使用PocketSphinx识别多个关键字

Question

我已经安装了PocketSphinx演示，它在Ubuntu和Eclipse下运行良好，但是尽管尝试过，我还是不知道如何添加对多个单词的识别。

我只想让代码识别单个单词，然后我可以在代码中切换（），例如“up”、“down”、“left”、“right”。我不想识别句子，只想识别单个单词。

在这方面的任何帮助都将不胜感激。我发现其他用户也有类似的问题，但到目前为止还没有人知道答案。

让我困惑的一件事是，为什么我们需要使用“唤醒”常数？

private static final String KWS_SEARCH = "wakeup";
private static final String KEYPHRASE = "oh mighty computer";
.
.
.
recognizer.addKeyphraseSearch(KWS_SEARCH, KEYPHRASE);

wakeup和什么有关系？

我取得了一些进展（？）：使用addGrammarSearch我可以使用。gram文件列出我的单词，例如向上、向下、向左、向右、向前、向后，如果我所说的都是那些特定的单词，这似乎很有效。但是，任何其他单词都会导致系统将所说的与所述单词中“最近”的单词匹配。理想情况下，如果所说的单词不在中，我不希望出现识别。gram文件。。。

Answer 1

正在更新安提诺乌斯修正案的PocketSphinx演示，以允许它在Android Studio上运行。这是我目前所拥有的，

//Note: change MainActivity to PocketSphinxActivity for demo use...
public class MainActivity extends Activity implements RecognitionListener {
private static final String DIGITS_SEARCH = "digits";
private SpeechRecognizer recognizer;

/* Used to handle permission request */
private static final int PERMISSIONS_REQUEST_RECORD_AUDIO = 1;

@Override
public void onCreate(Bundle state) {
    super.onCreate(state);

    setContentView(R.layout.main);
    ((TextView) findViewById(R.id.caption_text))
            .setText("Preparing the recognizer");

    // Check if user has given permission to record audio
    int permissionCheck = ContextCompat.checkSelfPermission(getApplicationContext(), Manifest.permission.RECORD_AUDIO);
    if (permissionCheck != PackageManager.PERMISSION_GRANTED) {
        ActivityCompat.requestPermissions(this, new String[]{Manifest.permission.RECORD_AUDIO}, PERMISSIONS_REQUEST_RECORD_AUDIO);
        return;
    }

    new AsyncTask<Void, Void, Exception>() {
        @Override
        protected Exception doInBackground(Void... params) {
            try {
                Assets assets = new Assets(MainActivity.this);
                File assetDir = assets.syncAssets();
                setupRecognizer(assetDir);
            } catch (IOException e) {
                return e;
            }
            return null;
        }
        @Override
        protected void onPostExecute(Exception result) {
            if (result != null) {
                ((TextView) findViewById(R.id.caption_text))
                        .setText("Failed to init recognizer " + result);
            } else {
                reset();
            }
        }
    }.execute();
    ((TextView) findViewById(R.id.caption_text)).setText("Say one, two, three, four, five, six...");
}

/**
 * In partial result we get quick updates about current hypothesis. In
 * keyword spotting mode we can react here, in other modes we need to wait
 * for final result in onResult.
 */

@Override
public void onPartialResult(Hypothesis hypothesis) {
    if (hypothesis == null) {
        return;
    } else if (hypothesis != null) {
        if (recognizer != null) {
            //recognizer.rapidSphinxPartialResult(hypothesis.getHypstr());
            String text = hypothesis.getHypstr();
            if (text.equals(DIGITS_SEARCH)) {
                recognizer.cancel();
                performAction();
                recognizer.startListening(DIGITS_SEARCH);
            }else{
                //Toast.makeText(getApplicationContext(),"Partial result = " +text,Toast.LENGTH_SHORT).show();
            }
        }
    }
}
@Override
public void onResult(Hypothesis hypothesis) {
    ((TextView) findViewById(R.id.result_text)).setText("");
    if (hypothesis != null) {
        String text = hypothesis.getHypstr();
        makeText(getApplicationContext(), "Hypothesis" +text, Toast.LENGTH_SHORT).show();
    }else if(hypothesis == null){
        makeText(getApplicationContext(), "hypothesis = null", Toast.LENGTH_SHORT).show();
    }
}
@Override
public void onDestroy() {
    super.onDestroy();
    recognizer.cancel();
    recognizer.shutdown();
}
@Override
public void onBeginningOfSpeech() {
}
@Override
public void onEndOfSpeech() {
   reset();
}
@Override
public void onTimeout() {
}
private void setupRecognizer(File assetsDir) throws IOException {
    // The recognizer can be configured to perform multiple searches
    // of different kind and switch between them
    recognizer = defaultSetup()
            .setAcousticModel(new File(assetsDir, "en-us-ptm"))
            .setDictionary(new File(assetsDir, "cmudict-en-us.dict"))
            // .setRawLogDir(assetsDir).setKeywordThreshold(1e-20f)
            .getRecognizer();
    recognizer.addListener(this);

    File digitsGrammar = new File(assetsDir, "digits.gram");
    recognizer.addKeywordSearch(DIGITS_SEARCH, digitsGrammar);
}
private void reset(){
    recognizer.stop();
    recognizer.startListening(DIGITS_SEARCH);
}
@Override
public void onError(Exception error) {
    ((TextView) findViewById(R.id.caption_text)).setText(error.getMessage());
}

public void performAction() {
    // do here whatever you want
    makeText(getApplicationContext(), "performAction done... ", Toast.LENGTH_SHORT).show();
}
}

买方注意：这是半成品。稍后再检查。如能提出建议，将不胜感激。

Answer 2

您可以使用addKeywordSearch，它用于使用关键字短语进行归档。例如，每行一个短语，每个短语在//中都有阈值

up /1.0/
down /1.0/
left /1.0/
right /1.0/
forwards /1e-1/

必须选择阈值以避免误报。

Answer 3

多亏了尼古拉的提示（见上面的答案），我开发了以下代码，运行良好，除非单词在列表中，否则无法识别它们。您可以将其直接复制并粘贴到PocketSphinxDemo代码中的主类上：

public class PocketSphinxActivity extends Activity implements RecognitionListener
{
private static final String DIGITS_SEARCH = "digits";
private SpeechRecognizer recognizer;

@Override
public void onCreate(Bundle state)
{
    super.onCreate(state);

    setContentView(R.layout.main);

    ((TextView) findViewById(R.id.caption_text)).setText("Preparing the recognizer");

    try
    {
        Assets assets = new Assets(PocketSphinxActivity.this);
        File assetDir = assets.syncAssets();
        setupRecognizer(assetDir);
    }
    catch (IOException e)
    {
        // oops
    }

    ((TextView) findViewById(R.id.caption_text)).setText("Say up, down, left, right, forwards, backwards");

    reset();
}

@Override
public void onPartialResult(Hypothesis hypothesis)
{
}

@Override
public void onResult(Hypothesis hypothesis)
{
    ((TextView) findViewById(R.id.result_text)).setText("");

    if (hypothesis != null)
    {
        String text = hypothesis.getHypstr();
        makeText(getApplicationContext(), text, Toast.LENGTH_SHORT).show();
    }
}

@Override
public void onBeginningOfSpeech()
{
}

@Override
public void onEndOfSpeech()
{
    reset();
}

private void setupRecognizer(File assetsDir)
{
    File modelsDir = new File(assetsDir, "models");

    recognizer = defaultSetup().setAcousticModel(new File(modelsDir, "hmm/en-us-semi"))
                               .setDictionary(new File(modelsDir, "dict/cmu07a.dic"))
                               .setRawLogDir(assetsDir).setKeywordThreshold(1e-20f)
                               .getRecognizer();

    recognizer.addListener(this);

    File digitsGrammar = new File(modelsDir, "grammar/digits.gram");
    recognizer.addKeywordSearch(DIGITS_SEARCH, digitsGrammar);
}

private void reset()
{
    recognizer.stop();
    recognizer.startListening(DIGITS_SEARCH);
}
}

您的数字。gram文件应类似于：

up /1e-1/
down /1e-1/
left /1e-1/
right /1e-1/
forwards /1e-1/
backwards /1e-1/

您应该在双斜杠/中尝试阈值以提高性能，其中1e-1表示0.1（我认为）。我认为最大值是1.0。

现在是下午5:30，所以我现在可以停止工作了。结果。