-region with one of the regions for your resource.
setx SPEECH_KEY your-key
setx SPEECH_REGION your-region

Note

If you only need to access the environment variable in the current running console, you can set the environment variable with set instead of setx.

After you add the environment variables, you may need to restart any running programs that will need to read the environment variable, including the console window. For example, if you are using Visual Studio as your editor, restart Visual Studio before running the example.

Recognize speech from a microphone

Follow these steps to create a new console application and install the Speech SDK.

  1. Open a command prompt where you want the new project, and create a console application with the .NET CLI. The Program.cs file should be created in the project directory.

    dotnet new console

  2. Install the Speech SDK in your new project with the .NET CLI.

    dotnet add package Microsoft.CognitiveServices.Speech

  3. Replace the contents of Program.cs with the following code.

    using System;
using System.IO;
using System.Threading.Tasks;
using Microsoft.CognitiveServices.Speech;
using Microsoft.CognitiveServices.Speech.Audio;

class Program 
{
    // This example requires environment variables named "SPEECH_KEY" and "SPEECH_REGION"
    static string speechKey = Environment.GetEnvironmentVariable("SPEECH_KEY");
    static string speechRegion = Environment.GetEnvironmentVariable("SPEECH_REGION");

    static void OutputSpeechRecognitionResult(SpeechRecognitionResult speechRecognitionResult)
    {
        switch (speechRecognitionResult.Reason)
        {
            case ResultReason.RecognizedSpeech:
                Console.WriteLine($"RECOGNIZED: Text={speechRecognitionResult.Text}");
                break;
            case ResultReason.NoMatch:
                Console.WriteLine($"NOMATCH: Speech could not be recognized.");
                break;
            case ResultReason.Canceled:
                var cancellation = CancellationDetails.FromResult(speechRecognitionResult);
                Console.WriteLine($"CANCELED: Reason={cancellation.Reason}");

                if (cancellation.Reason == CancellationReason.Error)
                {
                    Console.WriteLine($"CANCELED: ErrorCode={cancellation.ErrorCode}");
                    Console.WriteLine($"CANCELED: ErrorDetails={cancellation.ErrorDetails}");
                    Console.WriteLine($"CANCELED: Did you set the speech resource key and region values?");
                }
                break;
        }
    }

    async static Task Main(string[] args)
    {
        var speechConfig = SpeechConfig.FromSubscription(speechKey, speechRegion);        
        speechConfig.SpeechRecognitionLanguage = "en-US";

        using var audioConfig = AudioConfig.FromDefaultMicrophoneInput();
        using var speechRecognizer = new SpeechRecognizer(speechConfig, audioConfig);

        Console.WriteLine("Speak into your microphone.");
        var speechRecognitionResult = await speechRecognizer.RecognizeOnceAsync();
        OutputSpeechRecognitionResult(speechRecognitionResult);
    }
}

  4. To change the speech recognition language, replace en-US with another supported language. For example, es-ES for Spanish (Spain). The default language is en-US if you don't specify a language. For details about how to identify one of multiple languages that might be spoken, see language identification.

Run your new console application to start speech recognition from a microphone:

dotnet run

Important

Make sure that you set the SPEECH__KEY and SPEECH__REGION environment variables as described above. If you don't set these variables, the sample will fail with an error message.

Speak into your microphone when prompted. What you speak should be output as text:

Speak into your microphone.
RECOGNIZED: Text=I'm excited to try speech to text.

Remarks

Now that you've completed the quickstart, here are some additional considerations:

  • This example uses the RecognizeOnceAsync operation to transcribe utterances of up to 30 seconds, or until silence is detected. For information about continuous recognition for longer audio, including multi-lingual conversations, see How to recognize speech.
  • To recognize speech from an audio file, use FromWavFileInput instead of FromDefaultMicrophoneInput: 
    using var audioConfig = AudioConfig.FromWavFileInput("YourAudioFile.wav");
  • For compressed audio files such as MP4, install GStreamer and use PullAudioInputStream or PushAudioInputStream. For more information, see How to use compressed input audio.

Clean up resources

You can use the Azure portal or Azure Command Line Interface (CLI) to remove the Speech resource you created.

Reference documentation | Package (NuGet) | Additional Samples on GitHub

In this quickstart, you create and run an application to recognize and transcribe speech to text in real-time.

Tip

You can try real-time speech to text in Speech Studio without signing up or writing any code.

To instead transcribe audio files asynchronously, see Batch transcription. If you're not sure which speech to text solution is right for you, see the speech to text overview documentation.

Prerequisites

Set up the environment

The Speech SDK is available as a NuGet package and implements .NET Standard 2.0. You install the Speech SDK later in this guide, but first check the SDK installation guide for any more requirements.

Set environment variables

Your application must be authenticated to access Cognitive Services resources. For production, use a secure way of storing and accessing your credentials. For example, after you get a key for your Speech resource, write it to a new environment variable on the local machine running the application.

Tip

Don't include the key directly in your code, and never post it publicly. See the Cognitive Services security article for more authentication options like Azure Key Vault.

To set the environment variable for your Speech resource key, open a console window, and follow the instructions for your operating system and development environment.

  • To set the SPEECH_KEY environment variable, replace your-key with one of the keys for your resource.
  • To set the SPEECH_REGION environment variable, replace your-region with one of the regions for your resource.
setx SPEECH_KEY your-key
setx SPEECH_REGION your-region

Note

If you only need to access the environment variable in the current running console, you can set the environment variable with set instead of setx.

After you add the environment variables, you may need to restart any running programs that will need to read the environment variable, including the console window. For example, if you are using Visual Studio as your editor, restart Visual Studio before running the example.

Recognize speech from a microphone

Follow these steps to create a new console application and install the Speech SDK.

  1. Create a new C++ console project in Visual Studio Community 2022 named SpeechRecognition.

  2. Install the Speech SDK in your new project with the NuGet package manager.

    Install-Package Microsoft.CognitiveServices.Speech

  3. Replace the contents of SpeechRecognition.cpp with the following code:

    #include <iostream> 
#include <stdlib.h>
#include <speechapi_cxx.h>

using namespace Microsoft::CognitiveServices::Speech;
using namespace Microsoft::CognitiveServices::Speech::Audio;

std::string GetEnvironmentVariable(const char* name);

int main()
{
    // This example requires environment variables named "SPEECH_KEY" and "SPEECH_REGION"
    auto speechKey = GetEnvironmentVariable("SPEECH_KEY");
    auto speechRegion = GetEnvironmentVariable("SPEECH_REGION");

    if ((size(speechKey) == 0) || (size(speechRegion) == 0)) {
        std::cout << "Please set both SPEECH_KEY and SPEECH_REGION environment variables." << std::endl;
        return -1;
    }

    auto speechConfig = SpeechConfig::FromSubscription(speechKey, speechRegion);

    speechConfig->SetSpeechRecognitionLanguage("en-US");

    auto audioConfig = AudioConfig::FromDefaultMicrophoneInput();
    auto recognizer = SpeechRecognizer::FromConfig(speechConfig, audioConfig);

    std::cout << "Speak into your microphone.\n";
    auto result = recognizer->RecognizeOnceAsync().get();

    if (result->Reason == ResultReason::RecognizedSpeech)
    {
        std::cout << "RECOGNIZED: Text=" << result->Text << std::endl;
    }
    else if (result->Reason == ResultReason::NoMatch)
    {
        std::cout << "NOMATCH: Speech could not be recognized." << std::endl;
    }
    else if (result->Reason == ResultReason::Canceled)
    {
        auto cancellation = CancellationDetails::FromResult(result);
        std::cout << "CANCELED: Reason=" << (int)cancellation->Reason << std::endl;

        if (cancellation->Reason == CancellationReason::Error)
        {
            std::cout << "CANCELED: ErrorCode=" << (int)cancellation->ErrorCode << std::endl;
            std::cout << "CANCELED: ErrorDetails=" << cancellation->ErrorDetails << std::endl;
            std::cout << "CANCELED: Did you set the speech resource key and region values?" << std::endl;
        }
    }
}

std::string GetEnvironmentVariable(const char* name)
{
#if defined(_MSC_VER)
    size_t requiredSize = 0;
    (void)getenv_s(&requiredSize, nullptr, 0, name);
    if (requiredSize == 0)
    {
        return "";
    }
    auto buffer = std::make_unique<char[]>(requiredSize);
    (void)getenv_s(&requiredSize, buffer.get(), requiredSize, name);
    return buffer.get();
#else
    auto value = getenv(name);
    return value ? value : "";
#endif
}

  4. To change the speech recognition language, replace en-US with another supported language. For example, es-ES for Spanish (Spain). The default language is en-US if you don't specify a language. For details about how to identify one of multiple languages that might be spoken, see language identification.

Build and run your new console application to start speech recognition from a microphone.

Important

Make sure that you set the SPEECH__KEY and SPEECH__REGION environment variables as described above. If you don't set these variables, the sample will fail with an error message.

Speak into your microphone when prompted. What you speak should be output as text:

Speak into your microphone.
RECOGNIZED: Text=I'm excited to try speech to text.

Remarks

Now that you've completed the quickstart, here are some additional considerations:

  • This example uses the RecognizeOnceAsync operation to transcribe utterances of up to 30 seconds, or until silence is detected. For information about continuous recognition for longer audio, including multi-lingual conversations, see How to recognize speech.
  • To recognize speech from an audio file, use FromWavFileInput instead of FromDefaultMicrophoneInput: 
    auto audioInput = AudioConfig::FromWavFileInput("YourAudioFile.wav");
  • For compressed audio files such as MP4, install GStreamer and use PullAudioInputStream or PushAudioInputStream. For more information, see How to use compressed input audio.

Clean up resources

You can use the Azure portal or Azure Command Line Interface (CLI) to remove the Speech resource you created.

Reference documentation | Package (Go) | Additional Samples on GitHub

In this quickstart, you create and run an application to recognize and transcribe speech to text in real-time.

Tip

You can try real-time speech to text in Speech Studio without signing up or writing any code.

To instead transcribe audio files asynchronously, see Batch transcription. If you're not sure which speech to text solution is right for you, see the speech to text overview documentation.

Prerequisites

Set up the environment

Install the Speech SDK for Go. Check the SDK installation guide for any more requirements.

Set environment variables

Your application must be authenticated to access Cognitive Services resources. For production, use a secure way of storing and accessing your credentials. For example, after you get a key for your Speech resource, write it to a new environment variable on the local machine running the application.

Tip

Don't include the key directly in your code, and never post it publicly. See the Cognitive Services security article for more authentication options like Azure Key Vault.

To set the environment variable for your Speech resource key, open a console window, and follow the instructions for your operating system and development environment.

  • To set the SPEECH_KEY environment variable, replace your-key with one of the keys for your resource.
  • To set the SPEECH_REGION environment variable, replace your-region with one of the regions for your resource.
setx SPEECH_KEY your-key
setx SPEECH_REGION your-region

Note

If you only need to access the environment variable in the current running console, you can set the environment variable with set instead of setx.

After you add the environment variables, you may need to restart any running programs that will need to read the environment variable, including the console window. For example, if you are using Visual Studio as your editor, restart Visual Studio before running the example.

Recognize speech from a microphone

Follow these steps to create a new GO module.

  1. Open a command prompt where you want the new module, and create a new file named speech-recognition.go.

  2. Copy the following code into speech-recognition.go:

    package main

import (
	"bufio"
	"fmt"
	"os"

	"github.com/Microsoft/cognitive-services-speech-sdk-go/audio"
	"github.com/Microsoft/cognitive-services-speech-sdk-go/speech"
)

func sessionStartedHandler(event speech.SessionEventArgs) {
	defer event.Close()
	fmt.Println("Session Started (ID=", event.SessionID, ")")
}

func sessionStoppedHandler(event speech.SessionEventArgs) {
	defer event.Close()
	fmt.Println("Session Stopped (ID=", event.SessionID, ")")
}

func recognizingHandler(event speech.SpeechRecognitionEventArgs) {
	defer event.Close()
	fmt.Println("Recognizing:", event.Result.Text)
}

func recognizedHandler(event speech.SpeechRecognitionEventArgs) {
	defer event.Close()
	fmt.Println("Recognized:", event.Result.Text)
}

func cancelledHandler(event speech.SpeechRecognitionCanceledEventArgs) {
	defer event.Close()
	fmt.Println("Received a cancellation: ", event.ErrorDetails)
    fmt.Println("Did you set the speech resource key and region values?")
}

func main() {
    // This example requires environment variables named "SPEECH_KEY" and "SPEECH_REGION"
    speechKey :=  os.Getenv("SPEECH_KEY")
    speechRegion := os.Getenv("SPEECH_REGION")

	audioConfig, err := audio.NewAudioConfigFromDefaultMicrophoneInput()
	if err != nil {
		fmt.Println("Got an error: ", err)
		return
	}
	defer audioConfig.Close()
	speechConfig, err := speech.NewSpeechConfigFromSubscription(speechKey, speechRegion)
	if err != nil {
		fmt.Println("Got an error: ", err)
		return
	}
	defer speechConfig.Close()
	speechRecognizer, err := speech.NewSpeechRecognizerFromConfig(speechConfig, audioConfig)
	if err != nil {
		fmt.Println("Got an error: ", err)
		return
	}
	defer speechRecognizer.Close()
	speechRecognizer.SessionStarted(sessionStartedHandler)
	speechRecognizer.SessionStopped(sessionStoppedHandler)
	speechRecognizer.Recognizing(recognizingHandler)
	speechRecognizer.Recognized(recognizedHandler)
	speechRecognizer.Canceled(cancelledHandler)
	speechRecognizer.StartContinuousRecognitionAsync()
	defer speechRecognizer.StopContinuousRecognitionAsync()
	bufio.NewReader(os.Stdin).ReadBytes('\n')
}

Run the following commands to create a go.mod file that links to components hosted on GitHub:

go mod init speech-recognition
go get github.com/Microsoft/cognitive-services-speech-sdk-go

Important

Make sure that you set the SPEECH__KEY and SPEECH__REGION environment variables as described above. If you don't set these variables, the sample will fail with an error message.

Now build and run the code:

go build
go run speech-recognition

Clean up resources

You can use the Azure portal or Azure Command Line Interface (CLI) to remove the Speech resource you created.

Reference documentation | Additional Samples on GitHub

In this quickstart, you create and run an application to recognize and transcribe speech to text in real-time.

Tip

You can try real-time speech to text in Speech Studio without signing up or writing any code.

To instead transcribe audio files asynchronously, see Batch transcription. If you're not sure which speech to text solution is right for you, see the speech to text overview documentation.

Prerequisites

Set up the environment

Before you can do anything, you need to install the Speech SDK. The sample in this quickstart works with the Java Runtime.

  1. Install Apache Maven. Then run mvn -v to confirm successful installation.
  2. Create a new pom.xml file in the root of your project, and copy the following into it: 
    <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>
    <groupId>com.microsoft.cognitiveservices.speech.samples</groupId>
    <artifactId>quickstart-eclipse</artifactId>
    <version>1.0.0-SNAPSHOT</version>
    <build>
        <sourceDirectory>src</sourceDirectory>
        <plugins>
        <plugin>
            <artifactId>maven-compiler-plugin</artifactId>
            <version>3.7.0</version>
            <configuration>
            <source>1.8</source>
            <target>1.8</target>
            </configuration>
        </plugin>
        </plugins>
    </build>
    <dependencies>
        <dependency>
        <groupId>com.microsoft.cognitiveservices.speech</groupId>
        <artifactId>client-sdk</artifactId>
        <version>1.28.0</version>
        </dependency>
    </dependencies>
</project>
  3. Install the Speech SDK and dependencies. 
    mvn clean dependency:copy-dependencies

Set environment variables

Your application must be authenticated to access Cognitive Services resources. For production, use a secure way of storing and accessing your credentials. For example, after you get a key for your Speech resource, write it to a new environment variable on the local machine running the application.

Tip

Don't include the key directly in your code, and never post it publicly. See the Cognitive Services security article for more authentication options like Azure Key Vault.

To set the environment variable for your Speech resource key, open a console window, and follow the instructions for your operating system and development environment.

  • To set the SPEECH_KEY environment variable, replace your-key with one of the keys for your resource.
  • To set the SPEECH_REGION environment variable, replace your-region with one of the regions for your resource.
setx SPEECH_KEY your-key
setx SPEECH_REGION your-region

Note

If you only need to access the environment variable in the current running console, you can set the environment variable with set instead of setx.

After you add the environment variables, you may need to restart any running programs that will need to read the environment variable, including the console window. For example, if you are using Visual Studio as your editor, restart Visual Studio before running the example.

Recognize speech from a microphone

Follow these steps to create a new console application for speech recognition.

  1. Create a new file named SpeechRecognition.java in the same project root directory.

  2. Copy the following code into SpeechRecognition.java:

    import com.microsoft.cognitiveservices.speech.*;
import com.microsoft.cognitiveservices.speech.audio.AudioConfig;

import java.util.concurrent.ExecutionException;
import java.util.concurrent.Future;

public class SpeechRecognition {
    // This example requires environment variables named "SPEECH_KEY" and "SPEECH_REGION"
    private static String speechKey = System.getenv("SPEECH_KEY");
    private static String speechRegion = System.getenv("SPEECH_REGION");

    public static void main(String[] args) throws InterruptedException, ExecutionException {
        SpeechConfig speechConfig = SpeechConfig.fromSubscription(speechKey, speechRegion);
        speechConfig.setSpeechRecognitionLanguage("en-US");
        recognizeFromMicrophone(speechConfig);
    }

    public static void recognizeFromMicrophone(SpeechConfig speechConfig) throws InterruptedException, ExecutionException {
        AudioConfig audioConfig = AudioConfig.fromDefaultMicrophoneInput();
        SpeechRecognizer speechRecognizer = new SpeechRecognizer(speechConfig, audioConfig);

        System.out.println("Speak into your microphone.");
        Future<SpeechRecognitionResult> task = speechRecognizer.recognizeOnceAsync();
        SpeechRecognitionResult speechRecognitionResult = task.get();

        if (speechRecognitionResult.getReason() == ResultReason.RecognizedSpeech) {
            System.out.println("RECOGNIZED: Text=" + speechRecognitionResult.getText());
        }
        else if (speechRecognitionResult.getReason() == ResultReason.NoMatch) {
            System.out.println("NOMATCH: Speech could not be recognized.");
        }
        else if (speechRecognitionResult.getReason() == ResultReason.Canceled) {
            CancellationDetails cancellation = CancellationDetails.fromResult(speechRecognitionResult);
            System.out.println("CANCELED: Reason=" + cancellation.getReason());

            if (cancellation.getReason() == CancellationReason.Error) {
                System.out.println("CANCELED: ErrorCode=" + cancellation.getErrorCode());
                System.out.println("CANCELED: ErrorDetails=" + cancellation.getErrorDetails());
                System.out.println("CANCELED: Did you set the speech resource key and region values?");
            }
        }

        System.exit(0);
    }
}

  3. To change the speech recognition language, replace en-US with another supported language. For example, es-ES for Spanish (Spain). The default language is en-US if you don't specify a language. For details about how to identify one of multiple languages that might be spoken, see language identification.

Run your new console application to start speech recognition from a microphone:

javac SpeechRecognition.java -cp ".;target\dependency\*"
java -cp ".;target\dependency\*" SpeechRecognition

Important

Make sure that you set the SPEECH__KEY and SPEECH__REGION environment variables as described above. If you don't set these variables, the sample will fail with an error message.

Speak into your microphone when prompted. What you speak should be output as text:

Speak into your microphone.
RECOGNIZED: Text=I'm excited to try speech to text.

Remarks

Now that you've completed the quickstart, here are some additional considerations:

  • This example uses the RecognizeOnceAsync operation to transcribe utterances of up to 30 seconds, or until silence is detected. For information about continuous recognition for longer audio, including multi-lingual conversations, see How to recognize speech.
  • To recognize speech from an audio file, use fromWavFileInput instead of fromDefaultMicrophoneInput: 
    AudioConfig audioConfig = AudioConfig.fromWavFileInput("YourAudioFile.wav");
  • For compressed audio files such as MP4, install GStreamer and use PullAudioInputStream or PushAudioInputStream. For more information, see How to use compressed input audio.

Clean up resources

You can use the Azure portal or Azure Command Line Interface (CLI) to remove the Speech resource you created.

Reference documentation | Package (npm) | Additional Samples on GitHub | Library source code

In this quickstart, you create and run an application to recognize and transcribe speech to text in real-time.

Tip

You can try real-time speech to text in Speech Studio without signing up or writing any code.

To instead transcribe audio files asynchronously, see Batch transcription. If you're not sure which speech to text solution is right for you, see the speech to text overview documentation.

Prerequisites

You will also need a .wav audio file on your local machine. You can use your own .wav file (up to 30 seconds) or download the https://crbn.us/whatstheweatherlike.wav sample file.

Set up the environment

Before you can do anything, you need to install the Speech SDK for JavaScript. If you just want the package name to install, run npm install microsoft-cognitiveservices-speech-sdk. For guided installation instructions, see the SDK installation guide.

Set environment variables

Your application must be authenticated to access Cognitive Services resources. For production, use a secure way of storing and accessing your credentials. For example, after you get a key for your Speech resource, write it to a new environment variable on the local machine running the application.

Tip

Don't include the key directly in your code, and never post it publicly. See the Cognitive Services security article for more authentication options like Azure Key Vault.

To set the environment variable for your Speech resource key, open a console window, and follow the instructions for your operating system and development environment.

  • To set the SPEECH_KEY environment variable, replace your-key with one of the keys for your resource.
  • To set the SPEECH_REGION environment variable, replace your-region with one of the regions for your resource.
setx SPEECH_KEY your-key
setx SPEECH_REGION your-region

Note

If you only need to access the environment variable in the current running console, you can set the environment variable with set instead of setx.

After you add the environment variables, you may need to restart any running programs that will need to read the environment variable, including the console window. For example, if you are using Visual Studio as your editor, restart Visual Studio before running the example.

Recognize speech from a file

Follow these steps to create a Node.js console application for speech recognition.

  1. Open a command prompt where you want the new project, and create a new file named SpeechRecognition.js.

  2. Install the Speech SDK for JavaScript:

    npm install microsoft-cognitiveservices-speech-sdk

  3. Copy the following code into SpeechRecognition.js:

    const fs = require("fs");
const sdk = require("microsoft-cognitiveservices-speech-sdk");

// This example requires environment variables named "SPEECH_KEY" and "SPEECH_REGION"
const speechConfig = sdk.SpeechConfig.fromSubscription(process.env.SPEECH_KEY, process.env.SPEECH_REGION);
speechConfig.speechRecognitionLanguage = "en-US";

function fromFile() {
    let audioConfig = sdk.AudioConfig.fromWavFileInput(fs.readFileSync("YourAudioFile.wav"));
    let speechRecognizer = new sdk.SpeechRecognizer(speechConfig, audioConfig);

    speechRecognizer.recognizeOnceAsync(result => {
        switch (result.reason) {
            case sdk.ResultReason.RecognizedSpeech:
                console.log(`RECOGNIZED: Text=${result.text}`);
                break;
            case sdk.ResultReason.NoMatch:
                console.log("NOMATCH: Speech could not be recognized.");
                break;
            case sdk.ResultReason.Canceled:
                const cancellation = sdk.CancellationDetails.fromResult(result);
                console.log(`CANCELED: Reason=${cancellation.reason}`);

                if (cancellation.reason == sdk.CancellationReason.Error) {
                    console.log(`CANCELED: ErrorCode=${cancellation.ErrorCode}`);
                    console.log(`CANCELED: ErrorDetails=${cancellation.errorDetails}`);
                    console.log("CANCELED: Did you set the speech resource key and region values?");
                }
                break;
        }
        speechRecognizer.close();
    });
}
fromFile();

  4. In SpeechRecognition.js, replace YourAudioFile.wav with your own WAV file. This example only recognizes speech from a WAV file. For information about other audio formats, see How to use compressed input audio. This example supports up to 30 seconds audio.

  5. To change the speech recognition language, replace en-US with another supported language. For example, es-ES for Spanish (Spain). The default language is en-US if you don't specify a language. For details about how to identify one of multiple languages that might be spoken, see language identification.

Run your new console application to start speech recognition from a file:

node.exe SpeechRecognition.js

Important

Make sure that you set the SPEECH__KEY and SPEECH__REGION environment variables as described above. If you don't set these variables, the sample will fail with an error message.

The speech from the audio file should be output as text:

RECOGNIZED: Text=I'm excited to try speech to text.

Remarks

Now that you've completed the quickstart, here are some additional considerations:

This example uses the recognizeOnceAsync operation to transcribe utterances of up to 30 seconds, or until silence is detected. For information about continuous recognition for longer audio, including multi-lingual conversations, see How to recognize speech.

Note

Recognizing speech from a microphone is not supported in Node.js. It's supported only in a browser-based JavaScript environment. For more information, see the React sample and the implementation of speech to text from a microphone on GitHub. The React sample shows design patterns for the exchange and management of authentication tokens. It also shows the capture of audio from a microphone or file for speech to text conversions.

Clean up resources

You can use the Azure portal or Azure Command Line Interface (CLI) to remove the Speech resource you created.

Reference documentation | Package (Download) | Additional Samples on GitHub

In this quickstart, you create and run an application to recognize and transcribe speech to text in real-time.

Tip

You can try real-time speech to text in Speech Studio without signing up or writing any code.

To instead transcribe audio files asynchronously, see Batch transcription. If you're not sure which speech to text solution is right for you, see the speech to text overview documentation.

Prerequisites

Set up the environment

The Speech SDK for Objective-C is distributed as a framework bundle. The framework supports both Objective-C and Swift on both iOS and macOS.

The Speech SDK can be used in Xcode projects as a CocoaPod, or downloaded directly here and linked manually. This guide uses a CocoaPod. Install the CocoaPod dependency manager as described in its installation instructions.

Set environment variables

Your application must be authenticated to access Cognitive Services resources. For production, use a secure way of storing and accessing your credentials. For example, after you get a key for your Speech resource, write it to a new environment variable on the local machine running the application.

Tip

Don't include the key directly in your code, and never post it publicly. See the Cognitive Services security article for more authentication options like Azure Key Vault.

To set the environment variable for your Speech resource key, open a console window, and follow the instructions for your operating system and development environment.

  • To set the SPEECH_KEY environment variable, replace your-key with one of the keys for your resource.
  • To set the SPEECH_REGION environment variable, replace your-region with one of the regions for your resource.
setx SPEECH_KEY your-key
setx SPEECH_REGION your-region

Note

If you only need to access the environment variable in the current running console, you can set the environment variable with set instead of setx.

After you add the environment variables, you may need to restart any running programs that will need to read the environment variable, including the console window. For example, if you are using Visual Studio as your editor, restart Visual Studio before running the example.

Recognize speech from a microphone

Follow these steps to recognize speech in a macOS application.

  1. Clone the Azure-Samples/cognitive-services-speech-sdk repository to get the Recognize speech from a microphone in Objective-C on macOS sample project. The repository also has iOS samples.

  2. Navigate to the directory of the downloaded sample app (helloworld) in a terminal.

  3. Run the command pod install. This will generate a helloworld.xcworkspace Xcode workspace containing both the sample app and the Speech SDK as a dependency.

  4. Open the helloworld.xcworkspace workspace in Xcode.

  5. Open the file named AppDelegate.m and locate the buttonPressed method as shown here.

    - (void)buttonPressed:(NSButton *)button {
    // Creates an instance of a speech config with specified subscription key and service region.
    NSString *speechKey = [[[NSProcessInfo processInfo] environment] objectForKey:@"SPEECH_KEY"];
    NSString *serviceRegion = [[[NSProcessInfo processInfo] environment] objectForKey:@"SPEECH_REGION"];

    SPXAudioConfiguration *audioConfig = [[SPXAudioConfiguration alloc] initWithMicrophone:nil];
    SPXSpeechConfiguration *speechConfig = [[SPXSpeechConfiguration alloc] initWithSubscription:speechKey region:serviceRegion];
    SPXSpeechRecognizer *speechRecognizer = [[SPXSpeechRecognizer alloc] initWithSpeechConfiguration:speechConfig language:@"en-US" audioConfiguration:audioConfig];

    NSLog(@"Speak into your microphone.");

    SPXSpeechRecognitionResult *speechResult = [speechRecognizer recognizeOnce];

    // Checks result.
    if (SPXResultReason_Canceled == speechResult.reason) {
        SPXCancellationDetails *details = [[SPXCancellationDetails alloc] initFromCanceledRecognitionResult:speechResult];
        NSLog(@"Speech recognition was canceled: %@. Did you set the speech resource key and region values?", details.errorDetails);
        [self.label setStringValue:([NSString stringWithFormat:@"Canceled: %@", details.errorDetails])];
    } else if (SPXResultReason_RecognizedSpeech == speechResult.reason) {
        NSLog(@"Speech recognition result received: %@", speechResult.text);
        [self.label setStringValue:(speechResult.text)];
    } else {
        NSLog(@"There was an error.");
        [self.label setStringValue:(@"Speech Recognition Error")];
    }
}

  6. In AppDelegate.m, use the environment variables that you previously set for your Speech resource key and region.

    NSString *speechKey = [[[NSProcessInfo processInfo] environment] objectForKey:@"SPEECH_KEY"];
NSString *serviceRegion = [[[NSProcessInfo processInfo] environment] objectForKey:@"SPEECH_REGION"];

  7. To change the speech recognition language, replace en-US with another supported language. For example, es-ES for Spanish (Spain). The default language is en-US if you don't specify a language. For details about how to identify one of multiple languages that might be spoken, see language identification.

  8. Make the debug output visible (View > Debug Area > Activate Console).

  9. Build and run the example code by selecting Product > Run from the menu or selecting the Play button.

Important

Make sure that you set the SPEECH__KEY and SPEECH__REGION environment variables as described above. If you don't set these variables, the sample will fail with an error message.

After you select the button in the app and say a few words, you should see the text you have spoken on the lower part of the screen. When you run the app for the first time, you should be prompted to give the app access to your computer's microphone.

Remarks

Now that you've completed the quickstart, here are some additional considerations:

  • This example uses the recognizeOnce operation to transcribe utterances of up to 30 seconds, or until silence is detected. For information about continuous recognition for longer audio, including multi-lingual conversations, see How to recognize speech.
  • To recognize speech from an audio file, use initWithWavFileInput instead of initWithMicrophone: 
    SPXAudioConfiguration *audioConfig = [[SPXAudioConfiguration alloc] initWithWavFileInput:YourAudioFile];

Clean up resources

You can use the Azure portal or Azure Command Line Interface (CLI) to remove the Speech resource you created.

Reference documentation | Package (Download) | Additional Samples on GitHub

In this quickstart, you create and run an application to recognize and transcribe speech to text in real-time.

Tip

You can try real-time speech to text in Speech Studio without signing up or writing any code.

To instead transcribe audio files asynchronously, see Batch transcription. If you're not sure which speech to text solution is right for you, see the speech to text overview documentation.

Prerequisites

Set up the environment

The Speech SDK for Swift is distributed as a framework bundle. The framework supports both Objective-C and Swift on both iOS and macOS.

The Speech SDK can be used in Xcode projects as a CocoaPod, or downloaded directly here and linked manually. This guide uses a CocoaPod. Install the CocoaPod dependency manager as described in its installation instructions.

Set environment variables

Your application must be authenticated to access Cognitive Services resources. For production, use a secure way of storing and accessing your credentials. For example, after you get a key for your Speech resource, write it to a new environment variable on the local machine running the application.

Tip

Don't include the key directly in your code, and never post it publicly. See the Cognitive Services security article for more authentication options like Azure Key Vault.

To set the environment variable for your Speech resource key, open a console window, and follow the instructions for your operating system and development environment.

  • To set the SPEECH_KEY environment variable, replace your-key with one of the keys for your resource.
  • To set the SPEECH_REGION environment variable, replace your-region with one of the regions for your resource.
setx SPEECH_KEY your-key
setx SPEECH_REGION your-region

Note

If you only need to access the environment variable in the current running console, you can set the environment variable with set instead of setx.

After you add the environment variables, you may need to restart any running programs that will need to read the environment variable, including the console window. For example, if you are using Visual Studio as your editor, restart Visual Studio before running the example.

Recognize speech from a microphone

Follow these steps to recognize speech in a macOS application.

  1. Clone the Azure-Samples/cognitive-services-speech-sdk repository to get the Recognize speech from a microphone in Swift on macOS sample project. The repository also has iOS samples.

  2. Navigate to the directory of the downloaded sample app (helloworld) in a terminal.

  3. Run the command pod install. This will generate a helloworld.xcworkspace Xcode workspace containing both the sample app and the Speech SDK as a dependency.

  4. Open the helloworld.xcworkspace workspace in Xcode.

  5. Open the file named AppDelegate.swift and locate the applicationDidFinishLaunching and recognizeFromMic methods as shown here.

    import Cocoa

@NSApplicationMain
class AppDelegate: NSObject, NSApplicationDelegate {
    var label: NSTextField!
    var fromMicButton: NSButton!

    var sub: String!
    var region: String!

    @IBOutlet weak var window: NSWindow!

    func applicationDidFinishLaunching(_ aNotification: Notification) {
        print("loading")
        // load subscription information
        sub = ProcessInfo.processInfo.environment["SPEECH_KEY"]
        region = ProcessInfo.processInfo.environment["SPEECH_REGION"]

        label = NSTextField(frame: NSRect(x: 100, y: 50, width: 200, height: 200))
        label.textColor = NSColor.black
        label.lineBreakMode = .byWordWrapping

        label.stringValue = "Recognition Result"
        label.isEditable = false

        self.window.contentView?.addSubview(label)

        fromMicButton = NSButton(frame: NSRect(x: 100, y: 300, width: 200, height: 30))
        fromMicButton.title = "Recognize"
        fromMicButton.target = self
        fromMicButton.action = #selector(fromMicButtonClicked)
        self.window.contentView?.addSubview(fromMicButton)
    }

    @objc func fromMicButtonClicked() {
        DispatchQueue.global(qos: .userInitiated).async {
            self.recognizeFromMic()
        }
    }

    func recognizeFromMic() {
        var speechConfig: SPXSpeechConfiguration?
        do {
            try speechConfig = SPXSpeechConfiguration(subscription: sub, region: region)
        } catch {
            print("error \(error) happened")
            speechConfig = nil
        }
        speechConfig?.speechRecognitionLanguage = "en-US"

        let audioConfig = SPXAudioConfiguration()

        let reco = try! SPXSpeechRecognizer(speechConfiguration: speechConfig!, audioConfiguration: audioConfig)

        reco.addRecognizingEventHandler() {reco, evt in
            print("intermediate recognition result: \(evt.result.text ?? "(no result)")")
            self.updateLabel(text: evt.result.text, color: .gray)
        }

        updateLabel(text: "Listening ...", color: .gray)
        print("Listening...")

        let result = try! reco.recognizeOnce()
        print("recognition result: \(result.text ?? "(no result)"), reason: \(result.reason.rawValue)")
        updateLabel(text: result.text, color: .black)

        if result.reason != SPXResultReason.recognizedSpeech {
            let cancellationDetails = try! SPXCancellationDetails(fromCanceledRecognitionResult: result)
            print("cancelled: \(result.reason), \(cancellationDetails.errorDetails)")
            print("Did you set the speech resource key and region values?")
            updateLabel(text: "Error: \(cancellationDetails.errorDetails)", color: .red)
        }
    }

    func updateLabel(text: String?, color: NSColor) {
        DispatchQueue.main.async {
            self.label.stringValue = text!
            self.label.textColor = color
        }
    }
}

  6. In AppDelegate.m, use the environment variables that you previously set for your Speech resource key and region.

    sub = ProcessInfo.processInfo.environment["SPEECH_KEY"]
region = ProcessInfo.processInfo.environment["SPEECH_REGION"]

  7. To change the speech recognition language, replace en-US with another supported language. For example, es-ES for Spanish (Spain). The default language is en-US if you don't specify a language. For details about how to identify one of multiple languages that might be spoken, see language identification.

  8. Make the debug output visible by selecting View > Debug Area > Activate Console.

  9. Build and run the example code by selecting Product > Run from the menu or selecting the Play button.

Important

Make sure that you set the SPEECH__KEY and SPEECH__REGION environment variables as described above. If you don't set these variables, the sample will fail with an error message.

After you select the button in the app and say a few words, you should see the text you have spoken on the lower part of the screen. When you run the app for the first time, you should be prompted to give the app access to your computer's microphone.

Remarks

Now that you've completed the quickstart, here are some additional considerations:

This example uses the recognizeOnce operation to transcribe utterances of up to 30 seconds, or until silence is detected. For information about continuous recognition for longer audio, including multi-lingual conversations, see How to recognize speech.

Clean up resources

You can use the Azure portal or Azure Command Line Interface (CLI) to remove the Speech resource you created.

Reference documentation | Package (PyPi) | Additional Samples on GitHub

In this quickstart, you create and run an application to recognize and transcribe speech to text in real-time.

Tip

You can try real-time speech to text in Speech Studio without signing up or writing any code.

To instead transcribe audio files asynchronously, see Batch transcription. If you're not sure which speech to text solution is right for you, see the speech to text overview documentation.

Prerequisites

Set up the environment

The Speech SDK for Python is available as a Python Package Index (PyPI) module. The Speech SDK for Python is compatible with Windows, Linux, and macOS.

Install a version of Python from 3.7 or later. First check the SDK installation guide for any more requirements.

Set environment variables

Your application must be authenticated to access Cognitive Services resources. For production, use a secure way of storing and accessing your credentials. For example, after you get a key for your Speech resource, write it to a new environment variable on the local machine running the application.

Tip

Don't include the key directly in your code, and never post it publicly. See the Cognitive Services security article for more authentication options like Azure Key Vault.

To set the environment variable for your Speech resource key, open a console window, and follow the instructions for your operating system and development environment.

  • To set the SPEECH_KEY environment variable, replace your-key with one of the keys for your resource.
  • To set the SPEECH_REGION environment variable, replace your-region with one of the regions for your resource.
setx SPEECH_KEY your-key
setx SPEECH_REGION your-region

Note

If you only need to access the environment variable in the current running console, you can set the environment variable with set instead of setx.

After you add the environment variables, you may need to restart any running programs that will need to read the environment variable, including the console window. For example, if you are using Visual Studio as your editor, restart Visual Studio before running the example.

Recognize speech from a microphone

Follow these steps to create a new console application.

  1. Open a command prompt where you want the new project, and create a new file named speech_recognition.py.

  2. Run this command to install the Speech SDK:

    pip install azure-cognitiveservices-speech

  3. Copy the following code into speech_recognition.py:

    import os
import azure.cognitiveservices.speech as speechsdk

def recognize_from_microphone():
    # This example requires environment variables named "SPEECH_KEY" and "SPEECH_REGION"
    speech_config = speechsdk.SpeechConfig(subscription=os.environ.get('SPEECH_KEY'), region=os.environ.get('SPEECH_REGION'))
    speech_config.speech_recognition_language="en-US"

    audio_config = speechsdk.audio.AudioConfig(use_default_microphone=True)
    speech_recognizer = speechsdk.SpeechRecognizer(speech_config=speech_config, audio_config=audio_config)

    print("Speak into your microphone.")
    speech_recognition_result = speech_recognizer.recognize_once_async().get()

    if speech_recognition_result.reason == speechsdk.ResultReason.RecognizedSpeech:
        print("Recognized: {}".format(speech_recognition_result.text))
    elif speech_recognition_result.reason == speechsdk.ResultReason.NoMatch:
        print("No speech could be recognized: {}".format(speech_recognition_result.no_match_details))
    elif speech_recognition_result.reason == speechsdk.ResultReason.Canceled:
        cancellation_details = speech_recognition_result.cancellation_details
        print("Speech Recognition canceled: {}".format(cancellation_details.reason))
        if cancellation_details.reason == speechsdk.CancellationReason.Error:
            print("Error details: {}".format(cancellation_details.error_details))
            print("Did you set the speech resource key and region values?")

recognize_from_microphone()

  4. To change the speech recognition language, replace en-US with another supported language. For example, es-ES for Spanish (Spain). The default language is en-US if you don't specify a language. For details about how to identify one of multiple languages that might be spoken, see language identification.

Run your new console application to start speech recognition from a microphone:

python speech_recognition.py

Important

Make sure that you set the SPEECH__KEY and SPEECH__REGION environment variables as described above. If you don't set these variables, the sample will fail with an error message.

Speak into your microphone when prompted. What you speak should be output as text:

Speak into your microphone.
RECOGNIZED: Text=I'm excited to try speech to text.

Remarks

Now that you've completed the quickstart, here are some additional considerations:

  • This example uses the recognize_once_async operation to transcribe utterances of up to 30 seconds, or until silence is detected. For information about continuous recognition for longer audio, including multi-lingual conversations, see How to recognize speech.
  • To recognize speech from an audio file, use filename instead of use_default_microphone: 
    audio_config = speechsdk.audio.AudioConfig(filename="YourAudioFile.wav")
  • For compressed audio files such as MP4, install GStreamer and use PullAudioInputStream or PushAudioInputStream. For more information, see How to use compressed input audio.

Clean up resources

You can use the Azure portal or Azure Command Line Interface (CLI) to remove the Speech resource you created.

Speech to text REST API reference | Speech to text REST API for short audio reference | Additional Samples on GitHub

In this quickstart, you create and run an application to recognize and transcribe speech to text in real-time.

Tip

You can try real-time speech to text in Speech Studio without signing up or writing any code.

To instead transcribe audio files asynchronously, see Batch transcription. If you're not sure which speech to text solution is right for you, see the speech to text overview documentation.

Prerequisites

You will also need a .wav audio file on your local machine. You can use your own .wav file (up to 60 seconds) or download the https://crbn.us/whatstheweatherlike.wav sample file.

Set environment variables

Your application must be authenticated to access Cognitive Services resources. For production, use a secure way of storing and accessing your credentials. For example, after you get a key for your Speech resource, write it to a new environment variable on the local machine running the application.

Tip

Don't include the key directly in your code, and never post it publicly. See the Cognitive Services security article for more authentication options like Azure Key Vault.

To set the environment variable for your Speech resource key, open a console window, and follow the instructions for your operating system and development environment.

  • To set the SPEECH_KEY environment variable, replace your-key with one of the keys for your resource.
  • To set the SPEECH_REGION environment variable, replace your-region with one of the regions for your resource.
setx SPEECH_KEY your-key
setx SPEECH_REGION your-region

Note

If you only need to access the environment variable in the current running console, you can set the environment variable with set instead of setx.

After you add the environment variables, you may need to restart any running programs that will need to read the environment variable, including the console window. For example, if you are using Visual Studio as your editor, restart Visual Studio before running the example.

Recognize speech from a file

At a command prompt, run the following cURL command. Replace YourAudioFile.wav with the path and name of your audio file.

Choose your target environment

curl --location --request POST "https://%SPEECH_REGION%.stt.speech.microsoft.com/speech/recognition/conversation/cognitiveservices/v1?language=en-US&format=detailed" ^
--header "Ocp-Apim-Subscription-Key: %SPEECH_KEY%" ^
--header "Content-Type: audio/wav" ^
--data-binary "@YourAudioFile.wav"

Important

Make sure that you set the SPEECH__KEY and SPEECH__REGION environment variables as described above. If you don't set these variables, the sample will fail with an error message.

You should receive a response similar to what is shown here. The DisplayText should be the text that was recognized from your audio file. Up to 60 seconds of audio will be recognized and converted to text.

{
    "RecognitionStatus": "Success",
    "DisplayText": "My voice is my passport, verify me.",
    "Offset": 6600000,
    "Duration": 32100000
}

For more information, see Speech to text REST API for short audio.

Clean up resources

You can use the Azure portal or Azure Command Line Interface (CLI) to remove the Speech resource you created.

In this quickstart, you create and run an application to recognize and transcribe speech to text in real-time.

Tip

You can try real-time speech to text in Speech Studio without signing up or writing any code.

To instead transcribe audio files asynchronously, see Batch transcription. If you're not sure which speech to text solution is right for you, see the speech to text overview documentation.

Prerequisites

Set up the environment

Follow these steps and see the Speech CLI quickstart for additional requirements for your platform.

  1. Install the Speech CLI via the .NET CLI by entering this command:

    dotnet tool install --global Microsoft.CognitiveServices.Speech.CLI

  2. Configure your Speech resource key and region, by running the following commands. Replace SUBSCRIPTION-KEY with your Speech resource key, and replace REGION with your Speech resource region:

    spx config @key --set SUBSCRIPTION-KEY
spx config @region --set REGION

Recognize speech from a microphone

Run the following command to start speech recognition from a microphone:

spx recognize --microphone --source en-US

Speak into the microphone, and you see transcription of your words into text in real-time. The Speech CLI stops after a period of silence, 30 seconds, or when you press Ctrl+C.

Connection CONNECTED...
RECOGNIZED: I'm excited to try speech to text.

Remarks

Now that you've completed the quickstart, here are some additional considerations:

  • To recognize speech from an audio file, use --file instead of --microphone. For compressed audio files such as MP4, install GStreamer and use --format. For more information, see How to use compressed input audio.
    spx recognize --file YourAudioFile.wav
spx recognize --file YourAudioFile.mp4 --format any
  • To improve recognition accuracy of specific words or utterances, use a phrase list. You include a phrase list in-line or with a text file along with the recognize command:
    spx recognize --microphone --phrases "Contoso;Jessie;Rehaan;"
spx recognize --microphone --phrases @phrases.txt
  • To change the speech recognition language, replace en-US with another supported language. For example, es-ES for Spanish (Spain). The default language is en-US if you don't specify a language. 
    spx recognize --microphone --source es-ES
  • For continuous recognition of audio longer than 30 seconds, append --continuous: 
    spx recognize --microphone --source es-ES --continuous

Run this command for information about additional speech recognition options such as file input and output:

spx help recognize

Clean up resources

You can use the Azure portal or Azure Command Line Interface (CLI) to remove the Speech resource you created.

Next steps

Learn more about speech recognition