先确认下，模型配置对吗。

前提条件对吗

设置API-KEY

export DASHSCOPE_API_KEY=YOUR_DASHSCOPE_API_KEY

需要使用您的API-KEY替换示例中的 YOUR_DASHSCOPE_API_KEY ，代码才能正常运行。

示例代码需要满足：

python sdk version: dashscope>=1.10.0

java sdk version: >=2.5.0

# For prerequisites running the following sample, visit https://help.aliyun.com/document_detail/611472.html

import pyaudio
import dashscope
from dashscope.audio.asr import (Recognition, RecognitionCallback,
                                 RecognitionResult)

dashscope.api_key='<your-dashscope-api-key>'

mic = None
stream = None

class Callback(RecognitionCallback):
    def on_open(self) -> None:
        global mic
        global stream
        print('RecognitionCallback open.')
        mic = pyaudio.PyAudio()
        stream = mic.open(format=pyaudio.paInt16,
                          channels=1,
                          rate=16000,
                          input=True)

    def on_close(self) -> None:
        global mic
        global stream
        print('RecognitionCallback close.')
        stream.stop_stream()
        stream.close()
        mic.terminate()
        stream = None
        mic = None

    def on_event(self, result: RecognitionResult) -> None:
        print('RecognitionCallback sentence: ', result.get_sentence())

callback = Callback()
recognition = Recognition(model='paraformer-realtime-v1',
                          format='pcm',
                          sample_rate=16000,
                          callback=callback)
recognition.start()

while True:
    if stream:
        data = stream.read(3200, exception_on_overflow = False)
        recognition.send_audio_frame(data)
    else:
        break

recognition.stop()

package com.alibaba.dashscope.sample.recognition.quickstart;

import com.alibaba.dashscope.audio.asr.recognition.Recognition;
import com.alibaba.dashscope.audio.asr.recognition.RecognitionParam;
import io.reactivex.BackpressureStrategy;
import io.reactivex.Flowable;
import java.nio.ByteBuffer;
import javax.sound.sampled.AudioFormat;
import javax.sound.sampled.AudioSystem;
import javax.sound.sampled.TargetDataLine;

public class Main {

  public static void main(String[] args) {
    // 创建一个Flowable<ByteBuffer>
    Flowable<ByteBuffer> audioSource =
        Flowable.create(
            emitter -> {
              new Thread(
                      () -> {
                        try {
                          // 创建音频格式
                          AudioFormat audioFormat = new AudioFormat(16000, 16, 1, true, false);
                          // 根据格式匹配默认录音设备
                          TargetDataLine targetDataLine =
                              AudioSystem.getTargetDataLine(audioFormat);
                          targetDataLine.open(audioFormat);
                          // 开始录音
                          targetDataLine.start();
                          ByteBuffer buffer = ByteBuffer.allocate(1024);
                          long start = System.currentTimeMillis();
                          // 录音30s并进行实时转写
                          while (System.currentTimeMillis() - start < 300000) {
                            int read = targetDataLine.read(buffer.array(), 0, buffer.capacity());
                            if (read > 0) {
                              buffer.limit(read);
                              // 将录音音频数据发送给流式识别服务
                              emitter.onNext(buffer);
                              buffer = ByteBuffer.allocate(1024);
                              // 录音速率有限，防止cpu占用过高，休眠一小会儿
                              Thread.sleep(20);
                            }
                          }
                          // 通知结束转写
                          emitter.onComplete();
                        } catch (Exception e) {
                          emitter.onError(e);
                        }
                      })
                  .start();
            },
            BackpressureStrategy.BUFFER);

    // 创建Recognizer
    Recognition recognizer = new Recognition();
    // 创建RecognitionParam，audioFrames参数中传入上面创建的Flowable<ByteBuffer>
    RecognitionParam param =
        RecognitionParam.builder()
            .model("paraformer-realtime-v1")
            .format("pcm")
            .sampleRate(16000)
            .apiKey("your-dashscope-api-key")
            .build();

    // 流式调用接口
    recognizer
        .streamCall(param, audioSource)
        // 调用Flowable的subscribe方法订阅结果
        .blockingForEach(
            result -> {
              // 打印最终结果
              if (result.isSentenceEnd()) {
                System.out.println("Fix:" + result.getSentence().getText());
              } else {
                System.out.println("Result:" + result.getSentence().getText());
              }
            });
    System.exit(0);
  }
}