Java Stanley NLP：语音标签的一部分

自然语言处理（NLP）与语音标签的关系

java
import edu.cmu.sphinx.frontend.util.Microphone;
import edu.cmu.sphinx.frontend.util.StreamDataSource;
import edu.cmu.sphinx.util.props.ConfigurationManager;
public class MFCCFeatureExtractor {
    public static void main(String[] args) throws Exception {
        ConfigurationManager cm = new ConfigurationManager("config.xml");
        StreamDataSource dataSource = (StreamDataSource) cm.lookup("streamDataSource");
        Microphone microphone = (Microphone) cm.lookup("microphone");
        if (microphone.startRecording()) {
            while (true) {
                float[] audioData = dataSource.getData();
                // 提取MFCC特征
                float[] mfccFeatures = extractMFCC(audioData);
                // 对MFCC特征进行后续处理
                // ...
            }
        }
    }
    private static float[] extractMFCC(float[] audioData) {
        // TODO: 实现MFCC特征提取算法
        return null;
    }
}

java
import edu.cmu.sphinx.api.Configuration;
import edu.cmu.sphinx.api.LiveSpeechRecognizer;
public class SpeechRecognizer {
    public static void main(String[] args) throws Exception {
        Configuration configuration = new Configuration();
        configuration.setAcousticModelPath("hmm/en-us");
        configuration.setDictionaryPath("hmm/cmudict-en-us.dict");
        configuration.setLanguageModelPath("hmm/en-us.lm.bin");
        LiveSpeechRecognizer recognizer = new LiveSpeechRecognizer(configuration);
        recognizer.startRecognition(true);
        while (true) {
            // 获取识别结果
            String result = recognizer.getResult().getHypothesis();
            // 处理识别结果
            // ...
        }
    }
}

java
import edu.stanford.nlp.pipeline.Annotation;
import edu.stanford.nlp.pipeline.StanfordCoreNLP;
import edu.stanford.nlp.util.PropertiesUtils;
public class TextTranscription {
    public static void main(String[] args) {
        StanfordCoreNLP pipeline = new StanfordCoreNLP(PropertiesUtils.asProperties(
                "annotators", "tokenize,ssplit,pos,lemma,ner,parse,depparse,coref",
                "ssplit.isOneSentence", "true",
                "tokenize.language", "en"
        ));
        String speechRecognitionResult = "Hello, how are you?";
        Annotation annotation = new Annotation(speechRecognitionResult);
        pipeline.annotate(annotation);
        // 获取文本转录结果
        String textTranscriptionResult = annotation.toString();
        // 处理文本转录结果
        // ...
    }
}