Update speech_processor.py
parent
c0c3c7405d
commit
b68e390d4c
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@ -2,120 +2,141 @@
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import vosk
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import sys
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import json
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import struct
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import numpy as np
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from queue import Queue
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from threading import Thread
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import soundfile as sf
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import tempfile
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import os
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import wave
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import soundfile as sf
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# Global model - load once
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model = None
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# Global recognizer
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recognizer = None
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audio_queue = Queue()
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result_queue = Queue()
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def initialize_vosk():
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"""Initialize Vosk model"""
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global model, recognizer
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global recognizer
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model_path = "vosk-model" # Update this path
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model_path = "/app/vosk-model"
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if not os.path.exists(model_path):
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return {"success": False, "error": "Vosk model not found at /app/vosk-model"}
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return {"success": False, "error": "Model not found"}
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try:
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vosk.SetLogLevel(-1) # Reduce log verbosity
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vosk.SetLogLevel(-1)
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model = vosk.Model(model_path)
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recognizer = vosk.KaldiRecognizer(model, 16000)
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return {"success": True}
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except Exception as e:
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return {"success": False, "error": f"Failed to initialize Vosk: {str(e)}"}
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return {"success": False, "error": str(e)}
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def process_audio_chunk(audio_data):
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"""Process audio data and return transcription"""
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def audio_worker():
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global recognizer
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while True:
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audio_data, request_id = audio_queue.get()
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if not recognizer:
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init_result = initialize_vosk()
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if not init_result["success"]:
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return init_result
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try:
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# Write audio data to temporary file
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with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as temp_file:
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temp_file.write(audio_data)
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temp_filename = temp_file.name
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# Read audio file with soundfile
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try:
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audio_data, sample_rate = sf.read(temp_filename)
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# Write to temp file and read with soundfile
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with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as f:
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f.write(audio_data)
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temp_path = f.name
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# Convert to 16-bit PCM at 16kHz if needed
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if sample_rate != 16000:
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# Simple resampling (for better quality, use librosa)
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import numpy as np
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audio_data = np.interp(
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np.linspace(0, len(audio_data), int(len(audio_data) * 16000 / sample_rate)),
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np.arange(len(audio_data)),
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audio_data
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)
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try:
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data, samplerate = sf.read(temp_path, dtype='float32')
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# Convert to bytes
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audio_bytes = (audio_data * 32767).astype('int16').tobytes()
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# Resample if needed
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if samplerate != 16000:
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duration = len(data) / samplerate
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data = np.interp(
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np.linspace(0, len(data)-1, int(duration * 16000)),
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np.arange(len(data)),
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data
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)
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# Process with Vosk
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if recognizer.AcceptWaveform(audio_bytes):
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result = json.loads(recognizer.Result())
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text = result.get('text', '')
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else:
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result = json.loads(recognizer.PartialResult())
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text = result.get('partial', '')
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# Convert to 16-bit PCM
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data = (data * 32767).astype('int16')
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# Clean up
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os.unlink(temp_filename)
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# Process with Vosk
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if recognizer.AcceptWaveform(data.tobytes()):
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text = json.loads(recognizer.Result()).get('text', '')
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is_final = True
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else:
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text = json.loads(recognizer.PartialResult()).get('partial', '')
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is_final = False
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return {"success": True, "text": text}
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result_queue.put(({
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"success": True,
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"text": text,
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"is_final": is_final,
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"requestId": request_id
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}, request_id))
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finally:
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os.unlink(temp_path)
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except Exception as e:
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os.unlink(temp_filename)
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return {"success": False, "error": f"Audio processing error: {str(e)}"}
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except Exception as e:
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return {"success": False, "error": f"General error: {str(e)}"}
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result_queue.put(({
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"success": False,
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"error": str(e),
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"requestId": request_id
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}, request_id))
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def main():
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"""Main loop to process audio chunks from stdin"""
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# Initialize Vosk on startup
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# Initialize Vosk
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init_result = initialize_vosk()
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if not init_result["success"]:
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error_response = json.dumps(init_result).encode('utf-8')
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sys.stdout.buffer.write(len(error_response).to_bytes(4, byteorder='big'))
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sys.stdout.buffer.write(error_response)
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error = json.dumps({
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"success": False,
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"error": init_result["error"],
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"requestId": 0
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}).encode()
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sys.stdout.buffer.write(struct.pack('>I', len(error)))
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sys.stdout.buffer.write(error)
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sys.stdout.buffer.flush()
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sys.exit(1)
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return
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# Start worker thread
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Thread(target=audio_worker, daemon=True).start()
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while True:
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try:
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# Read length of incoming data
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length_data = sys.stdin.buffer.read(4)
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if not length_data:
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# Read message length (4 bytes)
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length_bytes = sys.stdin.buffer.read(4)
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if not length_bytes:
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break
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length = struct.unpack('>I', length_bytes)[0]
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length = int.from_bytes(length_data, byteorder='big')
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# Read request ID (4 bytes)
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id_bytes = sys.stdin.buffer.read(4)
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if not id_bytes:
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break
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request_id = struct.unpack('>I', id_bytes)[0]
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# Read audio data
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audio_data = sys.stdin.buffer.read(length)
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if len(audio_data) != length:
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break
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# Process audio
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result = process_audio_chunk(audio_data)
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# Add to processing queue
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audio_queue.put((audio_data, request_id))
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# Send result back
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response = json.dumps(result).encode('utf-8')
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sys.stdout.buffer.write(len(response).to_bytes(4, byteorder='big'))
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sys.stdout.buffer.write(response)
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sys.stdout.buffer.flush()
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# Check for results
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while not result_queue.empty():
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result, res_id = result_queue.get()
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response = json.dumps(result).encode()
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sys.stdout.buffer.write(struct.pack('>I', len(response)))
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sys.stdout.buffer.write(struct.pack('>I', res_id)))
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sys.stdout.buffer.write(response)
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sys.stdout.buffer.flush()
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except Exception as e:
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error_result = {"success": False, "error": str(e)}
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response = json.dumps(error_result).encode('utf-8')
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sys.stdout.buffer.write(len(response).to_bytes(4, byteorder='big'))
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sys.stdout.buffer.write(response)
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error = json.dumps({
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"success": False,
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"error": str(e),
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"requestId": request_id if 'request_id' in locals() else 0
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}).encode()
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sys.stdout.buffer.write(struct.pack('>I', len(error)))
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sys.stdout.buffer.write(error)
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sys.stdout.buffer.flush()
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if __name__ == "__main__":
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