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    Transcribe phone audio with enhanced models

    This tutorial shows how to transcribe the audio recorded from a phone using Speech-to-Text.

    Audio files can come from many different sources. Audio data can come from a phone (like voicemail) or a soundtrack included in a video file.

    Speech-to-Text can use one of several machine learning models to transcribe your audio file, to best match the original source of the audio. You can get better results from your speech transcription by specifying the source of the original audio. This allows the Speech-to-Text to process your audio files using a machine learning model trained for data similar to your audio file.

    Objectives

    • Send a audio transcription request for audio recorded from a phone (like voicemail) to Speech-to-Text.
    • Specify an enhanced speech recognition model for an audio transcription request.

    Costs

    This tutorial uses billable components of Cloud Platform, including:

    • Speech-to-Text

    Use the Pricing Calculator to generate a cost estimate based on your projected usage.

    New Cloud Platform users might be eligible for a free trial .

    Before you begin

    This tutorial has several prerequisites:

    Send a request

    To best transcribe audio captured on a phone, like a phone call or voicemail, you can set the model field in your RecognitionConfig payload to phone_call . The model field tells Speech-to-Text API which speech recognition model to use for the transcription request.

    You can improve the results of phone audio transcription by using an enhanced model . To use an enhanced model, you set the useEnhanced field to true in your RecognitionConfig payload.

    The following code samples demonstrate how to select a specific transcription model when calling Speech-to-Text.

    Protocol

    Refer to the speech:recognize API endpoint for complete details.

    To perform synchronous speech recognition, make a POST request and provide the appropriate request body. The following shows an example of a POST request using curl . The example uses the Google Cloud CLI to generate an access token. For instructions on installing the gcloud CLI, see the quickstart .

    curl  
-s  
-H  
 "Content-Type: application/json" 
  
 \ 
  
-H  
 "Authorization: Bearer 
 $( 
gcloud  
auth  
application-default  
print-access-token ) 
 " 
  
 \ 
  
https://speech.googleapis.com/v1/speech:recognize  
 \ 
  
--data  
 '{ 
 "config": { 
 "encoding": "LINEAR16", 
 "languageCode": "en-US", 
 "enableWordTimeOffsets": false, 
 "enableAutomaticPunctuation": true, 
  "model": "phone_call", 
  "useEnhanced": true 
 }, 
 "audio": { 
 "uri": "gs://cloud-samples-tests/speech/commercial_mono.wav" 
 } 
 }'

    See the RecognitionConfig reference documentation for more information on configuring the request body.

    If the request is successful, the server returns a 200 OK HTTP status code and the response in JSON format:

     { 
  
 "results" 
:  
 [ 
  
 { 
  
 "alternatives" 
:  
 [ 
  
 { 
  
 "transcript" 
:  
 "Hi, I'd like to buy a Chromecast. I was wondering whether you could help me with that." 
,  
 "confidence" 
:  
 0 
.8930228  
 } 
  
 ] 
,  
 "resultEndTime" 
:  
 "5.640s" 
  
 } 
,  
 { 
  
 "alternatives" 
:  
 [ 
  
 { 
  
 "transcript" 
:  
 " Certainly, which color would you like? We are blue black and red." 
,  
 "confidence" 
:  
 0 
.9101991  
 } 
  
 ] 
,  
 "resultEndTime" 
:  
 "10.220s" 
  
 } 
,  
 { 
  
 "alternatives" 
:  
 [ 
  
 { 
  
 "transcript" 
:  
 " Let's go with the black one." 
,  
 "confidence" 
:  
 0 
.8818244  
 } 
  
 ] 
,  
 "resultEndTime" 
:  
 "13.870s" 
  
 } 
,  
 { 
  
 "alternatives" 
:  
 [ 
  
 { 
  
 "transcript" 
:  
 " Would you like the new Chromecast Ultra model or the regular Chromecast?" 
,  
 "confidence" 
:  
 0 
.94733626  
 } 
  
 ] 
,  
 "resultEndTime" 
:  
 "18.460s" 
  
 } 
,  
 { 
  
 "alternatives" 
:  
 [ 
  
 { 
  
 "transcript" 
:  
 " Regular Chromecast is fine. Thank you. Okay. Sure. Would you like to ship it regular or Express?" 
,  
 "confidence" 
:  
 0 
.9519095  
 } 
  
 ] 
,  
 "resultEndTime" 
:  
 "25.930s" 
  
 } 
,  
 { 
  
 "alternatives" 
:  
 [ 
  
 { 
  
 "transcript" 
:  
 " Express, please." 
,  
 "confidence" 
:  
 0 
.9101229  
 } 
  
 ] 
,  
 "resultEndTime" 
:  
 "28.260s" 
  
 } 
,  
 { 
  
 "alternatives" 
:  
 [ 
  
 { 
  
 "transcript" 
:  
 " Terrific. It's on the way. Thank you. Thank you very much. Bye." 
,  
 "confidence" 
:  
 0 
.9321616  
 } 
  
 ] 
,  
 "resultEndTime" 
:  
 "34.150s" 
  
 } 
  
 ] 
 }

    Go

    To learn how to install and use the client library for Speech-to-Text, see Speech-to-Text client libraries . For more information, see the Speech-to-Text Go API reference documentation .

    To authenticate to Speech-to-Text, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      func 
  
 enhancedModel 
 ( 
 w 
  
 io 
 . 
 Writer 
 ) 
  
 error 
  
 { 
  
 ctx 
  
 := 
  
 context 
 . 
 Background 
 () 
  
 client 
 , 
  
 err 
  
 := 
  
 speech 
 . 
 NewClient 
 ( 
 ctx 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "NewClient: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 defer 
  
 client 
 . 
 Close 
 () 
  
 data 
 , 
  
 err 
  
 := 
  
 os 
 . 
 ReadFile 
 ( 
 "../testdata/commercial_mono.wav" 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "ReadFile: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 resp 
 , 
  
 err 
  
 := 
  
 client 
 . 
 Recognize 
 ( 
 ctx 
 , 
  
& speechpb 
 . 
 RecognizeRequest 
 { 
  
 Config 
 : 
  
& speechpb 
 . 
 RecognitionConfig 
 { 
  
 Encoding 
 : 
  
 speechpb 
 . 
 RecognitionConfig_LINEAR16 
 , 
  
 SampleRateHertz 
 : 
  
 8000 
 , 
  
 LanguageCode 
 : 
  
 "en-US" 
 , 
  
 UseEnhanced 
 : 
  
 true 
 , 
  
 // A model must be specified to use enhanced model. 
  
 Model 
 : 
  
 "phone_call" 
 , 
  
 }, 
  
 Audio 
 : 
  
& speechpb 
 . 
 RecognitionAudio 
 { 
  
 AudioSource 
 : 
  
& speechpb 
 . 
 RecognitionAudio_Content 
 { 
 Content 
 : 
  
 data 
 }, 
  
 }, 
  
 }) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "client.Recognize: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 for 
  
 i 
 , 
  
 result 
  
 := 
  
 range 
  
 resp 
 . 
 Results 
  
 { 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "%s\n" 
 , 
  
 strings 
 . 
 Repeat 
 ( 
 "-" 
 , 
  
 20 
 )) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Result %d\n" 
 , 
  
 i 
 + 
 1 
 ) 
  
 for 
  
 j 
 , 
  
 alternative 
  
 := 
  
 range 
  
 result 
 . 
 Alternatives 
  
 { 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Alternative %d: %s\n" 
 , 
  
 j 
 + 
 1 
 , 
  
 alternative 
 . 
 Transcript 
 ) 
  
 } 
  
 } 
  
 return 
  
 nil 
 }

    Java

    To learn how to install and use the client library for Speech-to-Text, see Speech-to-Text client libraries . For more information, see the Speech-to-Text Java API reference documentation .

    To authenticate to Speech-to-Text, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      /** 
 * Transcribe the given audio file using an enhanced model. 
 * 
 * @param fileName the path to an audio file. 
 */ 
 public 
  
 static 
  
 void 
  
 transcribeFileWithEnhancedModel 
 ( 
 String 
  
 fileName 
 ) 
  
 throws 
  
 Exception 
  
 { 
  
 Path 
  
 path 
  
 = 
  
 Paths 
 . 
 get 
 ( 
 fileName 
 ); 
  
 byte 
 [] 
  
 content 
  
 = 
  
 Files 
 . 
 readAllBytes 
 ( 
 path 
 ); 
  
 try 
  
 ( 
 SpeechClient 
  
 speechClient 
  
 = 
  
 SpeechClient 
 . 
 create 
 ()) 
  
 { 
  
 // Get the contents of the local audio file 
  
 RecognitionAudio 
  
 recognitionAudio 
  
 = 
  
 RecognitionAudio 
 . 
 newBuilder 
 (). 
 setContent 
 ( 
 ByteString 
 . 
 copyFrom 
 ( 
 content 
 )). 
 build 
 (); 
  
 // Configure request to enable enhanced models 
  
 RecognitionConfig 
  
 config 
  
 = 
  
 RecognitionConfig 
 . 
 newBuilder 
 () 
  
 . 
 setEncoding 
 ( 
 AudioEncoding 
 . 
 LINEAR16 
 ) 
  
 . 
 setLanguageCode 
 ( 
 "en-US" 
 ) 
  
 . 
 setSampleRateHertz 
 ( 
 8000 
 ) 
  
 . 
 setUseEnhanced 
 ( 
 true 
 ) 
  
 // A model must be specified to use enhanced model. 
  
 . 
 setModel 
 ( 
 "phone_call" 
 ) 
  
 . 
 build 
 (); 
  
 // Perform the transcription request 
  
 RecognizeResponse 
  
 recognizeResponse 
  
 = 
  
 speechClient 
 . 
 recognize 
 ( 
 config 
 , 
  
 recognitionAudio 
 ); 
  
 // Print out the results 
  
 for 
  
 ( 
 SpeechRecognitionResult 
  
 result 
  
 : 
  
 recognizeResponse 
 . 
 getResultsList 
 ()) 
  
 { 
  
 // There can be several alternative transcripts for a given chunk of speech. Just use the 
  
 // first (most likely) one here. 
  
 SpeechRecognitionAlternative 
  
 alternative 
  
 = 
  
 result 
 . 
 getAlternatives 
 ( 
 0 
 ); 
  
 System 
 . 
 out 
 . 
 format 
 ( 
 "Transcript: %s\n\n" 
 , 
  
 alternative 
 . 
 getTranscript 
 ()); 
  
 } 
  
 } 
 }

    Node.js

    To learn how to install and use the client library for Speech-to-Text, see Speech-to-Text client libraries . For more information, see the Speech-to-Text Node.js API reference documentation .

    To authenticate to Speech-to-Text, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      // Imports the Google Cloud client library for Beta API 
 /** 
 * TODO(developer): Update client library import to use new 
 * version of API when desired features become available 
 */ 
 const 
  
 speech 
  
 = 
  
 require 
 ( 
 ' @google-cloud/speech 
' 
 ). 
 v1p1beta1 
 ; 
 const 
  
 fs 
  
 = 
  
 require 
 ( 
 'fs' 
 ); 
 // Creates a client 
 const 
  
 client 
  
 = 
  
 new 
  
 speech 
 . 
  SpeechClient 
 
 (); 
 /** 
 * TODO(developer): Uncomment the following lines before running the sample. 
 */ 
 // const filename = 'Local path to audio file, e.g. /path/to/audio.raw'; 
 // const encoding = 'Encoding of the audio file, e.g. LINEAR16'; 
 // const sampleRateHertz = 16000; 
 // const languageCode = 'BCP-47 language code, e.g. en-US'; 
 const 
  
 config 
  
 = 
  
 { 
  
 encoding 
 : 
  
 encoding 
 , 
  
 languageCode 
 : 
  
 languageCode 
 , 
  
 useEnhanced 
 : 
  
 true 
 , 
  
 model 
 : 
  
 'phone_call' 
 , 
 }; 
 const 
  
 audio 
  
 = 
  
 { 
  
 content 
 : 
  
 fs 
 . 
 readFileSync 
 ( 
 filename 
 ). 
 toString 
 ( 
 'base64' 
 ), 
 }; 
 const 
  
 request 
  
 = 
  
 { 
  
 config 
 : 
  
 config 
 , 
  
 audio 
 : 
  
 audio 
 , 
 }; 
 // Detects speech in the audio file 
 const 
  
 [ 
 response 
 ] 
  
 = 
  
 await 
  
 client 
 . 
 recognize 
 ( 
 request 
 ); 
 response 
 . 
 results 
 . 
 forEach 
 ( 
 result 
  
 = 
>  
 { 
  
 const 
  
 alternative 
  
 = 
  
 result 
 . 
 alternatives 
 [ 
 0 
 ]; 
  
 console 
 . 
 log 
 ( 
 alternative 
 . 
 transcript 
 ); 
 });

    Python

    To learn how to install and use the client library for Speech-to-Text, see Speech-to-Text client libraries . For more information, see the Speech-to-Text Python API reference documentation .

    To authenticate to Speech-to-Text, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      from 
  
 google.cloud 
  
 import 
 speech 
 def 
  
 transcribe_file_with_enhanced_model 
 ( 
 audio_file 
 : 
 str 
 ) 
 - 
> speech 
 . 
 RecognizeResponse 
 : 
  
 """Transcribe the given audio file using an enhanced model. 
 Args: 
 audio_file (str): Path to the local audio file to be transcribed. 
 Example: "resources/commercial_mono.wav" 
 Returns: 
 speech.RecognizeResponse: The response containing the transcription results. 
 """ 
 client 
 = 
 speech 
 . 
 SpeechClient 
 () 
 # audio_file = 'resources/commercial_mono.wav' 
 with 
 open 
 ( 
 audio_file 
 , 
 "rb" 
 ) 
 as 
 f 
 : 
 audio_content 
 = 
 f 
 . 
 read 
 () 
 audio 
 = 
 speech 
 . 
 RecognitionAudio 
 ( 
 content 
 = 
 audio_content 
 ) 
 config 
 = 
 speech 
 . 
 RecognitionConfig 
 ( 
 encoding 
 = 
 speech 
 . 
 RecognitionConfig 
 . 
 AudioEncoding 
 . 
 LINEAR16 
 , 
 sample_rate_hertz 
 = 
 8000 
 , 
 language_code 
 = 
 "en-US" 
 , 
 use_enhanced 
 = 
 True 
 , 
 # A model must be specified to use enhanced model. 
 model 
 = 
 "phone_call" 
 , 
 ) 
 response 
 = 
 client 
 . 
 recognize 
 ( 
 config 
 = 
 config 
 , 
 audio 
 = 
 audio 
 ) 
 for 
 i 
 , 
 result 
 in 
 enumerate 
 ( 
 response 
 . 
 results 
 ): 
 alternative 
 = 
 result 
 . 
 alternatives 
 [ 
 0 
 ] 
 print 
 ( 
 "-" 
 * 
 20 
 ) 
 print 
 ( 
 f 
 "First alternative of result 
 { 
 i 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Transcript: 
 { 
 alternative 
 . 
 transcript 
 } 
 " 
 ) 
 return 
 response

    Additional languages

    C#: Please follow the C# setup instructions on the client libraries page and then visit the Speech-to-Text reference documentation for .NET.

    PHP: Please follow the PHP setup instructions on the client libraries page and then visit the Speech-to-Text reference documentation for PHP.

    Ruby: Please follow the Ruby setup instructions on the client libraries page and then visit the Speech-to-Text reference documentation for Ruby.

    Clean up

    To avoid incurring charges to your Google Cloud account for the resources used in this tutorial, either delete the project that contains the resources, or keep the project and delete the individual resources.

    Delete the project

    The easiest way to eliminate billing is to delete the project that you created for the tutorial.

    To delete the project:

    1. In the Google Cloud console, go to the Manage resources page.

      Go to Manage resources

    2. In the project list, select the project that you want to delete, and then click Delete .
    3. In the dialog, type the project ID, and then click Shut down to delete the project.

    Delete instances

    To delete a Compute Engine instance:

    1. In the Google Cloud console, go to the VM instances page.

      Go to VM instances

    2. Select the checkbox for the instance that you want to delete.
    3. To delete the instance, click More actions , click Delete , and then follow the instructions.

    Delete firewall rules for the default network

    To delete a firewall rule:

    1. In the Google Cloud console, go to the Firewall page.

      Go to Firewall

    2. Select the checkbox for the firewall rule that you want to delete.
    3. To delete the firewall rule, click Delete .
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