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This commit is contained in:
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101
test_audio.py
101
test_audio.py
@ -1,101 +0,0 @@
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#!/usr/bin/env python3
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"""
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简单的音频测试脚本,用于诊断树莓派上的音频问题
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"""
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import pyaudio
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import time
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import os
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def test_audio():
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"""测试音频设备"""
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print("=== 音频设备测试 ===")
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pa = pyaudio.PyAudio()
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# 列出所有设备
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print("\n可用的音频设备:")
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for i in range(pa.get_device_count()):
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info = pa.get_device_info_by_index(i)
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print(f" 设备 {i}: {info['name']}")
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print(f" 输入通道: {info['maxInputChannels']}")
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print(f" 输出通道: {info['maxOutputChannels']}")
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print(f" 默认采样率: {info['defaultSampleRate']}")
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print()
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# 查找默认输入设备
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default_input = pa.get_default_input_device_info()
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print(f"默认输入设备: {default_input['name']} (索引: {default_input['index']})")
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# 查找默认输出设备
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default_output = pa.get_default_output_device_info()
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print(f"默认输出设备: {default_output['name']} (索引: {default_output['index']})")
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pa.terminate()
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def test_recording():
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"""测试录音功能"""
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print("\n=== 录音测试 ===")
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pa = pyaudio.PyAudio()
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try:
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# 设置录音参数
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FORMAT = pyaudio.paInt16
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CHANNELS = 1
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RATE = 16000 # 降低采样率,使用设备默认的44100
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CHUNK = 1024
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print(f"尝试打开音频流,采样率: {RATE}")
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# 打开音频流
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stream = pa.open(
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format=FORMAT,
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channels=CHANNELS,
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rate=RATE,
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input=True,
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frames_per_buffer=CHUNK
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)
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print("开始录音5秒...")
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frames = []
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# 录音5秒
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for i in range(0, int(RATE / CHUNK * 5)):
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data = stream.read(CHUNK)
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frames.append(data)
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if i % 10 == 0:
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print(f"录音中... {i * CHUNK / RATE:.1f}秒")
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print("录音完成")
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# 停止流
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stream.stop_stream()
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stream.close()
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# 播放录音
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print("播放录音...")
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stream = pa.open(
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format=FORMAT,
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channels=CHANNELS,
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rate=RATE,
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output=True
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)
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for frame in frames:
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stream.write(frame)
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stream.stop_stream()
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stream.close()
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print("播放完成")
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except Exception as e:
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print(f"录音测试失败: {e}")
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finally:
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pa.terminate()
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if __name__ == "__main__":
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test_audio()
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test_recording()
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119
test_audio_playback.py
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119
test_audio_playback.py
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#!/usr/bin/env python3
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"""
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音频播放测试脚本
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用于测试树莓派的音频播放功能
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"""
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import subprocess
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import time
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import sys
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import os
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def test_audio_playback():
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"""测试音频播放功能"""
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print("=== 音频播放测试 ===")
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# 检查音频设备
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print("\n1. 检查音频设备...")
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try:
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result = subprocess.run(['aplay', '-l'], capture_output=True, text=True)
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if result.returncode == 0:
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print("音频设备列表:")
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print(result.stdout)
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else:
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print("错误: 无法获取音频设备列表")
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return False
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except FileNotFoundError:
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print("错误: aplay 命令未找到,请安装 alsa-utils")
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return False
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# 测试播放系统声音
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print("\n2. 测试播放系统提示音...")
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try:
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# 使用系统内置的测试声音
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result = subprocess.run(['speaker-test', '-t', 'sine', '-f', '440', '-l', '1'],
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capture_output=True, text=True, timeout=5)
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if result.returncode == 0:
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print("✓ 系统提示音播放成功")
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else:
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print("✗ 系统提示音播放失败")
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return False
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except (subprocess.TimeoutExpired, FileNotFoundError):
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print("提示: speaker-test 测试跳过,尝试直接播放音频文件")
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# 创建测试音频文件并播放
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print("\n3. 创建并播放测试音频文件...")
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test_audio_file = "/tmp/test_audio.wav"
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# 使用sox生成测试音频(如果可用)
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if os.path.exists("/usr/bin/sox"):
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try:
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subprocess.run(['sox', '-n', '-r', '44100', '-c', '2', test_audio_file,
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'synth', '3', 'sine', '440'], check=True)
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print("✓ 测试音频文件创建成功")
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except (subprocess.CalledProcessError, FileNotFoundError):
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print("无法创建测试音频文件,跳过文件播放测试")
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return True
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else:
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print("sox 未安装,跳过文件播放测试")
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return True
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# 播放测试音频文件
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try:
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result = subprocess.run(['aplay', test_audio_file], capture_output=True, text=True)
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if result.returncode == 0:
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print("✓ 音频文件播放成功")
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return True
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else:
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print("✗ 音频文件播放失败")
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print(f"错误信息: {result.stderr}")
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return False
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except FileNotFoundError:
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print("错误: aplay 命令未找到")
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return False
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finally:
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# 清理测试文件
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if os.path.exists(test_audio_file):
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os.remove(test_audio_file)
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def check_volume():
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"""检查并设置音量"""
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print("\n4. 检查音量设置...")
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try:
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result = subprocess.run(['amixer', 'sget', 'Master'], capture_output=True, text=True)
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if result.returncode == 0:
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print("当前音量设置:")
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print(result.stdout)
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# 设置音量到80%
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subprocess.run(['amixer', 'sset', 'Master', '80%'], check=True)
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print("✓ 音量已设置为80%")
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return True
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else:
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print("无法获取音量信息")
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return False
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except (subprocess.CalledProcessError, FileNotFoundError):
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print("amixer 命令未找到或执行失败")
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return False
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if __name__ == "__main__":
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print("树莓派音频播放功能测试")
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print("=" * 40)
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success = True
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# 检查音量
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if not check_volume():
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success = False
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# 测试音频播放
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if not test_audio_playback():
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success = False
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print("\n" + "=" * 40)
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if success:
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print("✓ 所有音频播放测试通过")
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sys.exit(0)
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else:
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print("✗ 部分音频播放测试失败")
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sys.exit(1)
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187
test_audio_recording.py
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187
test_audio_recording.py
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#!/usr/bin/env python3
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"""
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音频录音测试脚本
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用于测试树莓派的音频录音功能
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"""
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import subprocess
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import time
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import sys
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import os
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import signal
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def test_audio_recording():
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"""测试音频录音功能"""
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print("=== 音频录音测试 ===")
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# 检查录音设备
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print("\n1. 检查录音设备...")
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try:
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result = subprocess.run(['arecord', '-l'], capture_output=True, text=True)
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if result.returncode == 0:
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print("录音设备列表:")
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print(result.stdout)
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else:
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print("错误: 无法获取录音设备列表")
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return False
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except FileNotFoundError:
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print("错误: arecord 命令未找到,请安装 alsa-utils")
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return False
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# 录制测试音频
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print("\n2. 录制测试音频(5秒)...")
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test_record_file = "/tmp/test_record.wav"
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try:
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print("请对着麦克风说话(5秒录音开始)...")
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# 录制5秒音频
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result = subprocess.run(['arecord', '-d', '5', '-f', 'cd', test_record_file],
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capture_output=True, text=True)
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if result.returncode == 0:
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print("✓ 音频录制成功")
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# 检查文件是否存在且大小合理
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if os.path.exists(test_record_file):
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file_size = os.path.getsize(test_record_file)
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print(f"录制文件大小: {file_size} 字节")
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if file_size > 1000: # 至少1KB
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print("✓ 录音文件大小正常")
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return True
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else:
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print("✗ 录音文件太小,可能录音失败")
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return False
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else:
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print("✗ 录音文件未创建")
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return False
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else:
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print("✗ 音频录制失败")
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print(f"错误信息: {result.stderr}")
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return False
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except FileNotFoundError:
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print("错误: arecord 命令未找到")
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return False
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except KeyboardInterrupt:
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print("\n录音被用户中断")
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return False
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def test_audio_playback_verification():
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"""播放录制的音频进行验证"""
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print("\n3. 播放录制的音频进行验证...")
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test_record_file = "/tmp/test_record.wav"
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if not os.path.exists(test_record_file):
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print("错误: 找不到录制的音频文件")
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return False
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try:
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print("播放录制的音频...")
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result = subprocess.run(['aplay', test_record_file], capture_output=True, text=True)
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if result.returncode == 0:
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print("✓ 录音播放成功")
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return True
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else:
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print("✗ 录音播放失败")
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print(f"错误信息: {result.stderr}")
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return False
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except FileNotFoundError:
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print("错误: aplay 命令未找到")
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return False
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def test_microphone_levels():
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"""测试麦克风音量级别"""
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print("\n4. 测试麦克风音量级别...")
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try:
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# 获取麦克风音量
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result = subprocess.run(['amixer', 'sget', 'Capture'], capture_output=True, text=True)
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if result.returncode == 0:
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print("当前麦克风音量:")
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print(result.stdout)
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# 设置麦克风音量
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subprocess.run(['amixer', 'sset', 'Capture', '80%'], check=True)
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print("✓ 麦克风音量已设置为80%")
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return True
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else:
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print("无法获取麦克风音量信息")
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return False
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except (subprocess.CalledProcessError, FileNotFoundError):
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print("amixer 命令未找到或执行失败")
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return False
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def test_realtime_monitoring():
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"""实时音频监控测试"""
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print("\n5. 实时音频监控测试(3秒)...")
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try:
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print("开始实时监控,请对着麦克风说话...")
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# 使用parecord进行实时监控(如果可用)
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cmd = ['parecord', '--monitor', '--latency-msec', '100', '--duration', '3', '/dev/null']
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result = subprocess.run(cmd, capture_output=True, text=True, timeout=5)
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if result.returncode == 0:
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print("✓ 实时监控测试成功")
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return True
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else:
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print("提示: 实时监控测试跳过(需要pulseaudio)")
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return True
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except (subprocess.TimeoutExpired, FileNotFoundError, subprocess.CalledProcessError):
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print("提示: 实时监控测试跳过")
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return True
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def cleanup():
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"""清理测试文件"""
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test_files = ["/tmp/test_record.wav"]
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for file_path in test_files:
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if os.path.exists(file_path):
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try:
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os.remove(file_path)
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print(f"✓ 已清理测试文件: {file_path}")
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except OSError:
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print(f"警告: 无法清理测试文件: {file_path}")
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if __name__ == "__main__":
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print("树莓派音频录音功能测试")
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print("=" * 40)
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success = True
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# 测试麦克风音量
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if not test_microphone_levels():
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success = False
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# 测试音频录制
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if not test_audio_recording():
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success = False
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# 播放录制的音频
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if os.path.exists("/tmp/test_record.wav"):
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if not test_audio_playback_verification():
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success = False
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# 实时监控测试
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if not test_realtime_monitoring():
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success = False
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print("\n" + "=" * 40)
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if success:
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print("✓ 所有音频录音测试通过")
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else:
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print("✗ 部分音频录音测试失败")
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# 清理测试文件
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cleanup()
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sys.exit(0 if success else 1)
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@ -1,483 +0,0 @@
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#!/usr/bin/env python3
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"""
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Voice Assistant: Real-Time Voice Chat
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This app runs on a Raspberry Pi (or Linux desktop) and creates a low-latency, full-duplex voice interaction
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with an AI character. It uses local speech recognition
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(Vosk), local text-to-speech synthesis (Piper), and a locally hosted large language model via Ollama.
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Key Features:
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- Wake-free, continuous voice recognition with real-time transcription
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- LLM-driven responses streamed from a selected local model (e.g., LLaMA, Qwen, Gemma)
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- Audio response synthesis with a gruff custom voice using ONNX-based Piper models
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- Optional noise mixing and filtering via SoX
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- System volume control via ALSA
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- Modular and responsive design suitable for low-latency, character-driven agents
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Ideal for embedded voice AI demos, cosplay companions, or standalone AI characters.
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Copyright: M15.ai
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License: MIT
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"""
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import io
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import json
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import os
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import queue
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import re
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import subprocess
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import threading
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import time
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import wave
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import numpy as np
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import pyaudio
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import requests
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import soxr
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from pydub import AudioSegment
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from vosk import KaldiRecognizer, Model
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# ------------------- TIMING UTILITY -------------------
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class Timer:
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def __init__(self, label):
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self.label = label
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self.enabled = True
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def __enter__(self):
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self.start = time.time()
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return self
|
||||
def __exit__(self, exc_type, exc_val, exc_tb):
|
||||
if self.enabled:
|
||||
elapsed_ms = (time.time() - self.start) * 1000
|
||||
print(f"[Timing] {self.label}: {elapsed_ms:.0f} ms")
|
||||
def disable(self):
|
||||
self.enabled = False
|
||||
|
||||
# ------------------- FUNCTIONS -------------------
|
||||
|
||||
def get_input_device_index(preferred_name="default"):
|
||||
pa = pyaudio.PyAudio()
|
||||
index = None
|
||||
for i in range(pa.get_device_count()):
|
||||
info = pa.get_device_info_by_index(i)
|
||||
if preferred_name.lower() in info['name'].lower() and info['maxInputChannels'] > 0:
|
||||
print(f"[Debug] Selected input device {i}: {info['name']}")
|
||||
print(f"[Debug] Device sample rate: {info['defaultSampleRate']} Hz")
|
||||
index = i
|
||||
break
|
||||
pa.terminate()
|
||||
if index is None:
|
||||
print("[Warning] Preferred mic not found. Using default.")
|
||||
return None
|
||||
return index
|
||||
|
||||
def get_output_device_index(preferred_name="default"):
|
||||
pa = pyaudio.PyAudio()
|
||||
index = None
|
||||
for i in range(pa.get_device_count()):
|
||||
info = pa.get_device_info_by_index(i)
|
||||
if preferred_name.lower() in info['name'].lower() and info['maxOutputChannels'] > 0:
|
||||
print(f"[Debug] Selected output device {i}: {info['name']}")
|
||||
index = i
|
||||
break
|
||||
pa.terminate()
|
||||
if index is None:
|
||||
print("[Warning] Preferred output device not found. Using default.")
|
||||
return None
|
||||
return index
|
||||
|
||||
def parse_card_number(device_str):
|
||||
"""
|
||||
Extract ALSA card number from string like 'plughw:3,0'
|
||||
"""
|
||||
try:
|
||||
return int(device_str.split(":")[1].split(",")[0])
|
||||
except Exception as e:
|
||||
print(f"[Warning] Could not parse card number from {device_str}: {e}")
|
||||
return 0 # fallback
|
||||
|
||||
def list_input_devices():
|
||||
pa = pyaudio.PyAudio()
|
||||
print("[Debug] Available input devices:")
|
||||
for i in range(pa.get_device_count()):
|
||||
info = pa.get_device_info_by_index(i)
|
||||
if info['maxInputChannels'] > 0:
|
||||
print(f" {i}: {info['name']} ({int(info['defaultSampleRate'])} Hz, {info['maxInputChannels']}ch)")
|
||||
pa.terminate()
|
||||
|
||||
def resample_audio(data, orig_rate=48000, target_rate=16000):
|
||||
# Convert byte string to numpy array
|
||||
audio_np = np.frombuffer(data, dtype=np.int16)
|
||||
# Resample using soxr
|
||||
resampled_np = soxr.resample(audio_np, orig_rate, target_rate)
|
||||
# Convert back to bytes
|
||||
return resampled_np.astype(np.int16).tobytes()
|
||||
|
||||
def set_output_volume(volume_level, card_id=0):
|
||||
"""
|
||||
Set output volume using ALSA 'Speaker' control on specified card.
|
||||
volume_level: 1–10 (user scale)
|
||||
card_id: ALSA card number (from aplay -l)
|
||||
"""
|
||||
percent = max(1, min(volume_level, 10)) * 10 # map to 10–100%
|
||||
try:
|
||||
subprocess.run(
|
||||
['amixer', '-c', str(card_id), 'sset', 'Speaker', str(percent) + '%'],
|
||||
check=True,
|
||||
stdout=subprocess.DEVNULL,
|
||||
stderr=subprocess.DEVNULL
|
||||
)
|
||||
print(f"[Debug] Volume set to {percent}% on card {card_id}")
|
||||
except Exception as e:
|
||||
print(f"[Warning] Volume control failed on card {card_id}: {e}")
|
||||
|
||||
# ------------------- PATHS -------------------
|
||||
|
||||
CONFIG_PATH = os.path.expanduser("va_config.json")
|
||||
BASE_DIR = os.path.dirname(__file__)
|
||||
MODEL_PATH = os.path.join(BASE_DIR, 'vosk-model')
|
||||
CHAT_URL = 'https://open.bigmodel.cn/api/paas/v4/chat/completions'
|
||||
AUTH_TOKEN = '0c9cbaca9d2bbf864990f1e1decdf340.dXRMsZCHTUbPQ0rm' # Replace with your actual token
|
||||
|
||||
# ------------------- CONFIG FILE LOADING -------------------
|
||||
|
||||
DEFAULT_CONFIG = {
|
||||
"volume": 9,
|
||||
"mic_name": "default",
|
||||
"audio_output_device": "default",
|
||||
"model_name": "glm-4.5",
|
||||
"voice": "en_US-kathleen-low.onnx",
|
||||
"enable_audio_processing": False,
|
||||
"history_length": 4,
|
||||
"system_prompt": "You are a helpful assistant."
|
||||
}
|
||||
|
||||
def load_config():
|
||||
# Load config from system file or fall back to defaults
|
||||
if os.path.isfile(CONFIG_PATH):
|
||||
try:
|
||||
with open(CONFIG_PATH, 'r') as f:
|
||||
user_config = json.load(f)
|
||||
return {**DEFAULT_CONFIG, **user_config} # merge with defaults
|
||||
except Exception as e:
|
||||
print(f"[Warning] Failed to load system config: {e}")
|
||||
|
||||
print("[Debug] Using default config.")
|
||||
return DEFAULT_CONFIG
|
||||
|
||||
config = load_config()
|
||||
|
||||
# Apply loaded config values
|
||||
VOLUME = config["volume"]
|
||||
MIC_NAME = config["mic_name"]
|
||||
AUDIO_OUTPUT_DEVICE = config["audio_output_device"]
|
||||
AUDIO_OUTPUT_DEVICE_INDEX = get_output_device_index(config["audio_output_device"])
|
||||
OUTPUT_CARD = parse_card_number(AUDIO_OUTPUT_DEVICE) if AUDIO_OUTPUT_DEVICE else 0
|
||||
MODEL_NAME = config["model_name"]
|
||||
VOICE_MODEL = os.path.join("voices", config["voice"])
|
||||
ENABLE_AUDIO_PROCESSING = config["enable_audio_processing"]
|
||||
HISTORY_LENGTH = config["history_length"]
|
||||
|
||||
# Set system volume
|
||||
set_output_volume(VOLUME, OUTPUT_CARD)
|
||||
|
||||
# Setup messages with system prompt
|
||||
messages = [{"role": "system", "content": config["system_prompt"]}]
|
||||
|
||||
list_input_devices()
|
||||
RATE = 48000
|
||||
CHUNK = 1024
|
||||
CHANNELS = 1
|
||||
mic_enabled = True
|
||||
DEVICE_INDEX = get_input_device_index()
|
||||
|
||||
# SOUND EFFECTS
|
||||
NOISE_LEVEL = '0.04'
|
||||
BANDPASS_HIGHPASS = '300'
|
||||
BANDPASS_LOWPASS = '800'
|
||||
|
||||
# ------------------- VOICE MODEL -------------------
|
||||
|
||||
VOICE_MODELS_DIR = os.path.join(BASE_DIR, 'voices')
|
||||
if not os.path.isdir(VOICE_MODELS_DIR):
|
||||
os.makedirs(VOICE_MODELS_DIR)
|
||||
|
||||
VOICE_MODEL = os.path.join(VOICE_MODELS_DIR, config["voice"])
|
||||
|
||||
print('[Debug] Available Piper voices:')
|
||||
for f in os.listdir(VOICE_MODELS_DIR):
|
||||
if f.endswith('.onnx'):
|
||||
print(' ', f)
|
||||
print(f'[Debug] Using VOICE_MODEL: {VOICE_MODEL}')
|
||||
print(f"[Debug] Config loaded: model={MODEL_NAME}, voice={config['voice']}, vol={VOLUME}, mic={MIC_NAME}")
|
||||
|
||||
# ------------------- CONVERSATION STATE -------------------
|
||||
|
||||
audio_queue = queue.Queue()
|
||||
|
||||
# Audio callback form Shure
|
||||
def audio_callback(in_data, frame_count, time_info, status):
|
||||
global mic_enabled
|
||||
if not mic_enabled:
|
||||
return (None, pyaudio.paContinue)
|
||||
resampled_data = resample_audio(in_data, orig_rate=48000, target_rate=16000)
|
||||
audio_queue.put(resampled_data)
|
||||
return (None, pyaudio.paContinue)
|
||||
|
||||
# ------------------- STREAM SETUP -------------------
|
||||
|
||||
def start_stream():
|
||||
pa = pyaudio.PyAudio()
|
||||
|
||||
stream = pa.open(
|
||||
rate=RATE,
|
||||
format=pyaudio.paInt16,
|
||||
channels=CHANNELS,
|
||||
input=True,
|
||||
input_device_index=DEVICE_INDEX,
|
||||
frames_per_buffer=CHUNK,
|
||||
stream_callback=audio_callback
|
||||
)
|
||||
stream.start_stream()
|
||||
print(f'[Debug] Stream @ {RATE}Hz')
|
||||
return pa, stream
|
||||
|
||||
# ------------------- QUERY GLM API -------------------
|
||||
|
||||
def query_glm():
|
||||
headers = {
|
||||
'Authorization': 'Bearer ' + AUTH_TOKEN,
|
||||
'Content-Type': 'application/json'
|
||||
}
|
||||
payload = {
|
||||
"model": "glm-4.5",
|
||||
"messages": [messages[0]] + messages[-HISTORY_LENGTH:], # force system prompt at top
|
||||
"temperature": 0.6,
|
||||
"max_tokens": 1024,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
with Timer("Inference"): # measure inference latency
|
||||
try:
|
||||
resp = requests.post(CHAT_URL, json=payload, headers=headers)
|
||||
resp.raise_for_status() # Raise exception for HTTP errors
|
||||
except requests.exceptions.RequestException as e:
|
||||
print(f"[Error] GLM API request failed: {e}")
|
||||
return ''
|
||||
|
||||
data = resp.json()
|
||||
# Extract assistant message
|
||||
reply = ''
|
||||
if 'choices' in data and len(data['choices']) > 0:
|
||||
choice = data['choices'][0]
|
||||
if 'message' in choice and 'content' in choice['message']:
|
||||
reply = choice['message']['content'].strip()
|
||||
return reply
|
||||
|
||||
# ------------------- TTS & DEGRADATION -------------------
|
||||
|
||||
import tempfile
|
||||
|
||||
def play_response(text):
|
||||
import io
|
||||
import tempfile
|
||||
|
||||
# Mute the mic during playback to avoid feedback loop
|
||||
global mic_enabled
|
||||
mic_enabled = False # 🔇 mute mic
|
||||
|
||||
# clean the response
|
||||
clean = re.sub(r"[\*]+", '', text) # remove asterisks
|
||||
clean = re.sub(r"\(.*?\)", '', clean) # remove (stage directions)
|
||||
clean = re.sub(r"<.*?>", '', clean) # remove HTML-style tags
|
||||
clean = clean.replace('\n', ' ').strip() # normalize newlines
|
||||
clean = re.sub(r'\s+', ' ', clean) # collapse whitespace
|
||||
clean = re.sub(r'[\U0001F300-\U0001FAFF\u2600-\u26FF\u2700-\u27BF]+', '', clean) # remove emojis
|
||||
|
||||
piper_path = os.path.join(BASE_DIR, 'bin', 'piper', 'piper')
|
||||
|
||||
# 1. Generate Piper raw PCM
|
||||
with Timer("Piper inference"):
|
||||
try:
|
||||
piper_proc = subprocess.Popen(
|
||||
[piper_path, '--model', VOICE_MODEL, '--output_raw'],
|
||||
stdin=subprocess.PIPE,
|
||||
stdout=subprocess.PIPE,
|
||||
stderr=subprocess.DEVNULL
|
||||
)
|
||||
tts_pcm, _ = piper_proc.communicate(input=clean.encode())
|
||||
except Exception as e:
|
||||
print(f"[Error] Piper TTS failed: {e}")
|
||||
return
|
||||
|
||||
if ENABLE_AUDIO_PROCESSING:
|
||||
# SoX timing consolidation
|
||||
sox_start = time.time()
|
||||
|
||||
# 2. Convert raw PCM to WAV
|
||||
pcm_to_wav = subprocess.Popen(
|
||||
['sox', '-t', 'raw', '-r', '16000', '-c', str(CHANNELS), '-b', '16',
|
||||
'-e', 'signed-integer', '-', '-t', 'wav', '-'],
|
||||
stdin=subprocess.PIPE,
|
||||
stdout=subprocess.PIPE,
|
||||
stderr=subprocess.DEVNULL
|
||||
)
|
||||
tts_wav_16k, _ = pcm_to_wav.communicate(input=tts_pcm)
|
||||
|
||||
# 3. Estimate duration
|
||||
duration_sec = len(tts_pcm) / (RATE * 2)
|
||||
|
||||
# 4. Generate white noise WAV bytes
|
||||
noise_bytes = subprocess.check_output([
|
||||
'sox', '-n',
|
||||
'-r', '16000',
|
||||
'-c', str(CHANNELS),
|
||||
'-b', '16',
|
||||
'-e', 'signed-integer',
|
||||
'-t', 'wav', '-',
|
||||
'synth', str(duration_sec),
|
||||
'whitenoise', 'vol', NOISE_LEVEL
|
||||
], stderr=subprocess.DEVNULL)
|
||||
|
||||
# 5. Write both to temp files & mix
|
||||
with tempfile.NamedTemporaryFile(suffix='.wav') as tts_file, tempfile.NamedTemporaryFile(suffix='.wav') as noise_file:
|
||||
tts_file.write(tts_wav_16k)
|
||||
noise_file.write(noise_bytes)
|
||||
tts_file.flush()
|
||||
noise_file.flush()
|
||||
mixer = subprocess.Popen(
|
||||
['sox', '-m', tts_file.name, noise_file.name, '-t', 'wav', '-'],
|
||||
stdout=subprocess.PIPE,
|
||||
stderr=subprocess.DEVNULL
|
||||
)
|
||||
mixed_bytes, _ = mixer.communicate()
|
||||
|
||||
# 6. Apply filter
|
||||
filter_proc = subprocess.Popen(
|
||||
#['sox', '-t', 'wav', '-', '-t', 'wav', '-', 'highpass', BANDPASS_HIGHPASS, 'lowpass', BANDPASS_LOWPASS],
|
||||
['sox', '-t', 'wav', '-', '-r', '48000', '-t', 'wav', '-',
|
||||
'highpass', BANDPASS_HIGHPASS, 'lowpass', BANDPASS_LOWPASS],
|
||||
stdin=subprocess.PIPE,
|
||||
stdout=subprocess.PIPE,
|
||||
stderr=subprocess.DEVNULL
|
||||
)
|
||||
final_bytes, _ = filter_proc.communicate(input=mixed_bytes)
|
||||
|
||||
sox_elapsed = (time.time() - sox_start) * 1000
|
||||
print(f"[Timing] SoX (total): {int(sox_elapsed)} ms")
|
||||
|
||||
else:
|
||||
# No FX: just convert raw PCM to WAV
|
||||
pcm_to_wav = subprocess.Popen(
|
||||
['sox', '-t', 'raw', '-r', '16000', '-c', str(CHANNELS), '-b', '16',
|
||||
'-e', 'signed-integer', '-', '-t', 'wav', '-'],
|
||||
stdin=subprocess.PIPE,
|
||||
stdout=subprocess.PIPE,
|
||||
stderr=subprocess.DEVNULL
|
||||
)
|
||||
tts_wav_16k, _ = pcm_to_wav.communicate(input=tts_pcm)
|
||||
|
||||
resample_proc = subprocess.Popen(
|
||||
['sox', '-t', 'wav', '-', '-r', '48000', '-t', 'wav', '-'],
|
||||
stdin=subprocess.PIPE,
|
||||
stdout=subprocess.PIPE,
|
||||
stderr=subprocess.DEVNULL
|
||||
)
|
||||
final_bytes, _ = resample_proc.communicate(input=tts_wav_16k)
|
||||
|
||||
# 7. Playback
|
||||
with Timer("Playback"):
|
||||
try:
|
||||
wf = wave.open(io.BytesIO(final_bytes), 'rb')
|
||||
|
||||
pa = pyaudio.PyAudio()
|
||||
stream = pa.open(
|
||||
format=pa.get_format_from_width(wf.getsampwidth()),
|
||||
channels=wf.getnchannels(),
|
||||
rate=wf.getframerate(),
|
||||
output=True,
|
||||
output_device_index=AUDIO_OUTPUT_DEVICE_INDEX
|
||||
)
|
||||
|
||||
data = wf.readframes(CHUNK)
|
||||
while data:
|
||||
stream.write(data)
|
||||
data = wf.readframes(CHUNK)
|
||||
|
||||
stream.stop_stream()
|
||||
stream.close()
|
||||
pa.terminate()
|
||||
wf.close()
|
||||
|
||||
except wave.Error as e:
|
||||
print(f"[Error] Could not open final WAV: {e}")
|
||||
|
||||
finally:
|
||||
mic_enabled = True # 🔊 unmute mic
|
||||
time.sleep(0.3) # optional: small cooldown
|
||||
|
||||
|
||||
# ------------------- PROCESSING LOOP -------------------
|
||||
|
||||
def processing_loop():
|
||||
try:
|
||||
model = Model(MODEL_PATH)
|
||||
except Exception as e:
|
||||
print(f"[Error] Failed to load Vosk model: {e}")
|
||||
print(f"[Info] Model path: {MODEL_PATH}")
|
||||
return
|
||||
|
||||
#rec = KaldiRecognizer(model, RATE)
|
||||
rec = KaldiRecognizer(model, 16000)
|
||||
MAX_DEBUG_LEN = 200 # optional: limit length of debug output
|
||||
LOW_EFFORT_UTTERANCES = {"huh", "uh", "um", "erm", "hmm", "he's", "but"}
|
||||
|
||||
while True:
|
||||
data = audio_queue.get()
|
||||
|
||||
if rec.AcceptWaveform(data):
|
||||
start = time.time()
|
||||
r = json.loads(rec.Result())
|
||||
elapsed_ms = int((time.time() - start) * 1000)
|
||||
|
||||
user = r.get('text', '').strip()
|
||||
if user:
|
||||
print(f"[Timing] STT parse: {elapsed_ms} ms")
|
||||
print("User:", user)
|
||||
|
||||
if user.lower().strip(".,!? ") in LOW_EFFORT_UTTERANCES:
|
||||
print("[Debug] Ignored low-effort utterance.")
|
||||
rec = KaldiRecognizer(model, 16000)
|
||||
continue # Skip LLM response + TTS for accidental noise
|
||||
|
||||
messages.append({"role": "user", "content": user})
|
||||
# Generate assistant response
|
||||
resp_text = query_glm()
|
||||
if resp_text:
|
||||
# Clean debug print (remove newlines and carriage returns)
|
||||
clean_debug_text = resp_text.replace('\n', ' ').replace('\r', ' ')
|
||||
if len(clean_debug_text) > MAX_DEBUG_LEN:
|
||||
clean_debug_text = clean_debug_text[:MAX_DEBUG_LEN] + '...'
|
||||
|
||||
print('Assistant:', clean_debug_text)
|
||||
messages.append({"role": "assistant", "content": clean_debug_text})
|
||||
|
||||
# TTS generation + playback
|
||||
play_response(resp_text)
|
||||
else:
|
||||
print('[Debug] Empty response, skipping TTS.')
|
||||
|
||||
# Reset recognizer after each full interaction
|
||||
rec = KaldiRecognizer(model, 16000)
|
||||
|
||||
# ------------------- MAIN -------------------
|
||||
|
||||
if __name__ == '__main__':
|
||||
pa, stream = start_stream()
|
||||
t = threading.Thread(target=processing_loop, daemon=True)
|
||||
t.start()
|
||||
try:
|
||||
while stream.is_active():
|
||||
time.sleep(0.1)
|
||||
except KeyboardInterrupt:
|
||||
stream.stop_stream(); stream.close(); pa.terminate()
|
||||
@ -1,381 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Voice Assistant: Real-Time Voice Chat (修复版)
|
||||
|
||||
修复了树莓派上的音频设备问题
|
||||
"""
|
||||
|
||||
import io
|
||||
import json
|
||||
import os
|
||||
import queue
|
||||
import re
|
||||
import subprocess
|
||||
import threading
|
||||
import time
|
||||
import wave
|
||||
|
||||
import numpy as np
|
||||
import pyaudio
|
||||
import requests
|
||||
import soxr
|
||||
from pydub import AudioSegment
|
||||
from vosk import KaldiRecognizer, Model
|
||||
|
||||
|
||||
# ------------------- TIMING UTILITY -------------------
|
||||
class Timer:
|
||||
def __init__(self, label):
|
||||
self.label = label
|
||||
self.enabled = True
|
||||
def __enter__(self):
|
||||
self.start = time.time()
|
||||
return self
|
||||
def __exit__(self, exc_type, exc_val, exc_tb):
|
||||
if self.enabled:
|
||||
elapsed_ms = (time.time() - self.start) * 1000
|
||||
print(f"[Timing] {self.label}: {elapsed_ms:.0f} ms")
|
||||
def disable(self):
|
||||
self.enabled = False
|
||||
|
||||
# ------------------- FUNCTIONS -------------------
|
||||
|
||||
def get_input_device_index(preferred_name=None):
|
||||
pa = pyaudio.PyAudio()
|
||||
try:
|
||||
# 首先尝试获取默认设备
|
||||
if preferred_name is None:
|
||||
default_input = pa.get_default_input_device_info()
|
||||
print(f"[Debug] Using default input device: {default_input['name']}")
|
||||
return default_input['index']
|
||||
|
||||
# 如果有指定名称,尝试匹配
|
||||
for i in range(pa.get_device_count()):
|
||||
info = pa.get_device_info_by_index(i)
|
||||
if info['maxInputChannels'] > 0 and preferred_name.lower() in info['name'].lower():
|
||||
print(f"[Debug] Selected input device {i}: {info['name']}")
|
||||
print(f"[Debug] Device sample rate: {info['defaultSampleRate']} Hz")
|
||||
return i
|
||||
|
||||
# 如果没找到,使用默认设备
|
||||
default_input = pa.get_default_input_device_info()
|
||||
print(f"[Warning] Preferred mic not found. Using default: {default_input['name']}")
|
||||
return default_input['index']
|
||||
finally:
|
||||
pa.terminate()
|
||||
|
||||
def get_output_device_index(preferred_name=None):
|
||||
pa = pyaudio.PyAudio()
|
||||
try:
|
||||
# 首先尝试获取默认设备
|
||||
if preferred_name is None:
|
||||
default_output = pa.get_default_output_device_info()
|
||||
print(f"[Debug] Using default output device: {default_output['name']}")
|
||||
return default_output['index']
|
||||
|
||||
# 如果有指定名称,尝试匹配
|
||||
for i in range(pa.get_device_count()):
|
||||
info = pa.get_device_info_by_index(i)
|
||||
if info['maxOutputChannels'] > 0 and preferred_name.lower() in info['name'].lower():
|
||||
print(f"[Debug] Selected output device {i}: {info['name']}")
|
||||
return i
|
||||
|
||||
# 如果没找到,使用默认设备
|
||||
default_output = pa.get_default_output_device_info()
|
||||
print(f"[Warning] Preferred output device not found. Using default: {default_output['name']}")
|
||||
return default_output['index']
|
||||
finally:
|
||||
pa.terminate()
|
||||
|
||||
def list_input_devices():
|
||||
pa = pyaudio.PyAudio()
|
||||
try:
|
||||
print("[Debug] Available input devices:")
|
||||
for i in range(pa.get_device_count()):
|
||||
info = pa.get_device_info_by_index(i)
|
||||
if info['maxInputChannels'] > 0:
|
||||
print(f" {i}: {info['name']} ({int(info['defaultSampleRate'])} Hz, {info['maxInputChannels']}ch)")
|
||||
finally:
|
||||
pa.terminate()
|
||||
|
||||
def resample_audio(data, orig_rate=44100, target_rate=16000):
|
||||
# Convert byte string to numpy array
|
||||
audio_np = np.frombuffer(data, dtype=np.int16)
|
||||
# Resample using soxr
|
||||
resampled_np = soxr.resample(audio_np, orig_rate, target_rate)
|
||||
# Convert back to bytes
|
||||
return resampled_np.astype(np.int16).tobytes()
|
||||
|
||||
# ------------------- PATHS -------------------
|
||||
|
||||
CONFIG_PATH = os.path.expanduser("va_config.json")
|
||||
BASE_DIR = os.path.dirname(__file__)
|
||||
MODEL_PATH = os.path.join(BASE_DIR, 'vosk-model')
|
||||
CHAT_URL = 'https://open.bigmodel.cn/api/paas/v4/chat/completions'
|
||||
AUTH_TOKEN = '0c9cbaca9d2bbf864990f1e1decdf340.dXRMsZCHTUbPQ0rm'
|
||||
|
||||
# ------------------- CONFIG FILE LOADING -------------------
|
||||
|
||||
DEFAULT_CONFIG = {
|
||||
"volume": 8,
|
||||
"mic_name": None,
|
||||
"audio_output_device": None,
|
||||
"model_name": "glm-4.5",
|
||||
"voice": "en_US-kathleen-low.onnx",
|
||||
"enable_audio_processing": False,
|
||||
"history_length": 4,
|
||||
"system_prompt": "You are a helpful assistant."
|
||||
}
|
||||
|
||||
def load_config():
|
||||
if os.path.isfile(CONFIG_PATH):
|
||||
try:
|
||||
with open(CONFIG_PATH, 'r') as f:
|
||||
user_config = json.load(f)
|
||||
return {**DEFAULT_CONFIG, **user_config}
|
||||
except Exception as e:
|
||||
print(f"[Warning] Failed to load system config: {e}")
|
||||
|
||||
print("[Debug] Using default config.")
|
||||
return DEFAULT_CONFIG
|
||||
|
||||
config = load_config()
|
||||
|
||||
# Apply loaded config values
|
||||
VOLUME = config["volume"]
|
||||
MIC_NAME = config["mic_name"]
|
||||
AUDIO_OUTPUT_DEVICE = config["audio_output_device"]
|
||||
AUDIO_OUTPUT_DEVICE_INDEX = get_output_device_index(config["audio_output_device"])
|
||||
MODEL_NAME = config["model_name"]
|
||||
VOICE_MODEL = os.path.join("voices", config["voice"])
|
||||
ENABLE_AUDIO_PROCESSING = config["enable_audio_processing"]
|
||||
HISTORY_LENGTH = config["history_length"]
|
||||
|
||||
# Setup messages with system prompt
|
||||
messages = [{"role": "system", "content": config["system_prompt"]}]
|
||||
|
||||
list_input_devices()
|
||||
DEVICE_INDEX = get_input_device_index(config["mic_name"])
|
||||
|
||||
# 从设备获取采样率
|
||||
pa = pyaudio.PyAudio()
|
||||
device_info = pa.get_device_info_by_index(DEVICE_INDEX)
|
||||
INPUT_RATE = int(device_info['defaultSampleRate'])
|
||||
OUTPUT_RATE = int(device_info['defaultSampleRate'])
|
||||
pa.terminate()
|
||||
|
||||
CHUNK = 1024
|
||||
CHANNELS = 1
|
||||
mic_enabled = True
|
||||
|
||||
print(f"[Debug] Using sample rate: {INPUT_RATE} Hz")
|
||||
print(f"[Debug] Config loaded: model={MODEL_NAME}, voice={config['voice']}, vol={VOLUME}")
|
||||
|
||||
# ------------------- CONVERSATION STATE -------------------
|
||||
|
||||
audio_queue = queue.Queue()
|
||||
|
||||
# Audio callback
|
||||
def audio_callback(in_data, frame_count, time_info, status):
|
||||
global mic_enabled
|
||||
if not mic_enabled:
|
||||
return (None, pyaudio.paContinue)
|
||||
resampled_data = resample_audio(in_data, orig_rate=INPUT_RATE, target_rate=16000)
|
||||
audio_queue.put(resampled_data)
|
||||
return (None, pyaudio.paContinue)
|
||||
|
||||
# ------------------- STREAM SETUP -------------------
|
||||
|
||||
def start_stream():
|
||||
pa = pyaudio.PyAudio()
|
||||
|
||||
stream = pa.open(
|
||||
rate=INPUT_RATE, # 使用设备的默认采样率
|
||||
format=pyaudio.paInt16,
|
||||
channels=CHANNELS,
|
||||
input=True,
|
||||
input_device_index=DEVICE_INDEX,
|
||||
frames_per_buffer=CHUNK,
|
||||
stream_callback=audio_callback
|
||||
)
|
||||
stream.start_stream()
|
||||
print(f'[Debug] Stream @ {INPUT_RATE}Hz')
|
||||
return pa, stream
|
||||
|
||||
# ------------------- QUERY GLM API -------------------
|
||||
|
||||
def query_glm():
|
||||
headers = {
|
||||
'Authorization': 'Bearer ' + AUTH_TOKEN,
|
||||
'Content-Type': 'application/json'
|
||||
}
|
||||
payload = {
|
||||
"model": "glm-4.5",
|
||||
"messages": [messages[0]] + messages[-HISTORY_LENGTH:],
|
||||
"temperature": 0.6,
|
||||
"max_tokens": 1024,
|
||||
"stream": False
|
||||
}
|
||||
|
||||
with Timer("Inference"):
|
||||
try:
|
||||
resp = requests.post(CHAT_URL, json=payload, headers=headers)
|
||||
resp.raise_for_status()
|
||||
except requests.exceptions.RequestException as e:
|
||||
print(f"[Error] GLM API request failed: {e}")
|
||||
return ''
|
||||
|
||||
data = resp.json()
|
||||
reply = ''
|
||||
if 'choices' in data and len(data['choices']) > 0:
|
||||
choice = data['choices'][0]
|
||||
if 'message' in choice and 'content' in choice['message']:
|
||||
reply = choice['message']['content'].strip()
|
||||
return reply
|
||||
|
||||
# ------------------- TTS & DEGRADATION -------------------
|
||||
|
||||
def play_response(text):
|
||||
global mic_enabled
|
||||
mic_enabled = False
|
||||
|
||||
# clean the response
|
||||
clean = re.sub(r"[\*]+", '', text)
|
||||
clean = re.sub(r"\(.*?\)", '', clean)
|
||||
clean = re.sub(r"<.*?>", '', clean)
|
||||
clean = clean.replace('\n', ' ').strip()
|
||||
clean = re.sub(r'\s+', ' ', clean)
|
||||
clean = re.sub(r'[\U0001F300-\U0001FAFF\u2600-\u26FF\u2700-\u27BF]+', '', clean)
|
||||
|
||||
piper_path = os.path.join(BASE_DIR, 'bin', 'piper', 'piper')
|
||||
|
||||
if not os.path.exists(piper_path):
|
||||
print(f"[Error] Piper executable not found at {piper_path}")
|
||||
mic_enabled = True
|
||||
return
|
||||
|
||||
try:
|
||||
# Generate Piper raw PCM
|
||||
with Timer("Piper inference"):
|
||||
piper_proc = subprocess.Popen(
|
||||
[piper_path, '--model', VOICE_MODEL, '--output_raw'],
|
||||
stdin=subprocess.PIPE,
|
||||
stdout=subprocess.PIPE,
|
||||
stderr=subprocess.DEVNULL
|
||||
)
|
||||
tts_pcm, _ = piper_proc.communicate(input=clean.encode())
|
||||
|
||||
# Convert raw PCM to WAV for playback
|
||||
wav_io = io.BytesIO()
|
||||
with wave.open(wav_io, 'wb') as wf:
|
||||
wf.setnchannels(1)
|
||||
wf.setsampwidth(2)
|
||||
wf.setframerate(16000)
|
||||
wf.writeframes(tts_pcm)
|
||||
|
||||
wav_io.seek(0)
|
||||
wf = wave.open(wav_io, 'rb')
|
||||
|
||||
# Playback
|
||||
with Timer("Playback"):
|
||||
pa = pyaudio.PyAudio()
|
||||
stream = pa.open(
|
||||
format=pa.get_format_from_width(wf.getsampwidth()),
|
||||
channels=wf.getnchannels(),
|
||||
rate=wf.getframerate(),
|
||||
output=True,
|
||||
output_device_index=AUDIO_OUTPUT_DEVICE_INDEX
|
||||
)
|
||||
|
||||
data = wf.readframes(CHUNK)
|
||||
while data:
|
||||
stream.write(data)
|
||||
data = wf.readframes(CHUNK)
|
||||
|
||||
stream.stop_stream()
|
||||
stream.close()
|
||||
pa.terminate()
|
||||
wf.close()
|
||||
|
||||
except Exception as e:
|
||||
print(f"[Error] TTS playback failed: {e}")
|
||||
finally:
|
||||
mic_enabled = True
|
||||
time.sleep(0.3)
|
||||
|
||||
# ------------------- PROCESSING LOOP -------------------
|
||||
|
||||
def processing_loop():
|
||||
try:
|
||||
model = Model(MODEL_PATH)
|
||||
print("[Debug] Vosk model loaded successfully")
|
||||
except Exception as e:
|
||||
print(f"[Error] Failed to load Vosk model: {e}")
|
||||
print(f"[Info] Model path: {MODEL_PATH}")
|
||||
return
|
||||
|
||||
rec = KaldiRecognizer(model, 16000)
|
||||
MAX_DEBUG_LEN = 200
|
||||
LOW_EFFORT_UTTERANCES = {"huh", "uh", "um", "erm", "hmm", "he's", "but"}
|
||||
|
||||
while True:
|
||||
try:
|
||||
data = audio_queue.get()
|
||||
|
||||
if rec.AcceptWaveform(data):
|
||||
start = time.time()
|
||||
r = json.loads(rec.Result())
|
||||
elapsed_ms = int((time.time() - start) * 1000)
|
||||
|
||||
user = r.get('text', '').strip()
|
||||
if user:
|
||||
print(f"[Timing] STT parse: {elapsed_ms} ms")
|
||||
print("User:", user)
|
||||
|
||||
if user.lower().strip(".,!? ") in LOW_EFFORT_UTTERANCES:
|
||||
print("[Debug] Ignored low-effort utterance.")
|
||||
rec = KaldiRecognizer(model, 16000)
|
||||
continue
|
||||
|
||||
messages.append({"role": "user", "content": user})
|
||||
resp_text = query_glm()
|
||||
|
||||
if resp_text:
|
||||
clean_debug_text = resp_text.replace('\n', ' ').replace('\r', ' ')
|
||||
if len(clean_debug_text) > MAX_DEBUG_LEN:
|
||||
clean_debug_text = clean_debug_text[:MAX_DEBUG_LEN] + '...'
|
||||
|
||||
print('Assistant:', clean_debug_text)
|
||||
messages.append({"role": "assistant", "content": clean_debug_text})
|
||||
play_response(resp_text)
|
||||
else:
|
||||
print('[Debug] Empty response, skipping TTS.')
|
||||
|
||||
rec = KaldiRecognizer(model, 16000)
|
||||
|
||||
except Exception as e:
|
||||
print(f"[Error] Processing loop error: {e}")
|
||||
time.sleep(1)
|
||||
|
||||
# ------------------- MAIN -------------------
|
||||
|
||||
if __name__ == '__main__':
|
||||
try:
|
||||
pa, stream = start_stream()
|
||||
t = threading.Thread(target=processing_loop, daemon=True)
|
||||
t.start()
|
||||
|
||||
print("[Debug] Voice assistant started. Press Ctrl+C to exit.")
|
||||
while stream.is_active():
|
||||
time.sleep(0.1)
|
||||
|
||||
except KeyboardInterrupt:
|
||||
print("[Debug] Shutting down...")
|
||||
stream.stop_stream()
|
||||
stream.close()
|
||||
pa.terminate()
|
||||
except Exception as e:
|
||||
print(f"[Error] Main loop error: {e}")
|
||||
stream.stop_stream()
|
||||
stream.close()
|
||||
pa.terminate()
|
||||
Loading…
Reference in New Issue
Block a user