import numpy as np
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from funasr.utils.job_runner import MultiProcessRunnerV3
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from funasr.utils.misc import load_scp_as_list, load_scp_as_dict
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import os
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import librosa
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import soundfile as sf
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import argparse
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class MyRunner(MultiProcessRunnerV3):
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def prepare(self, parser):
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parser.add_argument("dir", type=str)
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parser.add_argument("out_dir", type=str)
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args = parser.parse_args()
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assert args.sr == 8000, "For callhome dataset, the sample rate should be 8000, use --sr 8000."
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if not os.path.exists(args.out_dir):
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os.makedirs(args.out_dir)
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print("loading data...")
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wav_scp = load_scp_as_dict(os.path.join(args.dir, "wav.scp"))
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utt2spk = load_scp_as_dict(os.path.join(args.dir, "utt2spk"))
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spk2utt = {}
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count = 0
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for utt, spk in utt2spk.items():
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if utt in wav_scp:
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if spk not in spk2utt:
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spk2utt[spk] = []
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spk2utt[spk].append(utt)
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count += 1
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task_list = spk2utt.keys()
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print("total: {} speakers, {} utterances".format(len(spk2utt), count))
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print("starting jobs...")
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return task_list, [spk2utt, wav_scp], args
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def post(self, results_list, args):
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pass
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def process(task_args):
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_, task_list, [spk2utt, wav_scp], args = task_args
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for spk in task_list:
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spk_wav_list = []
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for utt in spk2utt[spk]:
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wav = librosa.load(wav_scp[utt], sr=args.sr, mono=True)[0] * 32767
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spk_wav_list.append(wav)
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sig = np.concatenate(spk_wav_list, axis=0)
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save_path = os.path.join(args.out_dir, "{}.wav".format(spk))
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sf.write(save_path, sig.astype(np.int16), args.sr, "PCM_16", "LITTLE", "WAV", True)
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return None
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if __name__ == '__main__':
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my_runner = MyRunner(process)
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my_runner.run()
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