Is there a Java or C++ Open Speech Recognition Libraries?

Answer 1, Authority 100%

Look at CMU Sphinx (Open Source Toolkit For Speech Recognition).

Open source product for speech recognition, which includes a recognition library written in C, modifiable, a variable recognizer is written in Java.

Answer 2

Where to get the speech recognition engines themselves?
In Windows 7, they are not for the Russian version.

# include & lt; iostream & gt;
#Include "SPHELPER.H"
Short Main ()
{
  STD :: SYSTEM ("CHCP 1251");
  // Declare Local Identifiers:
  HRESULT HR = S_OK;
  CCOMPTR & LT; ISPRECOCOLONTEXT & GT; CPRECOCOLONTEXT;
  CCOMPTR & LT; ISPVOICE & GT; CPVoice;
  If (Failed (:: CoinItialize (NULL))) {
    STD :: COUT & LT; & LT; "N1) COM object initialization is not fulfilled!";
  } else {
    STD :: COUT & LT; & LT; "N1) The initialization of the COM object is completed!";
  }
hr = s_ok;
unsigned long num_engines = 0;
//
if (succeeded (hr))
{
STD :: COUT & LT; & LT; "\ N 1) We get engaging engines:";
HR = SPENUMTOKENS (SPCAT_RECOGNIZERS, NULL, NULL, & AMP; TOKEN);
}
if (succeeded (hr))
{
hr = token- & gt; getcount (& amp; num_engines);
STD :: COUT & LT; & LT; "\ N 2) Total engine:" & lt; & lt; num_engines;
}
  // CREATE A SHARED RECOGNITION CONTEXT.
  hr = cprecocontext.cocreateInstance (CLSID_SPSHAREDRECOGNIZER); // CLSID_SPINPROCRECCOCONTEXT CLSID_SPSHAREDRECOCOLONTEXT.
  If (succeeded (hr)) {
    // Create A Voice From The Context (With
    // SAME AUDIO FORMAT AS CONTEXT)
    HR = CPRECOCOCONTEXT- & GT; GetVoice (& amp; CPVoice);
  } else {
    STD :: COUT & LT; & LT; "Nudevice is not created";
  }
  If (succeeded (hr)) {
    // TELL THE ASSOCIATED VOICE TO STOP SPEAKING WHEN
    // The SR Engine Hears a Recognizable Sound.
    HR = CPRECOCOCONTEXT- & GT; SETVoicePurgeEvent (SPFEI (SPEI_SOUND_START));
  } else {
    STD :: COUT & LT; & LT; "NgetVoice () did not work";
  }
  If (succeeded (hr)) {
    // Do Stuff Here.
    STD :: COUT & LT; & LT; "N. SPECIAL";
  } else {
    STD :: COUT & LT; & LT; "NNE successful";
  }
}

Answer 3

You can try vosk . Advantages of the library:

• supports 8 languages ​​- Russian, English, German, French,
  Portuguese, Spanish, Chinese, Vietnamese. Soon
  Other

will be added.

• works without access to the network even on
  Mobile devices – Raspberry Pi, Android, iOS
• models for each language take up only 50mb, but there is much more
  Accurate large models for more accurate recognition
• is done for streaming sound, which allows you to implement instantaneous
  Reaction to Teams
• supports several popular programming languages ​​- C++, C, Java, C #, JavaScript
  • allows you to quickly customize the recognition dictionary to improve the recognition accuracy
  • allows you to identify the speaker

Example of work on Java such :

package test;
Import java.io.file;
Import java.io.fileInputStream;
Import java.io.fileoutputstream;
Import java.io.dataoutputstream;
Import java.io.ioException;
Import java.net.url;
Import java.nio. *;
Import org.kaldi.kaldirecognizer;
Import org.kaldi.Model;
import org.kaldi.spkmodel;
Public Class DecodeRTest {
  static {
    System.loadLibrary ("vosk_jni");
  }
  Public Static Void Main (String Args []) Throws IoException {
    FileInputStream AIS = NEW FileInputStream (New File ("/ Python / Example / Test.wav"));
    Model Model = NEW Model ("Model-EN");
    SPKModel SPKModel = New SPKModel ("Model-SPK");
    KALDIRECOGNIZER REC = New Kaldirecognizer (Model, SPKModel, 16000.0F);
    INT NBYETES; 
BYTE [] B = New Byte [4096];
     While ((nbytes = ais.read (b)) & gt; = 0) {
       if (rec.acceptwaveform (b)) {
         System.out.PrintLN (rec.result ());
       } else {
         System.Out.PrintLN (rec.partialResult ());
       }
     }
     System.Out.printLN (rec.finalResult ());
   }
}