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66 lines
1.9 KiB
Python
66 lines
1.9 KiB
Python
import time
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import numpy as np
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import queue
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from queue import Queue
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import multiprocessing as mp
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class BaseASR:
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def __init__(self, opt, parent=None):
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self.opt = opt
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self.parent = parent
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self.fps = opt.fps # 20 ms per frame
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self.sample_rate = 16000
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self.chunk = self.sample_rate // self.fps # 320 samples per chunk (20ms * 16000 / 1000)
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self.queue = Queue()
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self.output_queue = mp.Queue()
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self.batch_size = opt.batch_size
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self.frames = []
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self.stride_left_size = opt.l
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self.stride_right_size = opt.r
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#self.context_size = 10
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self.feat_queue = mp.Queue(2)
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#self.warm_up()
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def pause_talk(self):
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self.queue.queue.clear()
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def put_audio_frame(self,audio_chunk): #16khz 20ms pcm
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self.queue.put(audio_chunk)
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def get_audio_frame(self):
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try:
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frame = self.queue.get(block=True,timeout=0.01)
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type = 0
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#print(f'[INFO] get frame {frame.shape}')
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except queue.Empty:
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if self.parent and self.parent.curr_state>1: #播放自定义音频
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frame = self.parent.get_audio_stream(self.parent.curr_state)
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type = self.parent.curr_state
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else:
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frame = np.zeros(self.chunk, dtype=np.float32)
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type = 1
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return frame,type
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def get_audio_out(self): #get origin audio pcm to nerf
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return self.output_queue.get()
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def warm_up(self):
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for _ in range(self.stride_left_size + self.stride_right_size):
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audio_frame,type=self.get_audio_frame()
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self.frames.append(audio_frame)
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self.output_queue.put((audio_frame,type))
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for _ in range(self.stride_left_size):
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self.output_queue.get()
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def run_step(self):
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pass
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def get_next_feat(self,block,timeout):
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return self.feat_queue.get(block,timeout) |