247 lines
7.9 KiB
Python
247 lines
7.9 KiB
Python
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"""Audio capture module for recording microphone or system audio."""
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import numpy as np
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import sounddevice as sd
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from scipy import signal
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from typing import Callable, Optional, List, Tuple
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from threading import Thread, Event
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import queue
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class AudioCapture:
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"""Captures audio from input devices and provides chunks for processing."""
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def __init__(
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self,
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sample_rate: int = 16000,
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chunk_duration: float = 3.0,
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device: Optional[int] = None
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):
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"""
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Initialize audio capture.
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Args:
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sample_rate: Target audio sample rate in Hz (16000 for Whisper)
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chunk_duration: Duration of each audio chunk in seconds
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device: Input device index, or None for default
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"""
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self.target_sample_rate = sample_rate
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self.chunk_duration = chunk_duration
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self.device = device
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self.chunk_size = int(sample_rate * chunk_duration)
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# Hardware sample rate (will be auto-detected)
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self.hardware_sample_rate = None
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self.audio_queue = queue.Queue()
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self.is_recording = False
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self.stop_event = Event()
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self.recording_thread: Optional[Thread] = None
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def _detect_sample_rate(self) -> int:
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"""
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Detect a supported sample rate for the audio device.
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Returns:
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Supported sample rate
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"""
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# Try common sample rates in order of preference
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common_rates = [self.target_sample_rate, 48000, 44100, 22050, 32000, 8000]
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for rate in common_rates:
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try:
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# Try to create a test stream
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with sd.InputStream(
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device=self.device,
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channels=1,
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samplerate=rate,
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blocksize=1024
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):
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print(f"Using hardware sample rate: {rate} Hz")
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return rate
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except sd.PortAudioError:
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continue
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# If nothing works, default to 48000
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print(f"Warning: Could not detect sample rate, defaulting to 48000 Hz")
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return 48000
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def _resample(self, audio: np.ndarray, from_rate: int, to_rate: int) -> np.ndarray:
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"""
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Resample audio from one sample rate to another.
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Args:
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audio: Input audio data
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from_rate: Source sample rate
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to_rate: Target sample rate
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Returns:
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Resampled audio
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"""
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if from_rate == to_rate:
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return audio
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# Calculate resampling ratio
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num_samples = int(len(audio) * to_rate / from_rate)
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# Use scipy's resample for high-quality resampling
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resampled = signal.resample(audio, num_samples)
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return resampled.astype(np.float32)
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@staticmethod
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def get_input_devices() -> List[Tuple[int, str]]:
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"""
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Get list of available input audio devices.
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Returns:
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List of (device_index, device_name) tuples
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"""
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devices = []
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device_list = sd.query_devices()
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for i, device in enumerate(device_list):
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# Only include devices with input channels
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if device['max_input_channels'] > 0:
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devices.append((i, device['name']))
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return devices
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@staticmethod
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def get_default_device() -> Optional[Tuple[int, str]]:
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"""
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Get the default input device.
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Returns:
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(device_index, device_name) tuple or None
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"""
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try:
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default_device = sd.query_devices(kind='input')
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device_list = sd.query_devices()
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for i, device in enumerate(device_list):
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if device['name'] == default_device['name']:
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return (i, device['name'])
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except:
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pass
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return None
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def _audio_callback(self, indata, frames, time_info, status):
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"""Callback function for sounddevice stream."""
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if status:
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print(f"Audio status: {status}")
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# Copy audio data to queue
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audio_data = indata.copy().flatten()
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self.audio_queue.put(audio_data)
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def start_recording(self, callback: Optional[Callable[[np.ndarray], None]] = None):
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"""
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Start recording audio.
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Args:
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callback: Optional callback function to receive audio chunks
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"""
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if self.is_recording:
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return
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# Detect supported sample rate
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self.hardware_sample_rate = self._detect_sample_rate()
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self.is_recording = True
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self.stop_event.clear()
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def record_loop():
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"""Recording loop that runs in a separate thread."""
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buffer = np.array([], dtype=np.float32)
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# Calculate hardware chunk size
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hardware_chunk_size = int(self.hardware_sample_rate * self.chunk_duration)
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try:
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with sd.InputStream(
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device=self.device,
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channels=1,
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samplerate=self.hardware_sample_rate,
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callback=self._audio_callback,
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blocksize=int(self.hardware_sample_rate * 0.1) # 100ms blocks
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):
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while not self.stop_event.is_set():
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try:
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# Get audio data from queue (with timeout)
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audio_chunk = self.audio_queue.get(timeout=0.1)
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buffer = np.concatenate([buffer, audio_chunk])
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# If we have enough data for a full chunk
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if len(buffer) >= hardware_chunk_size:
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# Extract chunk
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chunk = buffer[:hardware_chunk_size]
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buffer = buffer[hardware_chunk_size:]
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# Resample to target rate if needed
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if self.hardware_sample_rate != self.target_sample_rate:
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chunk = self._resample(
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chunk,
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self.hardware_sample_rate,
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self.target_sample_rate
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)
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# Send to callback if provided
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if callback:
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callback(chunk)
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except queue.Empty:
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continue
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except Exception as e:
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print(f"Error in recording loop: {e}")
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except Exception as e:
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print(f"Error opening audio stream: {e}")
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self.is_recording = False
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self.recording_thread = Thread(target=record_loop, daemon=True)
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self.recording_thread.start()
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def stop_recording(self):
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"""Stop recording audio."""
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if not self.is_recording:
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return
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self.is_recording = False
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self.stop_event.set()
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if self.recording_thread:
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self.recording_thread.join(timeout=2.0)
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self.recording_thread = None
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def get_audio_chunk(self, timeout: float = 1.0) -> Optional[np.ndarray]:
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"""
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Get the next audio chunk from the queue.
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Args:
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timeout: Maximum time to wait for a chunk
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Returns:
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Audio chunk as numpy array or None if timeout
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"""
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try:
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return self.audio_queue.get(timeout=timeout)
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except queue.Empty:
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return None
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def is_recording_active(self) -> bool:
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"""Check if recording is currently active."""
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return self.is_recording
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def clear_queue(self):
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"""Clear any pending audio chunks from the queue."""
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while not self.audio_queue.empty():
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try:
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self.audio_queue.get_nowait()
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except queue.Empty:
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break
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def __del__(self):
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"""Cleanup when object is destroyed."""
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self.stop_recording()
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